From fab65f9be43f3f4dd0154020c625d92e8acd2462 Mon Sep 17 00:00:00 2001 From: RanZheng <364167184@qq.com> Date: Thu, 13 Mar 2025 11:00:42 +0800 Subject: [PATCH 001/750] =?UTF-8?q?monitor=20mg=5Fdirection=E3=80=81?= =?UTF-8?q?=E5=8A=A8=E6=80=81=E5=90=AF=E5=81=9C=E8=B5=84=E6=96=99=E6=9B=B4?= =?UTF-8?q?=E6=96=B0,=20dump=E8=B5=84=E6=96=99=E8=A1=A5=E5=85=85=E8=BF=9B?= =?UTF-8?q?=E7=A8=8B=E8=AF=B4=E6=98=8E?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../msprobe/docs/05.data_dump_PyTorch.md | 2 ++ debug/accuracy_tools/msprobe/docs/19.monitor.md | 11 +++++++---- 2 files changed, 9 insertions(+), 4 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md index be9386df1..6aea3126b 100644 --- a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md @@ -34,6 +34,8 @@ level 配置为"L0"或"mix"时，必须在该接口或 **start** 接口中配置 此接口的参数均不是必要，且优先级高于 [config.json](../config.json) 文件中的配置，但可配置的参数相比 config.json 较少。 +注：此接口的初始化需与采集目标在同一个进程中，否则将无法采集目标数据。 + ### 1.2 start **功能说明**：启动精度数据采集。在模型初始化之后的位置添加。需要与 stop 函数一起添加在 for 循环内。 diff --git a/debug/accuracy_tools/msprobe/docs/19.monitor.md b/debug/accuracy_tools/msprobe/docs/19.monitor.md index fa1b7d06d..c37031bbb 100644 --- a/debug/accuracy_tools/msprobe/docs/19.monitor.md +++ b/debug/accuracy_tools/msprobe/docs/19.monitor.md @@ -427,17 +427,17 @@ csv2tensorboard_by_step( ### 动态启停 动态启停模式：支持用户在训练过程中随时启动/更新监控。 -用户可在训练开始前通过配置环境变量DYNAMIC_MONITOR=True来确认开启动态启停模式，该模式下需要配合config.json文件中的dynamic_on字段来使用。 +用户可在训练开始前通过配置环境变量DYNAMIC_MONITOR=True来确认进入动态启停模式，该模式下需要配合config.json文件中的dynamic_on字段来使用。 在动态启停模式下，启动和停止分别由如下控制： - 启动： - 首次监控：config.json文件中dynamic_on字段为true，代表是否需要开启监控。 - 非首次监控：config文件时间戳更新且config.json文件中dynamic_on字段为true。 + 首次监控：查看config.json文件中dynamic_on字段，若为true则在下一步开启监控。 + 非首次监控：查看config文件时间戳，若时间戳更新且config.json文件中dynamic_on字段为true则在下一步开启监控。 - 停止： 到达collect_times之后自动停止并改config.json文件中dynamic_on字段为false，可再通过上述操作重启。 -大部分情况下，用户可在看到异常趋势后再手动更新config.json文件并打开dynamic_on开关；此外，使用时若想要在一开始就启动监控，可直接打开dynamic_on开关做基础配置的监测（首次不要求时间戳更新） +大部分情况下，用户可在看到异常趋势后再手动更新config.json文件并设dynamic_on为true；此外，使用时若想要在一开始就启动监控，可直接设dynamic_on为true做基础配置的监测（首次不要求时间戳更新） 注意事项： @@ -445,6 +445,7 @@ csv2tensorboard_by_step( - config中途修改出错时，若此时不在监控就不生效，若在监控则用原配置继续。 - 达到collect_times之后会自动将该值置为false待下次改true重启。 + ### 功能重载 此功能将在2026年废弃。请使用[动态启停](#动态启停)功能代替。 @@ -601,6 +602,7 @@ TrainerMon.monitor_gnorm_with_ad(model, grad_acc_steps, optimizer, dp_group, tp_ | "param_distribution" | 可选 | 若为true则会监控指定模块的参数， 默认为false。 | | "alert" | 可选 | "rules": 指定自动报警的异常检测机制及其相应的阈值。目前实现的异常检测是AnomalyTurbulence， 如果统计标量超出历史均值的指定浮动范围（threshold 0.5意味着上浮或者下浮50%）则在控制台打印报警信息。当"dump"字段配置为true表示异常事件写入文件，默认为false。**仅PyTorch场景支持此参数**。 | | "cc_distribution" | 可选 | 其中"enable"字段控制通信监控模块的开关；需要监控通信算子时，务必尽量早地实例化`TrainerMon`, 因为监控通过劫持原始func后挂hook实现，部分加速库初始化时会保存原始function，避免监控失效。"cc_codeline"字段指定监控的代码行，如:`train.py\\[23\\]`，默认为空列表，不特别指定；"cc_pre_hook"字段控制是否监控通信前的数据； 模块会在第二个optimize.step之前打印通信日志，包括通信api的调用栈、输入dtype、通信group。 "cc_log_only"为true时，仅打印日志，不监控通信的输入输出，并在打印后中断训练。可以根据通信日志设置"cc_codeline"，规避与训练过程不相关的通信，比如一些时间、metrics的同步。 | +| "mg_direction" | 可选 | 若为true则会计算权重梯度和动量方向一致的比例，默认为false。 | | "format" | 可选 | 数据落盘格式，默认值为"csv"，可选 \["csv", "tensorboard", "api"\]。仅PyThon和MindSpore动态图场景支持此参数，且MindSpore动态图场景仅支持\["csv"\]。 | | "ops" | 可选 | 类型为list，与ur_distribution、xy_distribution、mv_distribution、wg_distribution、mg_direction、cc_distribution配合，监控所选张量的统计指标，目前支持"min"、"max"、"norm"、"mean"、"zeros"、"nans"。其中，zeros代表监控所选张量的元素小于eps的比例，nans代表张量中nan的数量。当ops中无有效指标时，默认监控norm指标。 | | "eps" | 可选 | 若ops里包含"zeros"则需要配置，默认为1e-8。 | @@ -608,3 +610,4 @@ TrainerMon.monitor_gnorm_with_ad(model, grad_acc_steps, optimizer, dp_group, tp_ | "step_count_per_record" | 可选 | "format"为"csv"时生效，每个csv记录多少个step的数据，默认为1。 | | "append_output" | 可选 | 适用于断点续训场景。多卡场景下生效，指定两个时间戳，将输出续写到这两个时间戳范围间的输出件中，不在范围内的rank不被续写。时间戳应来自原有输出件目录前缀，例如["Dec03_21-34-40", "Dec03_21-34-41"]。默认为[]，不续写。**仅PyTorch场景支持此参数**。 | | "squash_name" | 可选 | 是否简化参数名/模块名，多模态场景建议关闭，默认为True | + -- Gitee From b6eb00e194bb39fafd6558a843db680f2601856c Mon Sep 17 00:00:00 2001 From: l30044004 Date: Fri, 14 Mar 2025 11:08:11 +0800 Subject: [PATCH 002/750] =?UTF-8?q?=E5=88=86=E7=BA=A7=E5=8F=AF=E8=A7=86?= =?UTF-8?q?=E5=8C=96=E8=B5=84=E6=96=99=E6=9B=B4=E6=96=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../msprobe/docs/21.visualization_PyTorch.md | 45 +++++++++++++----- .../docs/22.visualization_MindSpore.md | 41 +++++++++++----- .../docs/img/visualization/vis_browser_1.png | Bin 41972 -> 68523 bytes .../docs/img/visualization/vis_match_info.png | Bin 0 -> 280858 bytes .../img/visualization/vis_precision_info.png | Bin 239937 -> 336696 bytes .../img/visualization/vis_search_info.png | Bin 213098 -> 272737 bytes .../docs/img/visualization/vis_show_info.png | Bin 243284 -> 223862 bytes .../docs/img/visualization/vis_showcase.png | Bin 204204 -> 223952 bytes .../img/visualization/vis_unmatch_info.png | Bin 205630 -> 219915 bytes 9 files changed, 62 insertions(+), 24 deletions(-) create mode 100644 debug/accuracy_tools/msprobe/docs/img/visualization/vis_match_info.png diff --git a/debug/accuracy_tools/msprobe/docs/21.visualization_PyTorch.md b/debug/accuracy_tools/msprobe/docs/21.visualization_PyTorch.md index 34cdc2aa9..eae2b9fb1 100644 --- a/debug/accuracy_tools/msprobe/docs/21.visualization_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/21.visualization_PyTorch.md @@ -4,20 +4,32 @@ 工具支持PyTorch版本：2.1/2.2 -## 展示示例 +## 更新通知 -支持重建模型的层级结构； +请注意，tb_graph_ascend插件已于2025/3/12更新到1.0.0版本，如果当前环境已安装旧版本插件，推荐升级。 -支持两个模型的结构差异比对； +更新内容如下： -支持两个模型的精度数据比对，支持疑似有精度问题节点的快速搜索，自动跳转展开节点所在的层级。 +- 优化了信息栏，使用了更人性化、更美观的展示界面； +- 提升了节点渲染和搜索性能； +- 双图比对场景画布分离，操作左图时不会影响到右图； +- 新增浏览器匹配节点功能，双图比对场景有未匹配节点时，可通过在浏览器页面手动选中调试侧和标杆侧的未匹配节点进行精度比对； +- 新增颜色图例可配置功能。 + +## 工具特性 + +- 支持重建模型的层级结构； +- 支持两个模型的结构差异比对； +- 支持两个模型的精度数据比对； +- 支持模型数据的溢出检测； +- 支持多卡场景的批量构图，能够关联各卡的通信节点，分析各卡之间的数据传递； +- 支持节点名称搜索，按精度比对结果筛选节点，按溢出检测结果筛选节点，支持自动跳转展开节点所在的层级； +- 支持跨套件、跨框架的模型比对。 ![vis_show](./img/visualization/vis_showcase.png) ## 1.依赖安装 -分级可视化工具依赖**msprobe工具**和**tensorboard。** - ### 1.1 安装msprobe工具 [msprobe工具安装](https://gitee.com/ascend/mstt/blob/master/debug/accuracy_tools/msprobe/docs/01.installation.md) @@ -28,6 +40,8 @@ ``pip3 install tb-graph-ascend``即可。 +如需升级工具，请先``pip3 uninstall tb-graph-ascend``再``pip3 install tb-graph-ascend``即可。 + ## 2.模型结构数据采集 [PyTorch场景的数据采集](https://gitee.com/ascend/mstt/blob/master/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md) @@ -357,15 +371,16 @@ tensorboard --logdir out_path ![vis_precision_info.png](./img/visualization/vis_precision_info.png) ### 5.5 未匹配节点筛选 -节点匹配规则： -1.名称一致 +参考[匹配说明](#311-匹配说明) ，不符合匹配规则的节点为无匹配节点，颜色标灰。适用于排查两个模型结构差异的场景。 -2.节点输入输出参数数量一致，参数type、shape一致 +![vis_unmatch_info.png](./img/visualization/vis_unmatch_info.png) -3.节点的层级一致（父节点们一致） +### 5.6 手动选择节点匹配 -![vis_unmatch_info.png](./img/visualization/vis_unmatch_info.png) +可通过浏览器界面，通过鼠标选择两个待匹配的灰色节点进行匹配。当前暂不支持真实数据模式。 + +![vis_match_info.png](./img/visualization/vis_match_info.png) ## 6.图比对说明 @@ -472,5 +487,9 @@ yaml文件中只需配置待调试侧与标杆侧模型代码中功能一致但 节点呈现灰色，代表左边待调试侧节点与右边标杆侧节点没有匹配上，可能有以下几点原因： - **标杆侧确实没有能与待调试侧匹配上的节点**，属于代码实现上的差异，请确认此差异是否正常，是否会影响到整网精度。 -- **节点的输入或输出type、shape不一致，参数个数不一致，节点所在层级的父层级不一致**，导致节点无法匹配，具体匹配规则见[匹配说明](#311-匹配说明)，可尝试使用模糊匹配功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)。如果是参数shape不一致，即使是模糊匹配功能也无法让节点匹配上，请检查参数shape不一致是否合理。 -- **节点名称不一致**，导致节点无法匹配，可使用layer mapping功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)，如何自定义映射文件请参考[模型分级可视化如何配置layer mapping映射文件](./visualization/layer_mapping_example.md)。 +- **节点名称一致，但节点的输入或输出type、shape不一致，参数个数不一致，节点所在层级的父层级不一致，导致节点无法匹配** + - 具体匹配规则见[匹配说明](#311-匹配说明)，可尝试使用模糊匹配功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)； + - 如果是参数shape不一致，即使是模糊匹配功能也无法让节点匹配上，请检查参数shape不一致是否合理。 +- **节点名称不一致**，导致节点无法匹配，目前提供两种方法，选其一即可 + - 可使用layer mapping功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)，如何自定义映射文件请参考[模型分级可视化如何配置layer mapping映射文件](./visualization/layer_mapping_example.md)； + - 可通过浏览器页面手动选择未匹配节点进行匹配，请参考[手动选择节点匹配](#56-手动选择节点匹配)。 diff --git a/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md b/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md index 12306b8be..46c262c3e 100644 --- a/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md +++ b/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md @@ -4,13 +4,27 @@ 工具支持MindSpore版本：2.4.0 -## 展示示例 +## 更新通知 -支持重建模型的层级结构； +请注意，tb_graph_ascend插件已于2025/3/12更新到1.0.0版本，如果当前环境已安装旧版本插件，推荐升级。 -支持两个模型的结构差异比对； +更新内容如下： -支持两个模型的精度数据比对，支持疑似有精度问题节点的快速搜索，自动跳转展开节点所在的层级。 +- 优化了信息栏，使用了更人性化、更美观的展示界面； +- 提升了节点渲染和搜索性能； +- 双图比对场景画布分离，操作左图时不会影响到右图； +- 新增浏览器匹配节点功能，双图比对场景有未匹配节点时，可通过在浏览器页面手动选中调试侧和标杆侧的未匹配节点进行精度比对； +- 新增颜色图例可配置功能。 + +## 工具特性 + +- 支持重建模型的层级结构； +- 支持两个模型的结构差异比对； +- 支持两个模型的精度数据比对； +- 支持模型数据的溢出检测； +- 支持多卡场景的批量构图，能够关联各卡的通信节点，分析各卡之间的数据传递； +- 支持节点名称搜索，按精度比对结果筛选节点，按溢出检测结果筛选节点，支持自动跳转展开节点所在的层级； +- 支持跨套件、跨框架的模型比对。 ![vis_show](./img/visualization/vis_showcase.png) @@ -359,15 +373,16 @@ tensorboard --logdir out_path ![vis_precision_info.png](./img/visualization/vis_precision_info.png) ### 5.5 未匹配节点筛选 -节点匹配规则： -1.名称一致 +参考[匹配说明](#311-匹配说明) ，不符合匹配规则的节点为无匹配节点，颜色标灰。适用于排查两个模型结构差异的场景。 -2.节点输入输出参数数量一致，参数type、shape一致 +![vis_unmatch_info.png](./img/visualization/vis_unmatch_info.png) -3.节点的层级一致（父节点们一致） +### 5.6 手动选择节点匹配 -![vis_unmatch_info.png](./img/visualization/vis_unmatch_info.png) +可通过浏览器界面，通过鼠标选择两个待匹配的灰色节点进行匹配。当前暂不支持真实数据模式。 + +![vis_match_info.png](./img/visualization/vis_match_info.png) ## 6.图比对说明 @@ -488,5 +503,9 @@ yaml文件中只需配置MindSpore与PyTorch模型代码中功能一致但名称 节点呈现灰色，代表左边待调试侧节点与右边标杆侧节点没有匹配上，可能有以下几点原因： - **标杆侧确实没有能与待调试侧匹配上的节点**，属于代码实现上的差异，请确认此差异是否正常，是否会影响到整网精度。 -- **节点的输入或输出type、shape不一致，参数个数不一致，节点所在层级的父层级不一致**，导致节点无法匹配，具体匹配规则见[匹配说明](#311-匹配说明)，可尝试使用模糊匹配功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)。如果是参数shape不一致，即使是模糊匹配功能也无法让节点匹配上，请检查参数shape不一致是否合理。 -- **节点名称不一致**，导致节点无法匹配，可使用layer mapping功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)，如何自定义映射文件请参考[模型分级可视化如何配置layer mapping映射文件](./visualization/layer_mapping_example.md)。 +- **节点名称一致，但节点的输入或输出type、shape不一致，参数个数不一致，节点所在层级的父层级不一致，导致节点无法匹配** + - 具体匹配规则见[匹配说明](#311-匹配说明)，可尝试使用模糊匹配功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)； + - 如果是参数shape不一致，即使是模糊匹配功能也无法让节点匹配上，请检查参数shape不一致是否合理。 +- **节点名称不一致**，导致节点无法匹配，目前提供两种方法，选其一即可 + - 可使用layer mapping功能，如何使用此功能请参考[构图命令行说明](#31-构图命令行说明)，如何自定义映射文件请参考[模型分级可视化如何配置layer mapping映射文件](./visualization/layer_mapping_example.md)； + - 可通过浏览器页面手动选择未匹配节点进行匹配，请参考[手动选择节点匹配](#56-手动选择节点匹配)。 diff --git a/debug/accuracy_tools/msprobe/docs/img/visualization/vis_browser_1.png b/debug/accuracy_tools/msprobe/docs/img/visualization/vis_browser_1.png index 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zRy3F(e;6SC-`EwF+lv|WicCy(DC%+y(-YnTlM#c0n?JhWpCm2Fqx(qI+yURhcBPwN z@ML2U*oN=9e}Fte=F?@L|1J!Gubu=#;7e046WB-+NY$dL!dHEI1=HdTtpPU36!O8v zN3Ks>Sc)SuO?(1+z)n@|2av%pXO6y>#}ZxRwY?3|qH z-dFb4i$8t*b}ll6H$vwQf^=J#JwLabz$B9}6P*~4EzCk09OMS7v0@%Usypk_=0op zHtDt%gJDIj78QE5({r0=`Is8e^T5R=CG+v0fuR?!*?(o51Jj@LDk>^?QbM!U{wJIO z5cLq^3(!vje&*6VNpIU!s(T8k!P@-0^T(+Wua2>R;lbojzT4xM(^V+99>N`2ultWu zvJcFB`Ns7+S=fDC;Uq91d13!^rpO<u^p47X4SQRx55xO@qMY<5Z5V*=K3fc@OH*XYKP*mlR!p0tf8#Bzt7iD1e0y3r=%kK*gEY~g>e zy3n6tkf!y&^?!Xw$gTh1`uQh&{NF#H6vCvBwLE^9`piOvXTlCm10Kz{|Ao0@4^58 -- Gitee From 14fbaea7a15963a429edc5053cdc4e01b689c55d Mon Sep 17 00:00:00 2001 From: l30044004 Date: Fri, 14 Mar 2025 11:13:31 +0800 Subject: [PATCH 003/750] =?UTF-8?q?=E5=88=86=E7=BA=A7=E5=8F=AF=E8=A7=86?= =?UTF-8?q?=E5=8C=96=E8=B5=84=E6=96=99=E6=9B=B4=E6=96=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../accuracy_tools/msprobe/docs/22.visualization_MindSpore.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md b/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md index 46c262c3e..40775ed5e 100644 --- a/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md +++ b/debug/accuracy_tools/msprobe/docs/22.visualization_MindSpore.md @@ -30,8 +30,6 @@ ## 1.依赖安装 -分级可视化工具依赖**msprobe工具**和**tensorboard。** - ### 1.1 安装msprobe工具 [msprobe工具安装](https://gitee.com/ascend/mstt/blob/master/debug/accuracy_tools/msprobe/docs/01.installation.md) @@ -42,6 +40,8 @@ ``pip3 install tb-graph-ascend``即可。 +如需升级工具，请先``pip3 uninstall tb-graph-ascend``再``pip3 install tb-graph-ascend``即可。 + ## 2.模型结构数据采集 [MindSpore场景的精度数据采集](https://gitee.com/ascend/mstt/blob/master/debug/accuracy_tools/msprobe/docs/06.data_dump_MindSpore.md) -- Gitee From 3333c838348c14f3c334d2ad8c7d54ce9fc489ee Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 17 Mar 2025 16:52:53 +0800 Subject: [PATCH 004/750] stremalined stack --- .../msprobe/core/data_dump/data_processor/base.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/base.py b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/base.py index 775a80b24..1588b39bf 100644 --- a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/base.py +++ b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/base.py @@ -129,6 +129,8 @@ class BaseDataProcessor: for (_, path, line, func, code, _) in api_stack: if not code: continue + if "msprobe" in path: + continue stack_line = f"File {path}, line {str(line)}, in {func}, \n {code[0].strip()}" stack_str.append(stack_line) else: -- Gitee From 528db8dbbd24b19f8d6691a8ff85177495d328b2 Mon Sep 17 00:00:00 2001 From: yangxinxian <947098055@qq.com> Date: Tue, 18 Mar 2025 10:51:30 +0800 Subject: [PATCH 005/750] =?UTF-8?q?=E5=88=A0=E9=99=A4=E5=86=97=E4=BD=99?= =?UTF-8?q?=E4=BB=A3=E7=A0=81?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../bench_functions/flash_attention_score.py | 61 ------------------- .../mindspore/code_mapping/graph_parser.py | 18 ------ 2 files changed, 79 deletions(-) diff --git a/debug/accuracy_tools/msprobe/mindspore/api_accuracy_checker/bench_functions/flash_attention_score.py b/debug/accuracy_tools/msprobe/mindspore/api_accuracy_checker/bench_functions/flash_attention_score.py index cb268efea..c5adc9842 100644 --- a/debug/accuracy_tools/msprobe/mindspore/api_accuracy_checker/bench_functions/flash_attention_score.py +++ b/debug/accuracy_tools/msprobe/mindspore/api_accuracy_checker/bench_functions/flash_attention_score.py @@ -230,67 +230,6 @@ def convert_to_bnsd(_input, n, input_layout): return out.to(GTYPE) -def convert_from_bsnd(_input, input_layout): - """ - transform qkv from bsnd to input_layout. - B: batch_size - S: sequence_length - N: num_heads - D: head_dim - Args: - _input (torch.Tensor): tensor of shape (B,S,N,D) - input_layout (str): "BSH" or "SBH" or "BSND" or "BNSD" or "TND" - Returns: - tensor of shape (B,N,S,D) or (B,S,N,D) or (S,B,H) or (B,S,H) - """ - if input_layout == "BSH": - # (B,S,N,D)=>(B,S,N*D) - out = rearrange(_input, 'b s n d -> b s (n d)').contiguous() - elif input_layout == "SBH": - # (B,S,N,D)=>(S,B,N*D) - out = rearrange(_input, 'b s n d -> s b (n d)').contiguous() - elif input_layout == "BNSD": - # (B,S,N,D)=>(B,N,S,D) - out = rearrange(_input, 'b s n d -> b n s d').contiguous() - elif input_layout == "TND": - raise ValueError(f"input_layout {input_layout} does not supported for now.") - else: - out = _input - return out - - -def convert_to_bsnd(_input, n, input_layout): - """ - transform qkv from input_layout to bsnd. - B: batch_size - S: sequence_length - N: num_heads - D: head_dim - Args: - _input (torch.Tensor): tensor of shape (B,N,S,D) or (B,S,N,D) or (S,B,H) or (B,S,H) - n (int): num_heads - input_layout (str):"BSH" or "SBH" or "BSND" or "BNSD" or "TND" - Returns: - tensor of shape (B,S,N,D) - """ - if input_layout == "BSH": - # (B,S,N*D)=>(B,S,N,D) - out = rearrange(_input, 'b s (n d) -> b s n d', n=n) - elif input_layout == "SBH": - # (S,B,N*D)=>(B,S,N,D) - out = rearrange(_input, 's b (n d) -> b s n d', n=n) - elif input_layout == "BNSD": - # (B,N,S,D)=>(B,S,N,D) - out = rearrange(_input, 'b n s d -> b s n d', n=n) - elif input_layout == "TND": - raise ValueError(f"input_layout {input_layout} does not supported for now.") - else: - out = _input - if out.dim() != 4: - raise ValueError(f"convert qkv format failed with input_layout {input_layout}.") - return out - - def generate_attn_mask(*args): """ # 当sparse_mode=2、3、4时小算子到融合算子会走这个优化，反过来看就要拆解回原来的基本实现 diff --git a/debug/accuracy_tools/msprobe/mindspore/code_mapping/graph_parser.py b/debug/accuracy_tools/msprobe/mindspore/code_mapping/graph_parser.py index ee35750fb..262e3b6fe 100644 --- a/debug/accuracy_tools/msprobe/mindspore/code_mapping/graph_parser.py +++ b/debug/accuracy_tools/msprobe/mindspore/code_mapping/graph_parser.py @@ -34,19 +34,6 @@ class Parser: if isinstance(subgraph_node.attrs, list): subgraph_node.attrs.extend(attrs) - @staticmethod - def parse_graph_attributes(text: str, graph_node: GraphNode) -> None: - attr_pattern = re.compile(r'# Attrs:\s*(.*)', re.DOTALL) - match = attr_pattern.search(text, graph_node.pos) - if match: - attrs = match.group(1).strip().split('\n') - for attr in attrs: - if not attr: - break - key, value = attr.split(':') - if isinstance(graph_node.attrs, dict): - graph_node.attrs[key.strip()] = value.strip() - @staticmethod def parse_code_info(text: str, start_pos: int, end_pos: int) -> List[str]: code_info = [] @@ -203,11 +190,6 @@ class Parser: subgraph_info.end = end_pos logging.info('Parsed subgraph: %s', subgraph_name) - def count_nodes(self) -> Tuple[int, int]: - total_nodes = len(self.nodes) - total_cnodes = sum(1 for node in self.nodes.values() if node.name.startswith('CNode')) - return total_nodes, total_cnodes - def create_backward_map(self): for node in self.nodes.values(): if node.scope and node.scope.startswith("Gradients"): -- Gitee From 29f53e59fee0bf1b1be3fb4c1df6b899bca8c81b Mon Sep 17 00:00:00 2001 From: qiange Date: Wed, 19 Mar 2025 10:21:44 +0800 Subject: [PATCH 006/750] fix bug for ds stage opt attr error --- .../accuracy_tools/msprobe/pytorch/monitor/optimizer_collect.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/optimizer_collect.py b/debug/accuracy_tools/msprobe/pytorch/monitor/optimizer_collect.py index 131f3ecab..8c5faaa15 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/optimizer_collect.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/optimizer_collect.py @@ -224,7 +224,7 @@ class DeepSpeedZeroOptimizerStage0Mon(OptimizerMon): param_slice_mappings = torch_opt.state_dict()['param_slice_mappings'] for param, name in params2name.items(): group_idx = param2group[param] - state = torch_opt.state[torch_opt.fp32_groups_flat_partition[group_idx]] + state = torch_opt.optimizer.state[torch_opt.fp32_groups_flat_partition[group_idx]] if state.get('exp_avg', None) is None: logger.warning(f"optimizer state is None. Something is wrong if this is not the first step") break -- Gitee From eb80b6c97e29f3dccd7f89b3f2fb1e40f2d730f7 Mon Sep 17 00:00:00 2001 From: Linwei-Ying Date: Wed, 19 Mar 2025 14:15:50 +0800 Subject: [PATCH 007/750] compare remove files add warning --- debug/accuracy_tools/msprobe/core/compare/acc_compare.py | 4 +++- .../msprobe/core/compare/merge_result/merge_result.py | 9 +++++++-- 2 files changed, 10 insertions(+), 3 deletions(-) diff --git a/debug/accuracy_tools/msprobe/core/compare/acc_compare.py b/debug/accuracy_tools/msprobe/core/compare/acc_compare.py index f2aa8c479..bd4126a88 100644 --- a/debug/accuracy_tools/msprobe/core/compare/acc_compare.py +++ b/debug/accuracy_tools/msprobe/core/compare/acc_compare.py @@ -430,7 +430,9 @@ class Comparator: logger.info("Please check whether the input data belongs to you. If not, there may be security risks.") file_name = add_time_with_xlsx("compare_result" + suffix) file_path = os.path.join(os.path.realpath(output_path), file_name) - remove_path(file_path) + if os.path.exists(file_path): + logger.warning(f"{file_path} will be recovered") + remove_path(file_path) highlight_dict = {"red_rows": set(), "yellow_rows": set(), "red_lines": [], "yellow_lines": []} npu_json = input_param.get("npu_json_path") diff --git a/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py b/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py index b605bd59f..c43958f40 100644 --- a/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py +++ b/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py @@ -1,4 +1,4 @@ -# Copyright (c) 2024-2024, Huawei Technologies Co., Ltd. +# Copyright (c) 2024-2025, Huawei Technologies Co., Ltd. # All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); @@ -21,7 +21,8 @@ from functools import partial import pandas as pd from tqdm import tqdm -from msprobe.core.common.file_utils import load_yaml, logger, FileChecker, save_excel, read_xlsx, create_directory +from msprobe.core.common.file_utils import load_yaml, logger, FileChecker, save_excel, read_xlsx, create_directory, \ + remove_path from msprobe.core.common.const import FileCheckConst, Const, CompareConst from msprobe.core.common.utils import CompareException, add_time_with_xlsx from msprobe.core.compare.utils import table_value_is_valid @@ -329,6 +330,10 @@ def generate_merge_result(all_compare_index_dict_list, all_rank_num_list, all_co for i, df in enumerate(merge_df_list): # merge_df_list中df与compare_index_list中compare_index一一对应 final_result_df_list.append((df, compare_index_list[i])) + + if os.path.exists(output_path): + logger.warning(f"{output_path} will be recovered") + remove_path(output_path) save_excel(output_path, final_result_df_list) logger.info(f"The compare results of the multi-ranks are merged and saved in: {output_path}.") -- Gitee From c1f27f8a00169c670b60d2ed6da1180aed6d655e Mon Sep 17 00:00:00 2001 From: jiandaobao Date: Wed, 19 Mar 2025 14:52:51 +0800 Subject: [PATCH 008/750] grammer check --- .../pytorch/free_benchmark/perturbed_layers/npu/add_noise.py | 4 ++-- .../pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py | 4 ++-- .../pytorch/free_benchmark/result_handlers/check_handler.py | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py index 41ec39e3a..986b833ab 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py @@ -95,13 +95,13 @@ class AddNoiseLayer(NpuBaseLayer): except Exception: logger.warning_on_rank_0( f"[msprobe] Free Benchmark: For {self.api_name}, " - f"when calculate maximun value, tensor is changed to float32." + f"when calculating the maximum value, the tensor is changed to float32." ) max_val = TorchC.max(TorchC.abs(tensor_obj.to(torch.float32))).item() if max_val < abs_tol: logger.warning_on_rank_0( f"[msprobe] Free Benchmark: For {self.api_name}, " - f"Maximun value is less than the minimun threshold. Cancel add noise." + f"maximum value is less than the minimum threshold. Cancel adding noise." ) return False return True diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py index df1a73127..7d5cda6be 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py @@ -100,13 +100,13 @@ class BitNoiseLayer(NpuBaseLayer): except Exception: logger.warning_on_rank_0( f"[msprobe] Free Benchmark: For {self.api_name}, " - f"when calculate maximun value, tensor is changed to float32." + f"when calculate the maximum value, the tensor is changed to float32." ) max_val = TorchC.max(TorchC.abs(tensor_obj.to(torch.float32))).item() if max_val < abs_tol: logger.warning_on_rank_0( f"[msprobe] Free Benchmark: For {self.api_name}, " - f"Maximun value is less than the minimun threshold. Cancel add noise." + f"maximum value is less than the minimum threshold. Cancel adding noise." ) return False return True diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/result_handlers/check_handler.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/result_handlers/check_handler.py index 9feec1531..d088cd1d1 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/result_handlers/check_handler.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/result_handlers/check_handler.py @@ -49,6 +49,6 @@ class CheckerHandler(FuzzHandler): except Exception as e: logger.warning_on_rank_0( f"[msprobe] Free Benchmark: For {self.params.api_name}, " - f"when campare the result exception raise {e}" + f"when comparing the results, an exception is raised: {e}" ) return data_params.original_result -- Gitee From dc9f919480695961e21a712aa1f410d034cbb03c Mon Sep 17 00:00:00 2001 From: Linwei-Ying Date: Thu, 20 Mar 2025 10:48:52 +0800 Subject: [PATCH 009/750] compare logger bugfix --- debug/accuracy_tools/msprobe/core/common/utils.py | 2 +- debug/accuracy_tools/msprobe/core/compare/acc_compare.py | 3 +++ .../msprobe/core/compare/merge_result/merge_result.py | 1 + debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py | 2 +- 4 files changed, 6 insertions(+), 2 deletions(-) diff --git a/debug/accuracy_tools/msprobe/core/common/utils.py b/debug/accuracy_tools/msprobe/core/common/utils.py index 963ca8254..e08e40f1e 100644 --- a/debug/accuracy_tools/msprobe/core/common/utils.py +++ b/debug/accuracy_tools/msprobe/core/common/utils.py @@ -284,7 +284,7 @@ def set_dump_path(input_param): npu_path_valid = npu_path is not None and npu_path.endswith("dump.json") bench_path_valid = bench_path is not None and bench_path.endswith("dump.json") if not npu_path_valid or not bench_path_valid: - logger.error(f"Please check the json path is valid. npu_path: {npu_path}, bench_path: {bench_path}") + logger.error(f"Please check the json path is valid and ensure that neither npu_path nor bench_path is None.") raise CompareException(CompareException.INVALID_PATH_ERROR) input_param['npu_dump_data_dir'] = os.path.join(os.path.dirname(npu_path), Const.DUMP_TENSOR_DATA) input_param['bench_dump_data_dir'] = os.path.join(os.path.dirname(bench_path), Const.DUMP_TENSOR_DATA) diff --git a/debug/accuracy_tools/msprobe/core/compare/acc_compare.py b/debug/accuracy_tools/msprobe/core/compare/acc_compare.py index f2aa8c479..9f8b13211 100644 --- a/debug/accuracy_tools/msprobe/core/compare/acc_compare.py +++ b/debug/accuracy_tools/msprobe/core/compare/acc_compare.py @@ -282,6 +282,8 @@ class Comparator: result = [] bench_ops_all[CompareConst.N_A] = self._generate_na_data(bench_ops_all) for ms_op_name, bench_op_name in self.data_mapping_dict.items(): + check_op_str_pattern_valid(ms_op_name) + check_op_str_pattern_valid(bench_op_name) if ms_op_name in npu_ops_all and bench_op_name in bench_ops_all: npu_stack_info = npu_ops_all.get(ms_op_name).get("stack_info", None) bench_stack_info = bench_ops_all.get(bench_op_name).get("stack_info", None) @@ -333,6 +335,7 @@ class Comparator: pt_data_name = bench_ops_all.get(bench_op_name).get("data_name", None) result_item.append([ms_data_name, pt_data_name]) result.append(result_item) + logger.info(f"{ms_op_name}, {bench_op_name} compared.") elif ms_op_name not in npu_ops_all: logger.warning(f'Can not find npu op name : `{ms_op_name}` in npu dump json file.') elif bench_op_name not in npu_ops_all: diff --git a/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py b/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py index b605bd59f..3c32c8900 100644 --- a/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py +++ b/debug/accuracy_tools/msprobe/core/compare/merge_result/merge_result.py @@ -63,6 +63,7 @@ def get_result_path(input_dir): for f in os.listdir(input_dir) if f.endswith(FileCheckConst.XLSX_SUFFIX)] filt_compare_result_path_list = [] for file_path in compare_result_path_list: + FileChecker(file_path, FileCheckConst.FILE, FileCheckConst.READ_ABLE).common_check() file_name = os.path.basename(file_path) if check_compare_result_name(file_name): compare_result_path_checker = FileChecker(file_path, FileCheckConst.FILE, FileCheckConst.READ_ABLE) diff --git a/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py b/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py index 61766ed27..69abbf12b 100644 --- a/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py +++ b/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py @@ -206,7 +206,7 @@ class TestUtils(TestCase): with self.assertRaises(CompareException) as context: set_dump_path(input_param) self.assertEqual(context.exception.code, CompareException.INVALID_PATH_ERROR) - mock_error.assert_called_with("Please check the json path is valid. npu_path: None, bench_path: bench_path") + mock_error.assert_called_with("Please check the json path is valid and ensure that neither npu_path nor bench_path is None.") @patch.object(logger, "error") def test_get_dump_mode(self, mock_error): -- Gitee From 0cc803cdd0ac9f3a7e93ec26a993fab085b03524 Mon Sep 17 00:00:00 2001 From: lcw Date: Wed, 19 Mar 2025 14:44:24 +0800 Subject: [PATCH 010/750] =?UTF-8?q?=E3=80=90bugfix=E3=80=91=E4=BF=AE?= =?UTF-8?q?=E5=A4=8D=E5=A4=9A=E7=BA=BF=E7=A8=8B=E4=B8=8B=E5=81=B6=E7=8E=B0?= =?UTF-8?q?json.dump=E6=8A=A5=E9=94=99?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../msprobe/core/data_dump/json_writer.py | 57 +++++++++++-------- 1 file changed, 32 insertions(+), 25 deletions(-) diff --git a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py index b1e26d16f..2d8364791 100644 --- a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py +++ b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py @@ -16,13 +16,15 @@ import csv import os import copy -import numpy as np +import threading from msprobe.core.common.const import Const, FileCheckConst from msprobe.core.common.file_utils import change_mode, FileOpen, save_json, load_json from msprobe.core.common.log import logger from msprobe.core.common.exceptions import MsprobeException +lock = threading.Lock() + class DataWriter: @@ -90,28 +92,32 @@ class DataWriter: self.write_json() def update_data(self, new_data): - if not isinstance(new_data, dict) or len(new_data.keys()) != 1: - logger.warning(f"The data info({new_data}) should be a dict with only one outer key.") - return - dump_data = self.cache_data.get(Const.DATA) - if not isinstance(dump_data, dict): - logger.warning(f"The dump data({dump_data}) should be a dict.") - return - - key = next(iter(new_data.keys())) - if key in dump_data: - dump_data.get(key).update(new_data.get(key)) - else: - dump_data.update(new_data) + with lock: + if not isinstance(new_data, dict) or len(new_data.keys()) != 1: + logger.warning(f"The data info({new_data}) should be a dict with only one outer key.") + return + dump_data = self.cache_data.get(Const.DATA) + if not isinstance(dump_data, dict): + logger.warning(f"The dump data({dump_data}) should be a dict.") + return + + key = next(iter(new_data.keys())) + if key in dump_data: + dump_data.get(key).update(new_data.get(key)) + else: + dump_data.update(new_data) def update_stack(self, new_data): - self.cache_stack.update(new_data) + with lock: + self.cache_stack.update(new_data) def update_construct(self, new_data): - self.cache_construct.update(new_data) + with lock: + self.cache_construct.update(new_data) def update_debug(self, new_data): - self.cache_debug['data'].update(new_data) + with lock: + self.cache_debug['data'].update(new_data) def write_data_json(self, file_path): logger.info(f"dump.json is at {os.path.dirname(os.path.dirname(file_path))}. ") @@ -127,14 +133,15 @@ class DataWriter: save_json(file_path, self.cache_debug, indent=1) def write_json(self): - if self.cache_data: - self.write_data_json(self.dump_file_path) - if self.cache_stack: - self.write_stack_info_json(self.stack_file_path) - if self.cache_construct: - self.write_construct_info_json(self.construct_file_path) - if self.cache_debug: - self.write_debug_info_json(self.debug_file_path) + with lock: + if self.cache_data: + self.write_data_json(self.dump_file_path) + if self.cache_stack: + self.write_stack_info_json(self.stack_file_path) + if self.cache_construct: + self.write_construct_info_json(self.construct_file_path) + if self.cache_debug: + self.write_debug_info_json(self.debug_file_path) def fill_stack_tensor_data(self): self.process_stat_data_recursive(self.cache_data) -- Gitee From bfadc7a0565f3ea1b44093d17e18354f62301d47 Mon Sep 17 00:00:00 2001 From: wuyulong17 <2284273586@qq.com> Date: Wed, 19 Mar 2025 20:19:13 +0800 Subject: [PATCH 011/750] 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plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore b/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore new file mode 100644 index 000000000..46a6e4897 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore @@ -0,0 +1,9 @@ +node_modules/ +package-lock.json +.npmrc +yarn.lock +dist/ +build/ +tb_graph_ascend.egg-info/ +__pycache__/ +/server/static/index.html \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/README.md b/plugins/tensorboard-plugins/tb_graph_ascend/README.md new file mode 100644 index 000000000..8b05e9569 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/README.md @@ -0,0 +1,226 @@ +# tb-graph-ascend + +### 介绍 + +此工具是将模型结构进行分级可视化展示的 Tensorboard 插件。可将模型的层级关系、精度性能数据进行可视化，并支持将调试模型和标杆模型进行分视图展示和关联比对，方便用户快速定位精度问题。 + +### 快速安装说明 + +- 相关依赖： + + `python >= 3.7 ，tensorboard >= 2.11.2，numpy <= 1.26.3` + +- 安装方式 + + 1. pip 安装（推荐） + + - 现本插件已经上传到 pypi 社区，用户可在 python 环境下直接通过以下 pip 指令进行安装： + ``` + pip install tb-graph-ascend + ``` + - 也可在 pypi 社区上下载离线 whl 包，传输到无法访问公网的环境上离线安装使用。访问[下载链接](https://pypi.org/project/tb-graph-ascend/#files)选择 whl 包进行下载，之后便可使用指令安装（此处{version}为 whl 包实际版本） + ``` + pip install tb-graph_ascend_{version}-py3-none-any.whl + ``` + + 2. 从源代码安装 + + - 从仓库下载源码并切换到 poc 分支: + + ``` + git clone https://gitee.com/ascend/mstt.git -b poc + ``` + + - 进入目录 `plugins/tensorboard-plugins/tb_graph_ascend` 下 + - 编译前端代码，根据操作系统选取不同指令 + + ``` + cd fe + // Windows系统 + npm run buildWin + // 其他可使用cp指令的系统，如Linux或Mac + npm run buildLinux + ``` + + **注意**: 此步骤需要安装 Node.js 环境 + + - 回到上级目录直接安装: + ``` + cd ../ + python setup.py develop + ``` + - 或： 构建 whl 包安装 + ``` + python setup.py bdist_wheel + ``` + 在 `plugins/tensorboard-plugins/tb_graph_ascend/dist` 目录下取出 whl 包，使用以下指令安装（此处{version}为 whl 包实际版本） + ``` + pip install tb-graph_ascend_{version}-py3-none-any.whl + ``` + +### 解析数据说明 + +- 准备数据 + + 将通过[msprobe](https://gitee.com/ascend/mstt/tree/master/debug/accuracy_tools/msprobe#10-%E5%88%86%E7%BA%A7%E5%8F%AF%E8%A7%86%E5%8C%96%E6%9E%84%E5%9B%BE%E6%AF%94%E5%AF%B9)工具构图功能采集得到的文件后缀为.vis 的模型结构文件（文件本身为 json 格式）放置于某个文件夹中，路径名称下文称之为 `out_path` \ + E.g. \ + `---output_path` \ + `-----output.vis` \ + `-----output2.vis` + +### 启动方式 + +1. 启动 TensorBoard + + ``` + tensorboard --logdir output_path + ``` + + 如果网络浏览器与启动 TensorBoard 的机器不在同一台机器上，则需要在尾部加上`--bind_all`命令，如： + + ``` + tensorboard --logdir output_path --bind_all + ``` + + 注意：确保默认端口 6006 对浏览器的主机打开。 + + 如果需要切换端口号需要在尾部加上指定的端口号，如`--port=6007` + + ``` + tensorboard --logdir output_path --port=6007 + ``` + +2. 在浏览器上打开 tensorboard + + 在浏览器中打开 URL： `http://localhost:6006`。 + 如果 tensorboard 启动命令使用`--bind_all`, 则需将主机名由`localhost`替换为主机的 ip 地址。 + + 注意：如果`--logdir` 指定目录下的文件太大或太多，请等候，刷新浏览器查看加载结果。 + +### 前端主体 + +#### 页面展示说明 + +① 设置栏 +② 图例 +③ 图结构 +④ 节点信息和比对详情 +⑤ 缩略图 +![输入图片说明](./doc/images/mainPage.png) + +#### 操作方式： + +1. 节点双击打开，单击选中。 +2. 选中的节点边框呈现蓝色，比对场景下若其存在对应节点，则对应节点边框为浅蓝色 +3. 键盘 WS 根据鼠标位置放大缩小，AD 左右移动， +4. 鼠标滚轮上下移动，鼠标可拖动页面 +5. 比对场景鼠标右键可选中节点，并可展开至对应侧的节点并选中 + +### 设置栏 + +#### 1.设置 + +![输入图片说明](./doc/images/setting.png) +| 字段 | 含义 | +|------|------| +| Fit to screen | 根据浏览器窗口的大小和比例，自动缩放图表，完整显示整个模型结构 | +| Download PNG | 以PNG的形式下载当前展开的模型结构 | +| Run | 模型结构文件所在目录 | +| Tag | 模型结构文件名称 | +| MicroStep | 展示模型结构文件某个MicroStep（若未按MicroStep采集则不会出现） | +| Step | 展示模型结构文件某个Step（若未按Step采集则不会出现） | +| 节点搜索 | 通过节点名称快速定位到节点，支持模糊搜索，括号内显示某侧节点总数 | +| 数据侧 | 选择在调试侧或标杆侧搜索节点节点 | + +#### 2.目录 + +![目录](./doc/images/directory.png) + +1. 目录中的节点名称、层级信息、颜色、是否可以展开与图中的对应节点一致。 + +2. 若存在箭头则代表节点可展开，若不存在则代表其不存在子节点。 + +3. 单击目录中的节点时，若可以展开，则图中相应的节点会展开并被选中，否则仅选中。 + +4. 单击目录中已展开的节点时，目录和图中的结构都会收缩，若图中结构已经收缩，则仅选中。 + +5. 如果图中该节点已经展开，则仅会选中该节点，而不会收缩。 + +#### 3.精度筛选 + +![精度筛选](./doc/images/accuracyFilter.png) +| 字段 | 含义 | +| ---------------- | ---------------------------------------------------------------------------------------------------------------------------------- | +| 精度筛选 | 勾选想要查看的颜色，可得到筛选后的节点列表，鼠标点击列表中节点名称，图自动展开到指定节点（仅展示叶子节点，展示顺序按 dump 时间序） | +| 标杆侧未匹配节点（比对场景特有） | 展示标杆侧未匹配节点，可通过列表或搜索上/下一个按钮来切换展示的节点 | + +#### 4.匹配（比对场景特有） +![alt text](./doc/images/matched.png) + +| 功能 | 说明 | +| ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| 保存 | 匹配过程中，所有的操作只会在内存中进行，并不会持久化到文件中，因此匹配结束后需要点击保存按钮，将操作后数据更新到文件中，否则下次刷新页面，之前的操作将不会保留 +| 未匹配节点 | 会展示 NPU 侧和标杆侧的未匹配节点，点击列表节点会自动展开至对应层并选中该节，点击图中选中未匹配节点也会在列表自动选中 | +| 点击匹配 | 根据数据模式（md5 模式/统计值模式/tensor 模式）对未匹配两侧的各一个节点进行匹配，若不能匹配则给出原因，若能匹配成功则该对节点移入已匹配节点中，匹配结果将在原始文件中持久化记录 | +| 已匹配节点 | 展示已匹配成功节点，点击列表节点会自动展开至对应层并选中该节点，并且会在另个列表中自动选中对应的节点 | +| 取消匹配 | 将两个节点的所有属性还原至未匹配之前的状态，匹配列表中也会减去这两个节点 | + + +#### 5.图例 + +##### 5.1节点图例 + +![节点图例](./doc/images/legend.png) + +| 图例名称 | 说明 | +| ------------------------------ | --------------------------------------------- | +| Module or Operators | 模块或者计算单元 | +| Unexpanded Module or Operators | 无法展开的模块或者计算单元 | +| Api List | 模块间游离的 API 的集合，只会在首层节点中出现 | + +##### 5.2颜色图例: + +![颜色图例](./doc/images/colors.png) + +展示颜色及对应的精度区间，支持用户自定义配置，若未配置则使用默认配置，用户可自定义配置颜色区间和颜色。 + +![颜色配置](./doc/images/colorConfig.png) + +点击齿轮图标可进入配置界面，点击**添加区间**按钮可增加区间，点击某条配置后的减号按钮可删除此区间，最大支持配置5个区间，区间可选择颜色和输入精度区间范围。配置完成后点击确认即可全局生效，且该配置会对同目录下其他同次采集生成的模型结构文件生效。 + +### 图结构 + +#### 1.模型层级结构 + +图中结构为模型层级结构，为顺序执行序，顺序为从上到下，从左到右 +* 若为对比图，节点的颜色代表这个节点的精度误差 +* 节点单击选中，展示节点信息，若可展开双击展开，右键若为对比图可进行跳转功能 + +#### 2.缩略图 + +展示整个模型计算图的缩略图和当前视窗所在位置，可以通过在缩率图中点击和拖动视窗快速查看模型的不同部分。 + +### 信息栏 +用户鼠标放在分割线，鼠标变为可拖拽标识，按下鼠标移动可以改变信息栏高度，方便用户查看节点信息 + +#### 1.节点详情 +对于单图构建，以表格的形式展示模型中各节点在目标侧的input和output参数信息。 + +#### 2.比对详情 +对于多图比较，以表格的形式展示模型中各节点在目标侧和标杆侧的input和output参数信息，使用不同的颜色区分目标节点和匹配节点数据，如果不存在匹配节点，则只展示当前选中节点数据。 + +采用从前到后的顺序匹配策略，对于已经匹配的数据，目标节点和匹配节点的数据间隔展示，表格第一列添加绿色标识，如果目标侧节点数据和匹配侧节点数据长度不一致，则会存在未匹配的数据，未匹配的数据会以红色标识，并且全量添加到表格尾部，方便用户查看。 + +表头支持横向拖拽，更改每一列的宽度，方便查看过长的数据，鼠标悬停也会展示全部数据，方便用户查看。 + +![输入图片说明](./doc/images/compare-info.png) + +##### 3.节点信息 +展示除了input和output以外的信息，目前主要用来展示节点的stackInfo数据，表格共两列分别展示目标侧和匹配侧的stackInfo数据，如果不存在匹配节点，则只展示当前选中节点的数据，对于stackInfo数据支持一键复制，方便用户在其他编辑器查看数据。表头支持横向拖拽，更改每一列的宽度，方便用户查看过长的数据。 + +![输入图片说明](./doc/images/node-info.png) + +### 附录 + +[公网地址说明](./doc/公网地址说明.csv) + diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/doc/images/accuracyFilter.png b/plugins/tensorboard-plugins/tb_graph_ascend/doc/images/accuracyFilter.png new file mode 100644 index 0000000000000000000000000000000000000000..f5ed9e9b16de86c3a7cf789442c94d7d02d950c4 GIT binary patch literal 8146 zcmd6scT`i)w)letjYx|K2q+~8C>=saz)+=!|qoM%Q@itwXigv$+4QO*cCqALCvI@2S{G-b1qxEEprg`W)*F2i6 zEpdGhb)mY;7Ic_utP)j+uCc^JAo1lfs`?u|n$)*$eL!`_Oqrvp7!9gf17BZ?K_y1h 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@@ +IPַ/URLַ//ַ,;˵ +http://www.apache.org/licenses/LICENSE-2.0,License +pmail_mindstudio@huawei.com,MindStudioٷ +https://gitee.com/ascend/mstt/tree/master/plugins/tensorboard-plugins/tb_graph_ascend,ֵַ +https://npms.io,npm߹ַ +http://codepen.io/shyndman/pen/,룬ע +https://github.com/webcomponents/shadycss/issues/193,룬ע +http://jsbin.com/temexa/4,룬ע +https://fonts.googleapis.com/,룬ʽļ +https://developer.mozilla.org/,룬ע +https://github.com/vaadin/vaadin-time-picker/issues/145,룬ע diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/.prettierrc b/plugins/tensorboard-plugins/tb_graph_ascend/fe/.prettierrc new file mode 100644 index 000000000..e3d2acb00 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/.prettierrc @@ -0,0 +1,13 @@ +{ + "parser": "typescript", + "semi": true, + "singleQuote": true, + "jsxSingleQuote": false, + "bracketSpacing": true, + "tabWidth": 2, + "useTabs": false, + "trailingComma": "all", + "proseWrap": "always", + "endOfLine": "lf", + "printWidth": 120 +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/index.html b/plugins/tensorboard-plugins/tb_graph_ascend/fe/index.html new file mode 100644 index 000000000..06b36c378 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/index.html @@ -0,0 +1,28 @@ + + + + + + + + + + + diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/package.json b/plugins/tensorboard-plugins/tb_graph_ascend/fe/package.json new file mode 100644 index 000000000..2f6ab57b6 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/package.json @@ -0,0 +1,89 @@ +{ + "name": "tb-graph-ascend", + "version": "0.1.0", + "description": "#### Description {**When you're done, you can delete the content in this README and update the file with details for others getting started with your repository**}", + "main": "index.js", + "scripts": { + "buildLinux": "cross-env NODE_ENV=production webpack && cp dist/index.html ../server/static/", + "buildWin": "cross-env NODE_ENV=production webpack && copy dist\\index.html ..\\server\\static\\", + "dev": "webpack server", + "prettier": "prettier --config ./.prettierrc --write ./src/**/*.ts" + }, + "devDependencies": { + "@types/d3": "5.7.2", + "@types/lodash": "^4.14.172", + "@types/node": "^16.4.13", + "@types/offscreencanvas": "^2019.6.3", + "@types/requirejs": "^2.1.33", + "@types/resize-observer-browser": "^0.1.6", + "@types/three": "^0.131.0", + "html-loader": "^5.1.0", + "html-webpack-plugin": "^5.6.3", + "inline-chunk-html-plugin": "^1.1.1", + "ts-loader": "^9.5.1", + "tslib": "^2.6.2", + "typescript": "^5.4.5", + "webpack": "^5.96.1", + "webpack-cli": "^5.1.4" + }, + "dependencies": { + "@polymer/decorators": "^3.0.0", + "@polymer/iron-behaviors": "^3.0.1", + "@polymer/iron-collapse": "^3.0.1", + "@polymer/iron-flex-layout": "^3.0.1", + "@polymer/iron-icon": "^3.0.1", + "@polymer/iron-icons": "^3.0.1", + "@polymer/iron-iconset-svg": "^3.0.1", + "@polymer/iron-list": "^3.1.0", + "@polymer/iron-pages": "^3.0.1", + "@polymer/iron-resizable-behavior": "^3.0.1", + "@polymer/paper-behaviors": "^3.0.1", + "@polymer/paper-button": "^3.0.1", + "@polymer/paper-checkbox": "^3.1.0", + "@polymer/paper-dialog": "^3.0.1", + "@polymer/paper-dialog-scrollable": "^3.0.1", + "@polymer/paper-dropdown-menu": "^3.1.0", + "@polymer/paper-header-panel": "^3.0.1", + "@polymer/paper-icon-button": "^3.0.2", + "@polymer/paper-input": "^3.2.1", + "@polymer/paper-item": "^3.0.1", + "@polymer/paper-listbox": "^3.0.1", + "@polymer/paper-material": "^3.0.1", + "@polymer/paper-menu-button": "^3.0.1", + "@polymer/paper-progress": "^3.0.1", + "@polymer/paper-radio-button": "^3.0.1", + "@polymer/paper-radio-group": "^3.0.1", + "@polymer/paper-slider": "^3.0.1", + "@polymer/paper-spinner": "^3.0.2", + "@polymer/paper-styles": "^3.0.1", + "@polymer/paper-tabs": "^3.1.0", + "@polymer/paper-toast": "^3.0.1", + "@polymer/paper-toggle-button": "^3.0.1", + "@polymer/paper-toolbar": "^3.0.1", + "@polymer/paper-tooltip": "^3.0.1", + "@polymer/polymer": "^3.5.1", + "@types/lodash": "^4.17.1", + "@vaadin/button": "^23.5.11", + "@vaadin/combo-box": "^23.5.11", + "@vaadin/details": "^24.6.5", + "@vaadin/icon": "^23.5.11", + "@vaadin/icons": "^23.5.11", + "@vaadin/notification": "^23.5.11", + "@vaadin/progress-bar": "^23.5.11", + "@vaadin/tabs": "^23.5.11", + "@vaadin/tabsheet": "^23.5.11", + "@vaadin/text-field": "^24.6.6", + "@vaadin/tooltip": "^23.5.11", + "@vaadin/vaadin-combo-box": "^23.5.12", + "@vaadin/vaadin-grid": "^23.5.11", + "@vaadin/vaadin-select": "^23.5.12", + "clean-webpack-plugin": "^4.0.0", + "cross-env": "^7.0.3", + "css-loader": "^7.1.2", + "d3": "5.7.0", + "dagre": "^0.8.5", + "lodash": "^4.17.21", + "prettier": "^3.4.2", + "style-loader": "^4.0.0" + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/index.css b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/index.css new file mode 100644 index 000000000..ac81d67c4 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/index.css @@ -0,0 +1,17 @@ +html, +body, +graph-app { + height: 100%; + margin: 0; + font-family: Roboto, sans-serif; +} + +vaadin-combo-box-scroller { + overflow: scroll; + font-size: 14px; +} + +vaadin-combo-box-item { + overflow: unset; + font-size: 14px; +} \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/index.ts new file mode 100644 index 000000000..6e65aac4e --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/index.ts @@ -0,0 +1,18 @@ +/* Copyright (c) 2024, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import './tf_graph_dashboard/index'; +import './index.css'; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dark_mode_mixin.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dark_mode_mixin.ts new file mode 100644 index 000000000..e389b76d6 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dark_mode_mixin.ts @@ -0,0 +1,55 @@ +/* Copyright 2021 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { PolymerElement } from '@polymer/polymer'; + +/** + * Polymer mixin replacement for `:host-context(body.dark-mode)`. + *- + * Unfortunately, Firefox does not support `:host-context()` and cannot use the + * WebComponent way of styling shadow DOMs with context for ancestor [1][2]. + * To work around the issue, we are creating a WebComponent mixin that adds + * class `dark-mode` to `:host` when body contains the class, `.dark-mode`. + * + * Unfortunately, due to our infamiliarity with mixins, our types are imperfect. + * + */ +export function DarkModeMixin(Base: new () => PolymerElement): new () => T { + return class Foo extends Base { + private observer?: MutationObserver; + + override connectedCallback(): void { + super.connectedCallback(); + this._maybeSetDarkMode(); + + this.observer = new MutationObserver((mutations) => { + const classChanged = mutations.some((mutation) => { + return mutation.attributeName === 'class'; + }); + if (classChanged) this._maybeSetDarkMode(); + }); + this.observer.observe(document.body, { attributes: true }); + } + + override disconnectedCallback(): void { + super.disconnectedCallback(); + this.observer?.disconnect(); + } + + private _maybeSetDarkMode(): void { + this.classList.toggle('dark-mode', document.body.classList.contains('dark-mode')); + } + } as unknown as new () => T; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dom-repeat.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dom-repeat.ts new file mode 100644 index 000000000..53f21caa6 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dom-repeat.ts @@ -0,0 +1,16 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +export * from '@polymer/polymer/lib/elements/dom-repeat'; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dom.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dom.ts new file mode 100644 index 000000000..7b1ace8b9 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/dom.ts @@ -0,0 +1,16 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +export * from '@polymer/polymer/lib/legacy/polymer.dom'; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/irons_and_papers.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/irons_and_papers.ts new file mode 100644 index 000000000..23b3fc88a --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/irons_and_papers.ts @@ -0,0 +1,52 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +/** + * @fileoverview Imports all TensorBoard dependencies to paper and iron components. Please + * import this module for dependency on iron and paper components. + */ + +import '@polymer/iron-collapse/iron-collapse'; +import '@polymer/iron-flex-layout/iron-flex-layout-classes'; +import '@polymer/iron-icon'; +import '@polymer/iron-icons/image-icons'; +import '@polymer/iron-icons/iron-icons'; +import '@polymer/iron-iconset-svg'; +import '@polymer/iron-list/iron-list'; +import '@polymer/iron-pages'; +import '@polymer/paper-button'; +import '@polymer/paper-checkbox'; +import '@polymer/paper-dialog'; +import '@polymer/paper-dialog-scrollable'; +import '@polymer/paper-dropdown-menu/paper-dropdown-menu'; +import '@polymer/paper-header-panel'; +import '@polymer/paper-icon-button/paper-icon-button'; +import '@polymer/paper-input/paper-input'; +import '@polymer/paper-input/paper-textarea'; +import '@polymer/paper-item'; +import '@polymer/paper-listbox'; +import '@polymer/paper-material'; +import '@polymer/paper-menu-button'; +import '@polymer/paper-progress'; +import '@polymer/paper-radio-button'; +import '@polymer/paper-radio-group'; +import '@polymer/paper-slider'; +import '@polymer/paper-spinner/paper-spinner'; +import '@polymer/paper-spinner/paper-spinner-lite'; +import '@polymer/paper-styles/paper-styles'; +import '@polymer/paper-tabs'; +import '@polymer/paper-toast'; +import '@polymer/paper-toggle-button'; +import '@polymer/paper-toolbar'; +import '@polymer/paper-tooltip/paper-tooltip'; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/legacy_element_mixin.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/legacy_element_mixin.ts new file mode 100644 index 000000000..e0768eac4 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/legacy_element_mixin.ts @@ -0,0 +1,16 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +export * from '@polymer/polymer/lib/legacy/legacy-element-mixin'; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/register_style_dom_module.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/register_style_dom_module.ts new file mode 100644 index 000000000..fd968cc73 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/polymer/register_style_dom_module.ts @@ -0,0 +1,52 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import '@polymer/polymer/lib/elements/dom-module'; + +export interface DomModuleOptions { + moduleName: string; + styleDependencies?: string[]; + styleContent: string; +} + +/** + * Interop for Polymer 3 styling + * + * The following process is a workaround. While Polymer 3.0 does not use + * elements for templating, style modules do. The following process + * is a workaround for this fact. This process may be updated as required. + */ +export function registerStyleDomModule(args: DomModuleOptions): void { + const { moduleName, styleContent } = args; + const domModule = document.createElement('dom-module'); + const template = document.createElement('template'); + + const styleIncludes: HTMLStyleElement[] = []; + if (args.styleDependencies) { + args.styleDependencies.forEach((dep) => { + const style = document.createElement('style'); + style.setAttribute('include', dep); + styleIncludes.push(style); + }); + } + const style = document.createElement('style'); + Object.assign(style, { textContent: styleContent }); + + styleIncludes.forEach((styleElement) => { + template.content.appendChild(styleElement); + }); + template.content.appendChild(style); + domModule.appendChild(template); + (domModule as any).register(moduleName); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tb_debug/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tb_debug/index.ts new file mode 100644 index 000000000..f492ad1fe --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tb_debug/index.ts @@ -0,0 +1,16 @@ +/* Copyright 2021 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +export * from './types'; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tb_debug/types.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tb_debug/types.ts new file mode 100644 index 000000000..2f575df43 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tb_debug/types.ts @@ -0,0 +1,77 @@ +/* Copyright 2021 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +export interface ActionEvent { + eventCategory: string; + eventAction: string; + eventLabel?: string; + eventValue?: number; +} + +export const GRAPH_DEBUG_ACTION_EVENT_CATEGORY = 'Graph dashboard actions'; +export const GRAPH_DEBUG_TIMING_EVENT_CATEGORY = 'Graph dashboard timings'; + +/** + * Timing-based events, part of `GRAPH_DEBUG_TIMING_EVENT_CATEGORY`. + */ +export enum GraphDebugTimingEventId { + // Pre-rendering. + // `FETCH_PBTXT_BYTES` is fired for both filesystem and server sources. + FETCH_PBTXT_BYTES = 'FETCH_PBTXT_BYTES', + FETCH_PBTXT_BYTES_FROM_FILESYSTEM = 'FETCH_PBTXT_BYTES_FROM_FILESYSTEM', + FETCH_PBTXT_BYTES_FROM_SERVER = 'FETCH_PBTXT_BYTES_FROM_SERVER', + PARSE_PBTXT_INTO_OBJECT = 'PARSE_PBTXT_INTO_OBJECT', + FETCH_METADATA_PBTXT_BYTES = 'FETCH_METADATA_PBTXT_BYTES', + PARSE_METADATA_PBTXT_INTO_OBJECT = 'PARSE_METADATA_PBTXT_INTO_OBJECT', + NORMALIZING_NAMES = 'NORMALIZING_NAMES', + BUILD_SLIM_GRAPH = 'BUILD_SLIM_GRAPH', + HIERARCHY_ADD_NODES = 'HIERARCHY_ADD_NODES', + HIERARCHY_DETECT_SERIES = 'HIERARCHY_DETECT_SERIES', + HIERARCHY_ADD_EDGES = 'HIERARCHY_ADD_EDGES', + HIERARCHY_FIND_SIMILAR_SUBGRAPHS = 'HIERARCHY_FIND_SIMILAR_SUBGRAPHS', + // Rendering. + RENDER_BUILD_HIERARCHY = 'RENDER_BUILD_HIERARCHY', + RENDER_SCENE_LAYOUT = 'RENDER_SCENE_LAYOUT', + RENDER_SCENE_BUILD_SCENE = 'RENDER_SCENE_BUILD_SCENE', + // Total graph loading (superset of other phases). Note that after [1], + // this timing no longer includes `HIERARCHY_FIND_SIMILAR_SUBGRAPHS`, + // which is computed lazily. + GRAPH_LOAD_SUCCEEDED = 'GRAPH_LOAD_SUCCEEDED', + GRAPH_LOAD_FAILED = 'GRAPH_LOAD_FAILED', +} + +/** + * Non-timing based actions due to user interaction, part of + * `GRAPH_DEBUG_ACTION_EVENT_CATEGORY`. + */ +export enum GraphDebugActionEventId { + // Labeled by state: expanded or collapsed. + NODE_EXPANSION_TOGGLED = 'NODE_EXPANSION_TOGGLED', + NODE_SEARCH_RESULT_FOCUSED = 'NODE_SEARCH_RESULT_FOCUSED', + // Labeled by direction between auxiliary graph and the main graph. + NODE_AUXILIARY_EXTRACTION_CHANGED = 'NODE_AUXILIARY_EXTRACTION_CHANGED', + // Labeled by graph type: Op, Conceptual, Profile. + GRAPH_TYPE_CHANGED = 'GRAPH_TYPE_CHANGED', + TRACE_INPUT_MODE_TOGGLED = 'TRACE_INPUT_MODE_TOGGLED', + // Labeled by mode: Structure, Device, TPU Compat, etc. + NODE_COLOR_MODE_CHANGED = 'NODE_COLOR_MODE_CHANGED', + UPLOADED_GRAPH_FROM_FILESYSTEM = 'UPLOADED_GRAPH_FROM_FILESYSTEM', +} + +// Merge the string enums. +export const GraphDebugEventId = { + ...GraphDebugTimingEventId, + ...GraphDebugActionEventId, +}; +export type GraphDebugEventId = typeof GraphDebugEventId; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/canceller.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/canceller.ts new file mode 100644 index 000000000..bc840bb4a --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/canceller.ts @@ -0,0 +1,68 @@ +/* Copyright 2017 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +export interface CancelResult { + value: T; + cancelled: boolean; +} + +/** + * A class that allows marking promises as cancelled. + * + * This can be useful to, e.g., prevent old network requests from + * stomping new ones and writing bad data. + * + * Usage: + * + * const canceller = new Canceller(); + * let myPromise: Promise = getPromise(); + * myPromise.then(canceller.cancellable(({value, cancelled} => { + * if (cancelled) { + * console.warn("Don't make promises you can't keep >:-{"); + * } + * console.log("Enjoy your value:", value); + * })); + * + * // If `myPromise` is resolved now, then `cancelled` will be `false`. + * canceller.cancelAll(); + * // If `myPromise` is resolved now, then `cancelled` will be `true`. + */ +export class Canceller { + /** + * How many times has `cancelAll` been called? + */ + private cancellationCount = 0; + /** + * Create a cancellable task. This returns a new function that, when + * invoked, will pass its argument to the provided function as well as + * a `cancelled` argument. This argument will be `false` unless and + * until `cancelAll` is invoked after the creation of this task. + */ + public cancellable(f: (result: CancelResult) => U): (T) => U { + const originalCancellationCount = this.cancellationCount; + return (value) => { + const cancelled = this.cancellationCount !== originalCancellationCount; + return f({ value, cancelled }); + }; + } + + /** + * Mark all outstanding tasks as cancelled. Tasks not yet created will + * not be affected. + */ + public cancelAll(): void { + this.cancellationCount++; + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/requestManager.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/requestManager.ts new file mode 100644 index 000000000..bdd927ce2 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/requestManager.ts @@ -0,0 +1,294 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +const FEATURE_FLAGS_HEADER_NAME = 'X-TensorBoard-Feature-Flags'; + +interface ResolveReject { + resolve: (x: unknown) => void; + reject: (x: unknown) => void; +} + +/** + * Manages many fetch requests. Launches up to nSimultaneousRequests + * simultaneously, and maintains a LIFO queue of requests to process when + * more urls are requested than can be handled at once. The queue can be + * cleared. + * + * When a request is made, a Promise is returned which resolves with the + * parsed JSON result from the request. + */ +export class RequestCancellationError extends Error { + public override name = 'RequestCancellationError'; +} + +export class InvalidRequestOptionsError extends Error { + public override name = 'InvalidRequestOptionsError'; + constructor(msg: string) { + super(msg); + // The following is needed due to a limitation of TypeScript when + Object.setPrototypeOf(this, InvalidRequestOptionsError.prototype); + } +} + +export class RequestNetworkError extends Error { + public override name: string; + public req: XMLHttpRequest; + public url: string; + constructor(req: XMLHttpRequest, url) { + super(); + this.message = `RequestNetworkError: ${req.status} at ${url}`; + this.name = 'RequestNetworkError'; + this.req = req; + this.url = url; + } +} + +/** The HTTP method-type to use. Currently only 'GET' and 'POST' are + * supported. + */ +export enum HttpMethodType { + GET = 'GET', + POST = 'POST', +} + +/** + * Holds options that can be used to configure the HTTP request. + */ +export class RequestOptions { + public methodType: HttpMethodType; + /** The content-type request header to use. Cannot be set for a GET request.*/ + public contentType?: string; + /** The request body to use. This is the object that is passed to the + * XMLHttpRequest.send() method. If not given the 'send' method is called + * without an argument. + */ + public body?: any; + /** If specified, this will be the value set in the + * XMLHttpRequest.withCredentials property. + */ + public withCredentials?: boolean; + // Validates this object. Throws InvalidRequestOptionsError on error. + public validate(): void { + if (this.methodType === HttpMethodType.GET) { + // We don't allow a body for a GET. + if (this.body) { + throw new InvalidRequestOptionsError('body must be missing for a GET request.'); + } + } + // We allow body-less or contentType-less POSTs even if they don't + // make much sense. + } +} + +// Form data for a POST request as a convenient multidict interface, +// since the built-in `FormData` type doesn't have a value constructor. +// +// A raw string value is equivalent to a singleton array, and thus an +// empty array value is equivalent to omitting the key entirely. +export interface PostData { + [key: string]: string | string[]; +} + +export class RequestManager { + private _queue: ResolveReject[]; + private _maxRetries: number; + private _nActiveRequests: number; + private _nSimultaneousRequests: number; + constructor(nSimultaneousRequests = 1000, maxRetries = 3) { + this._queue = []; + this._nActiveRequests = 0; + this._nSimultaneousRequests = nSimultaneousRequests; + this._maxRetries = maxRetries; + } + + /** + * Gives a promise that loads assets from given url (respects queuing). If + * postData is provided, this request will use POST, not GET. This is an + * object mapping POST keys to string values. + */ + public request(url: string, postData?: PostData): Promise { + const requestOptions = requestOptionsFromPostData(postData); + return this.requestWithOptions(url, requestOptions); + } + + public requestWithOptions(url: string, requestOptions: RequestOptions): Promise { + requestOptions.validate(); + const promise = new Promise((resolve, reject) => { + const resolver = { resolve: resolve, reject: reject }; + this._queue.push(resolver); + this.launchRequests(); + }) + .then(() => { + return this.promiseWithRetries(url, this._maxRetries, requestOptions); + }) + .then( + (response) => { + // Success - Let's free space for another active + // request, and launch it + this._nActiveRequests--; + this.launchRequests(); + return response; + }, + (rejection) => { + if (rejection.name === 'RequestNetworkError') { + // If we failed due to network error, we should + // decrement + // _nActiveRequests because this request was + // active + this._nActiveRequests--; + this.launchRequests(); + } + return Promise.reject(rejection); + }, + ); + return promise; + } + + public fetch(url: string, fetchOptions?: RequestInit): Promise { + return new Promise((resolve, reject) => { + const resolver = { resolve: resolve, reject: reject }; + this._queue.push(resolver); + this.launchRequests(); + }).then(() => { + let numTries = 1; + return new Promise((resolve) => { + const retryFetch = (): void => { + fetch(url, fetchOptions).then((response) => { + if (!response.ok && this._maxRetries > numTries) { + numTries++; + retryFetch(); + return; + } + resolve(response); + this._nActiveRequests--; + this.launchRequests(); + }); + }; + retryFetch(); + }); + }); + } + + public clearQueue(): void { + while (this._queue.length > 0) { + this._queue.pop()?.reject(new RequestCancellationError('Request cancelled by clearQueue')); + } + } + + /* Return number of currently pending requests */ + public activeRequests(): number { + return this._nActiveRequests; + } + + /* Return total number of outstanding requests (includes queue) */ + public outstandingRequests(): number { + return this._nActiveRequests + this._queue.length; + } + + /* Actually get promise from url using XMLHttpRequest */ + protected _promiseFromUrl(url: string, requestOptions: RequestOptions): Promise { + return new Promise((resolve, reject) => { + const req = buildXMLHttpRequest( + requestOptions.methodType, + url, + requestOptions.withCredentials, + requestOptions.contentType, + ); + req.setRequestHeader(FEATURE_FLAGS_HEADER_NAME, JSON.stringify({})); + req.onload = function (): void { + if (req.status === 200) { + resolve(JSON.parse(req.responseText) as any); + } else { + reject(new RequestNetworkError(req, url)); + } + }; + req.onerror = function (): void { + reject(new RequestNetworkError(req, url)); + }; + if (requestOptions.body) { + req.send(requestOptions.body); + } else { + req.send(); + } + }); + } + + private launchRequests(): void { + while (this._nActiveRequests < this._nSimultaneousRequests && this._queue.length > 0) { + this._nActiveRequests++; + this._queue.pop()?.resolve(undefined); + } + } + + /** + * Try to request a given URL using overwritable _promiseFromUrl method. + * If the request fails for any reason, we will retry up to maxRetries + * times. In practice, this will help us paper over transient network issues + * like '502 Bad Gateway'. + * By default, Chrome displays network errors in console, so + * the user will be able to tell when the requests are failing. I think this + * is a feature, if the request failures and retries are causing any + * pain to users, they can see it and file issues. + */ + private promiseWithRetries(url: string, maxRetries: number, requestOptions: RequestOptions): any { + let success = (x): any => x; + let failure = (x): any => { + if (maxRetries > 0) { + return this.promiseWithRetries(url, maxRetries - 1, requestOptions); + } else { + return Promise.reject(x); + } + }; + return this._promiseFromUrl(url, requestOptions).then(success, failure); + } +} + +function buildXMLHttpRequest( + methodType: HttpMethodType, + url: string, + withCredentials?: boolean, + contentType?: string, +): XMLHttpRequest { + const req = new XMLHttpRequest(); + req.open(methodType, url); + if (withCredentials) { + req.withCredentials = withCredentials; + } + if (contentType) { + req.setRequestHeader('Content-Type', contentType); + } + return req; +} + +function requestOptionsFromPostData(postData?: PostData): RequestOptions { + const result = new RequestOptions(); + if (!postData) { + result.methodType = HttpMethodType.GET; + return result; + } + result.methodType = HttpMethodType.POST; + result.body = formDataFromDictionary(postData); + return result; +} + +function formDataFromDictionary(postData: PostData): FormData { + const formData = new FormData(); + for (const [key, maybeValues] of Object.entries(postData)) { + const values = Array.isArray(maybeValues) ? maybeValues : [maybeValues]; + for (const value of values) { + formData.append(key, value); + } + } + return formData; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/scrollbar-style.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/scrollbar-style.ts new file mode 100644 index 000000000..67113080a --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/scrollbar-style.ts @@ -0,0 +1,39 @@ +/* Copyright 2016 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { registerStyleDomModule } from '../polymer/register_style_dom_module'; + +registerStyleDomModule({ + moduleName: 'scrollbar-style', + styleContent: ` + .scrollbar::-webkit-scrollbar-track { + visibility: hidden; + } + + .scrollbar::-webkit-scrollbar { + width: 10px; + } + + .scrollbar::-webkit-scrollbar-thumb { + border-radius: 10px; + -webkit-box-shadow: inset 0 0 2px rgba(0, 0, 0, 0.3); + background-color: var(--paper-grey-500); + color: var(--paper-grey-900); + } + .scrollbar { + box-sizing: border-box; + } + `, +}); diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tensorboard-color.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tensorboard-color.ts new file mode 100644 index 000000000..e76ed139f --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tensorboard-color.ts @@ -0,0 +1,57 @@ +/* Copyright 2016 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +const style = document.createElement('style'); +style.setAttribute('is', 'custom-style'); +style.textContent = ` + :root { + --tb-orange-weak: #ffa726; + --tb-orange-strong: #f57c00; + --tb-orange-dark: #dc7320; + --tb-grey-darker: #e2e2e2; + --tb-grey-lighter: #f3f3f3; + --tb-ui-dark-accent: #757575; + --tb-ui-light-accent: #e0e0e0; + --tb-ui-border: var(--paper-grey-300); + --tb-graph-faded: #e0d4b3; + --tb-secondary-text-color: var(--paper-grey-800); + --tb-raised-button-shadow-color: rgba(0, 0, 0, 0.2); + --primary-background-color: #fff; + --secondary-background-color:rgb(247, 247, 247); + --tb-layout-background-color: #f5f5f5; + --tb-link: #1976d2; /* material blue 700. */ + --tb-link-visited: #7b1fa2; /* material purple 700. */ + } + + :root .dark-mode { + --tb-ui-border: var(--paper-grey-700); + --tb-ui-dark-accent: var(--paper-grey-400); + --tb-ui-light-accent: var(--paper-grey-600); + --tb-secondary-text-color: var(--paper-grey-400); + --tb-raised-button-shadow-color: rgba(255, 255, 255, 0.5); + --primary-text-color: #fff; + --secondary-text-color: var(--paper-grey-400); + --primary-background-color: #303030; /* material grey A400. */ + --secondary-background-color: #3a3a3a; + --tb-layout-background-color: #3a3a3a; + --tb-link: #42a5f5; /* material blue 400. */ + --tb-link-visited: #ba68c8; /* material purple 300. */ + /* Overrides paper-material */ + --shadow-elevation-2dp_-_box-shadow: 0 2px 2px 0 rgba(255, 255, 255, 0.14), + 0 1px 5px 0 rgba(255, 255, 255, 0.12), + 0 3px 1px -2px rgba(255, 255, 255, 0.2); + } +`; +document.head.appendChild(style); diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts new file mode 100644 index 000000000..4ae57964e --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts @@ -0,0 +1,151 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { customElement } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import { DarkModeMixin } from '../polymer/dark_mode_mixin'; +import './scrollbar-style'; +import './tensorboard-color'; + +@customElement('tf-dashboard-layout') +class TfDashboardLayout extends DarkModeMixin(PolymerElement) { + static readonly template = html` +

    + +
    + +
    +
    + +
    + +
    + + + `; + + _toggleSidebar(): void { + // 通过 ID 获取元素并隐藏 + const sidebar = this.shadowRoot?.querySelector('#sidebar'); + const sidebarToggle = this.shadowRoot?.querySelector('#sidebar-toggle'); + // 检查并切换 display 样式 + if (sidebar) { + sidebar?.classList.toggle('sider-hidden'); // 改为显示 + sidebarToggle?.classList.toggle('sidebar-toggle-fold'); // 改变箭头方向 + } + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_globals/globals.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_globals/globals.ts new file mode 100644 index 000000000..503570bde --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_globals/globals.ts @@ -0,0 +1,37 @@ +/* Copyright 2016 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +// If true, TensorBoard stores its hash in the URI state. +// If false, tab switching in TensorBoard will not update location hash, +// because hash updates interfere with wct_tests. +let _useHash = false; + +export function setUseHash(shouldUseHash: boolean): void { + _useHash = shouldUseHash; +} + +export function useHash(): boolean { + return _useHash; +} + +let _fakeHash = ''; + +export function setFakeHash(h: string): void { + _fakeHash = h; +} + +export function getFakeHash(): string { + return _fakeHash; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/components/legend/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/components/legend/index.ts new file mode 100644 index 000000000..c4e85d38e --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/components/legend/index.ts @@ -0,0 +1,107 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import { PolymerElement, html } from '@polymer/polymer'; +import { customElement } from '@polymer/decorators'; +@customElement('scene-legend') +class Legend extends PolymerElement { + static get template(): HTMLTemplateElement { + return html` + +
    +
    + + Module or Operators +
    +
    + + Unexpanded Module or Operators +
    + +
    + Unexpandable Node: It can be an Api, operator or module. It cannot be expanded because it has no + subnodes +
    +     +
    +
    +
    + + Api List +
    + +
    Apis between modules
    +     +
    +
    +
    + + Multi Collection +
    + +
    Fusion node Collection
    +     +
    +
    +
    + `; + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-minimap.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-minimap.ts new file mode 100644 index 000000000..5ddbc8662 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-minimap.ts @@ -0,0 +1,87 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { customElement } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import * as tf_scene_minimap from '../tf_graph_common/minimap'; + +@customElement('tf-graph-minimap') +export class TfGraphMinimap extends PolymerElement { + static readonly template = html` + + + + + + + + + + + + + + + + + `; + /** + * Initializes the minimap and returns a minimap object to notify when + * things update. + * + * @param svg The main svg element. + * @param zoomG The svg group used for panning and zooming the main svg. + * @param mainZoom The main zoom behavior. + * @param maxWAndH The maximum width/height for the minimap. + * @param labelPadding Padding in pixels due to the main graph labels. + */ + + init(svg, zoomG, mainZoom, maxWAndH, labelPadding): tf_scene_minimap.Minimap { + return new tf_scene_minimap.Minimap(svg, zoomG, mainZoom, this, maxWAndH, labelPadding); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.html.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.html.ts new file mode 100644 index 000000000..769b67f53 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.html.ts @@ -0,0 +1,820 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import { html } from '@polymer/polymer'; + +// Please keep node font-size/classnames in sync with tf-graph-common/common.ts +export const template = html` + +
    +
    +
    +
    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +`; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts new file mode 100644 index 000000000..dfc1e02b1 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts @@ -0,0 +1,747 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { customElement, observe, property } from '@polymer/decorators'; +import { PolymerElement } from '@polymer/polymer'; +import * as d3 from 'd3'; +import * as _ from 'lodash'; +import { DarkModeMixin } from '../polymer/dark_mode_mixin'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import * as tb_debug from '../tb_debug'; +import '../tf_dashboard_common/tensorboard-color'; +import * as tf_graph from '../tf_graph_common/graph'; +import * as tf_graph_layout from '../tf_graph_common/layout'; +import * as tf_graph_minimap from '../tf_graph_common/minimap'; +import * as tf_graph_scene_node from '../tf_graph_common/node'; +import * as tf_graph_render from '../tf_graph_common/render'; +import * as tf_graph_scene from '../tf_graph_common/scene'; +import { TfGraphScene } from '../tf_graph_common/tf-graph-scene'; +import * as tf_graph_util from '../tf_graph_common/util'; +import './tf-graph-minimap'; +import { template } from './tf-graph-scene.html'; + +@customElement('tf-graph-scene') +class TfGraphScene2 extends LegacyElementMixin(DarkModeMixin(PolymerElement)) implements TfGraphScene { + static readonly template = template; + @property({ type: Number }) + _step: number = 20; + + @property({ type: Number }) + _scaleStep: number = 1; + + @property({ type: Number }) + mouseX: number = 0; + + @property({ type: Number }) + mouseY: number = 0; + + @property({ type: Number }) + x: number = 0; + + @property({ type: Number }) + y: number = 0; + + @property({ type: Object }) + renderHierarchy: tf_graph_render.RenderGraphInfo; + + @property({ type: String }) + name: string; + + @property({ type: Boolean }) + traceInputs: boolean; + + // For each render hierarchy, we only fit it to the viewport once (when the scene is attached to + // the DOM). We do not fit the hierarchy again (unless the user clicks the reset button). For + // instance, if the user enters a certain view in the graph, switches to another dashboard, and + // returns to the graph dashboard, the user expects the previous view. These properties enable + // that behavior. + + /** Whether the scene has fit the current render hierarchy (to the viewport) at least once. */ + @property({ type: Boolean }) + _hasRenderHierarchyBeenFitOnce: boolean; + + /** Whether this scene element is currently attached to a parent element. */ + @property({ type: Boolean }) + _isAttached: boolean; + + /** This property is a d3_zoom object. */ + @property({ type: Object }) + _zoom: object; + + /** This property is a d3_drag object. */ + @property({ type: Object }) + _drag: object; + + @property({ + type: String, + observer: '_highlightedNodeChanged', + }) + highlightedNode: string; + + @property({ + type: String, + observer: '_selectedNodeChanged', + }) + selectedNode: string; + + @property({ + type: String, + observer: '_linkedNodeChanged', + }) + linkedNode: string; + + // An optional callback that implements the tf.graph.edge.EdgeSelectionCallback signature. If + // provided, edges are selectable, and this callback is run when an edge is selected. + @property({ type: Object }) + handleEdgeSelected: object; + + /** Keeps track of if the graph has been zoomed/panned since loading */ + @property({ + type: Boolean, + observer: '_onZoomChanged', + }) + _zoomed: boolean = false; + + /** + * Keeps track of the starting coordinates of a graph zoom/pan. + * + * @private {{x: number, y: number}?} + */ + @property({ + type: Object, + }) + _zoomStartCoords: object | null = null; + + /** + * Keeps track of the current coordinates of a graph zoom/pan + * + * @private {{x: number, y: number}?} + */ + @property({ + type: Object, + }) + _zoomTransform: object | null = null; + + /** Maximum distance of a zoom event for it to be interpreted as a click */ + @property({ + type: Number, + }) + _maxZoomDistanceForClick: number = 20; + + /* + * Dictionary for easily stylizing nodes when state changes. + * _nodeGroupIndex[nodeName] = d3_selection of the nodeGroup + */ + @property({ + type: Object, + }) + _nodeGroupIndex = {}; + + /* + * Dictionary for easily stylizing annotation nodes when state changes. + * _annotationGroupIndex[nodeName][hostNodeName] = + * d3_selection of the annotationGroup + */ + @property({ + type: Object, + }) + _annotationGroupIndex = {}; + + /* + * Dictionary for easily stylizing edges when state changes. + * _edgeGroupIndex[edgeName] = d3_selection of the edgeGroup + */ + @property({ + type: Object, + }) + _edgeGroupIndex = {}; + + /** + * Max font size for metanode label strings. + */ + @property({ + type: Number, + }) + maxMetanodeLabelLengthFontSize: number = 9; + + /** + * Min font size for metanode label strings. + */ + @property({ type: Number }) + minMetanodeLabelLengthFontSize: number = 6; + + /** + * Metanode label strings longer than this are given smaller fonts. + */ + @property({ type: Number }) + maxMetanodeLabelLengthLargeFont: number = 11; + + /** + * Metanode label strings longer than this are truncated with ellipses. + */ + @property({ type: Number }) + maxMetanodeLabelLength: number = 50; + + @property({ type: Object }) + progress: any; + + // An array of ContextMenuItem objects. Items that appear in the context + // menu for a node. + @property({ type: Array }) + nodeContextMenuItems: unknown[]; + + /** + * A minimap object to notify for zoom events. + */ + private minimap: tf_graph_minimap.Minimap; + + @observe('renderHierarchy') + _renderHierarchyChanged(): void { + let renderHierarchy = this.renderHierarchy; + this._hasRenderHierarchyBeenFitOnce = false; + this._resetState(); + this._build(renderHierarchy); + } + + // Animation and fitting must come after the observer for the hierarchy changing because we must + // first build the render hierarchy. + @observe('_isAttached', 'renderHierarchy') + _animateAndFit(): void { + const isAttached = this._isAttached; + if (this._hasRenderHierarchyBeenFitOnce || !isAttached) { + // Do not animate and fit if the scene has already fitted this render hierarchy once. Or if + // the graph dashboard is not attached (in which case the scene lacks DOM info for fitting). + return; + } + // Fit to screen after the graph is done animating. + setTimeout(this.fit.bind(this), tf_graph_layout.PARAMS.animation.duration); + } + + // When renderHierarchy changes, we need to first build the new SVG based + // on the new hierarchy (and it is asynchronous). We will let that observer + // update the input trace. + @observe('traceInputs', 'selectedNode') + _updateInputTrace(): void { + tf_graph_scene_node.updateInputTrace( + this.getGraphSvgRoot(), + this.renderHierarchy, + this.selectedNode, + this.traceInputs, + ); + } + + getNode(nodeName): tf_graph_render.RenderNodeInfo { + return this.renderHierarchy.getRenderNodeByName(nodeName); + } + + isNodeExpanded(node): boolean { + return node.expanded; + } + + setNodeExpanded(renderNode): void { + this._build(this.renderHierarchy); + this._updateLabels(!this._zoomed); + } + + /** + * Pans to a node. Assumes that the node exists. + * @param nodeName {string} The name of the node to pan to. + */ + panToNode(nodeName): void { + const zoomed = tf_graph_scene.panToNode(nodeName, this.$.svg, this.$.root, this._zoom); + if (zoomed) { + this._zoomed = true; + } + } + + /** + * Returns the outer-most SVG that renders the graph. + */ + getGraphSvgRoot(): SVGElement { + return this.$.svg as SVGElement; + } + + getContextMenu(): HTMLElement { + return this.$.contextMenu as HTMLElement; + } + + /** + * Resets the state of the component. Called whenever the whole graph + * (dataset) changes. + */ + _resetState(): void { + // Reset the state of the component. + this._nodeGroupIndex = {}; + this._annotationGroupIndex = {}; + this._edgeGroupIndex = {}; + this._updateLabels(false); + // Remove all svg elements under the 'root' svg group. + d3.select(this.$.svg).select('#root').selectAll('*').remove(); + // And the defs. + tf_graph_scene_node.removeGradientDefinitions(this.$.svg as SVGElement); + } + + /** Main method for building the scene */ + _build(renderHierarchy: tf_graph_render.RenderGraphInfo): void { + if (!renderHierarchy) { + return; + } + tf_graph_util.time( + 'tf-graph-scene (layout):', + (): void => { + // layout the scene for this meta / series node + tf_graph_layout.layoutScene(renderHierarchy.root); + }, + tb_debug.GraphDebugEventId.RENDER_SCENE_LAYOUT, + ); + tf_graph_util.time( + 'tf-graph-scene (build scene):', + (): void => { + tf_graph_scene_node.buildGroupForScene(d3.select(this.$.root), renderHierarchy.root, this); + tf_graph_scene.addGraphClickListener(this.$.svg, this); + this._updateInputTrace(); + }, + tb_debug.GraphDebugEventId.RENDER_SCENE_BUILD_SCENE, + ); + // Update the minimap again when the graph is done animating. + setTimeout((): void => { + this.minimap.update(); + }, tf_graph_layout.PARAMS.animation.duration); + } + + ready(): void { + super.ready(); + this._zoom = d3 + .zoom() + .on( + 'end', + function (): void { + if (this._zoomStartCoords) { + // Calculate the total distance dragged during the zoom event. + // If it is sufficiently small, then fire an event indicating + // that zooming has ended. Otherwise wait to fire the zoom end + // event, so that a mouse click registered as part of this zooming + // is ignored (as this mouse click was part of a zooming, and should + // not be used to indicate an actual click on the graph). + let dragDistance = Math.sqrt( + Math.pow(this._zoomStartCoords.x - this._zoomTransform.x, 2) + + Math.pow(this._zoomStartCoords.y - this._zoomTransform.y, 2), + ); + if (dragDistance < this._maxZoomDistanceForClick) { + this._fireEnableClick(); + } else { + setTimeout(this._fireEnableClick.bind(this), 50); + } + } + this._zoomStartCoords = null; + }.bind(this), + ) + .on( + 'zoom', + function (): void { + this._zoomTransform = d3.event.transform; + if (!this._zoomStartCoords) { + this._zoomStartCoords = this._zoomTransform; + this.fire('disable-click'); + } + this._zoomed = true; + d3.select(this.$.root).attr('transform', d3.event.transform.toString()); + this.x = d3.event.transform.x; + this.y = d3.event.transform.y; + this.k = d3.event.transform.k; + // Notify the minimap. + this.minimap.zoom(d3.event.transform); + }.bind(this), + ); + + d3.select(this.$.svg).call(this._addEventListener.bind(this)).on('dblclick.zoom', null); + d3.select(window).on( + 'resize', + function (): void { + // Notify the minimap that the user's window was resized. + // The minimap will figure out the new dimensions of the main svg + // and will use the existing translate and scale params. + this.minimap.zoom(); + }.bind(this), + ); + // Initialize the minimap. + this.minimap = (this.$.minimap as any).init( + this.$.svg, + this.$.root, + this._zoom, + tf_graph_layout.PARAMS.minimap.size, + tf_graph_layout.PARAMS.subscene.meta.labelHeight, + ); + + // Add keyboard event listener + this._addEventListener(); + } + + _addEventListener(): void { + let isDragging = false; + let startX; + let startY; + let lastTime = 0; + const smoothFactor = 0.2; // 控制平滑的因子 + const maxDelta = 800; // 限制滚动速度 + const svgElement = this.$.svg as SVGSVGElement; + svgElement.setAttribute('tabindex', '0'); + + svgElement.addEventListener('mousedown', (event: MouseEvent) => { + isDragging = true; + startX = event.clientX; + startY = event.clientY; + svgElement.focus(); + }); + window.addEventListener('mouseup', () => { + isDragging = false; + }); + svgElement.addEventListener('mousemove', (event: MouseEvent) => { + [this.mouseX, this.mouseY] = [event.clientX, event.clientY]; + }); + // prettier-ignore + svgElement.addEventListener( + 'mousemove', // 不能根据鼠标移动来ws，提节流方法 + _.throttle((event: MouseEvent) => { + if (isDragging) { + this.x = this.x + ((event.clientX - startX) / 2); + this.y = this.y + ((event.clientY - startY) / 2); + this._moveView(); + startX = event.clientX; + startY = event.clientY; + } + }, 15), + ); // 节流，限制触发频率。每15毫秒，事件最多执行一次 + // prettier-ignore + svgElement.addEventListener('wheel', (event: WheelEvent) => { + const currentTime = performance.now(); + const deltaTime = currentTime - lastTime; + if (deltaTime > 16) { + // 确保每帧调用 + const deltaY = Math.sign(event.deltaY) * Math.min(Math.abs(event.deltaY), maxDelta); + this.y = this.y - (deltaY * smoothFactor * 2); + this._moveView(); + lastTime = currentTime; + } + }); + svgElement.addEventListener('keydown', (event: KeyboardEvent) => { + switch (event.key) { + case 'w': + case 'W': + this._scaleStep = 1.1; + this._scaleView(this._scaleStep); + break; + case 's': + case 'S': + this._scaleStep = 0.9; + this._scaleView(this._scaleStep); + break; + case 'a': + case 'A': + this.x += this._step; + this._moveView(); + break; + case 'd': + case 'D': + this.x -= this._step; + this._moveView(); + break; + default: + return; // Exit if it's not an arrow key + } + }); + } + + _scaleView(scaleFactor: number): void { + if (this._zoomTransform) { + const svgElement = this.$.svg as SVGSVGElement; + const currentTransform = d3.zoomTransform(svgElement); + const k = currentTransform.k === 0 ? 1 : currentTransform.k; + const [mouseX, mouseY] = [ + this.mouseX - svgElement.getBoundingClientRect().left, + this.mouseY - svgElement.getBoundingClientRect().top, + ]; + const translateX = (mouseX - currentTransform.x) / k; + const translateY = (mouseY - currentTransform.y) / k; + const newScale = currentTransform.k * scaleFactor; + this.x = (mouseX - translateX) * newScale; + this.y = (mouseY - translateY) * newScale; + const newTransform = d3.zoomIdentity.translate(this.x, this.y).scale(newScale); + d3.select(this.$.svg).call(d3.zoom().transform, newTransform); + d3.select(this.$.root).attr('transform', newTransform.toString()); + this._zoomTransform = newTransform; + this.minimap.zoom(newTransform); + } + } + + _moveView(): void { + if (this._zoomTransform) { + requestAnimationFrame(() => { + const svgElement = this.$.svg as SVGElement; + const currentTransform = d3.zoomTransform(svgElement); + const newTransform = d3.zoomIdentity.translate(this.x, this.y).scale(currentTransform.k); + const svgSelection = d3.select(this.$.svg); + const rootSelection = d3.select(this.$.root); + svgSelection.call(d3.zoom().transform, newTransform); + rootSelection.attr('transform', newTransform.toString()); + // 更新存储的变换对象 + this._zoomTransform = newTransform; + // 通知小地图更新，只在变换发生变化时调用 + this.minimap.zoom(newTransform); + }); + } + } + + override attached(): void { + this.set('_isAttached', true); + } + + override detached(): void { + this.set('_isAttached', false); + } + + _updateLabels(showLabels): void { + let mainGraphTitleElement = this.$$('.title') as HTMLElement; + let titleStyle = mainGraphTitleElement.style; + let auxTitleElement = this.$$('.auxTitle') as HTMLElement; + let auxTitleStyle = auxTitleElement.style; + let functionLibraryTitleStyle = (this.$$('.functionLibraryTitle') as HTMLElement).style; + const root = d3.select(this.$.svg); + let core = root.select(`.${tf_graph_scene.Class.Scene.GROUP}>.${tf_graph_scene.Class.Scene.CORE}`).node(); + const isProgressComplete = showLabels && this.progress && this.progress.value === 100 && core; + if (isProgressComplete) { + let aux = + root.select(`.${tf_graph_scene.Class.Scene.GROUP}>.${tf_graph_scene.Class.Scene.INEXTRACT}`).node() || + root.select(`.${tf_graph_scene.Class.Scene.GROUP}>.${tf_graph_scene.Class.Scene.OUTEXTRACT}`).node(); + let coreX = (core as any).getCTM().e; + let auxX = aux ? (aux as any).getCTM().e : null; + titleStyle.display = 'inline'; + titleStyle.left = `${coreX}px`; + if (auxX !== null && auxX !== coreX) { + auxTitleStyle.display = 'inline'; + // Make sure that the aux title is positioned rightwards enough so as to + // prevent overlap with the main graph title. + auxX = Math.max(coreX + mainGraphTitleElement.getBoundingClientRect().width, auxX); + auxTitleStyle.left = `${auxX}px`; + } else { + auxTitleStyle.display = 'none'; + } + let functionLibrary = root + .select(`.${tf_graph_scene.Class.Scene.GROUP}>.${tf_graph_scene.Class.Scene.FUNCTION_LIBRARY}`) + .node(); + let functionLibraryX = functionLibrary ? (functionLibrary as any).getCTM().e : null; + if (functionLibraryX !== null && functionLibraryX !== auxX) { + functionLibraryTitleStyle.display = 'inline'; + // Make sure that the function library title is positioned rightwards + // enough so as to prevent overlap with other content. + functionLibraryX = Math.max(auxX + auxTitleElement.getBoundingClientRect().width, functionLibraryX); + functionLibraryTitleStyle.left = `${functionLibraryX}px`; + } else { + functionLibraryTitleStyle.display = 'none'; + } + } else { + titleStyle.display = 'none'; + auxTitleStyle.display = 'none'; + functionLibraryTitleStyle.display = 'none'; + } + } + + fit(): void { + this._hasRenderHierarchyBeenFitOnce = true; + this._scaleStep = 1; + tf_graph_scene.fit( + this.$.svg, + this.$.root, + this._zoom, + function (): void { + this._zoomed = false; + }.bind(this), + ); + } + + getImageBlob(): Promise { + return this.minimap.getImageBlob(); + } + + isNodeSelected(n): boolean { + return n === this.selectedNode; + } + + isNodeHighlighted(n): boolean { + return n === this.highlightedNode; + } + + isNodeLinked(n): boolean { + return n === this.linkedNode; + } + + addAnnotationGroup(a, d, selection): void { + let an = a.node.name; + this._annotationGroupIndex[an] = this._annotationGroupIndex[an] || {}; + this._annotationGroupIndex[an][d.node.name] = selection; + } + + getAnnotationGroupsIndex(a): any { + return this._annotationGroupIndex[a]; + } + + removeAnnotationGroup(a, d): void { + delete this._annotationGroupIndex[a.node.name][d.node.name]; + } + + addNodeGroup(n, selection): void { + this._nodeGroupIndex[n] = selection; + } + + getNodeGroup(n): any { + return this._nodeGroupIndex[n]; + } + + removeNodeGroup(n): void { + delete this._nodeGroupIndex[n]; + } + + addEdgeGroup(n, selection): void { + this._edgeGroupIndex[n] = selection; + } + + getEdgeGroup(e): any { + return this._edgeGroupIndex[e]; + } + + /** + * Update node and annotation node of the given name. + * @param {String} n node name + */ + _updateNodeState(n): void { + let node = this.getNode(n); + if (!node) { + return; + } + let nodeGroup = this.getNodeGroup(n); + if (nodeGroup) { + tf_graph_scene_node.stylize(nodeGroup, node, this as any); + } + if ( + node.node.type === (tf_graph.NodeType.META || tf_graph.NodeType.API_LIST || tf_graph.NodeType.MULTI_COLLECTION) && + (node.node as any).associatedFunction && + !node.isLibraryFunction + ) { + // The node is that of a function call. Also link the node within the + // function library. This clarifies to the user that the library function + // is being used. + let libraryFunctionNodeName = tf_graph.FUNCTION_LIBRARY_NODE_PREFIX + (node.node as any).associatedFunction; + let functionGroup = d3.select( + `.${tf_graph_scene.Class.Scene.GROUP}>.${tf_graph_scene.Class.Scene.FUNCTION_LIBRARY} g[data-name="${libraryFunctionNodeName}"]`, + ); + tf_graph_scene_node.stylize(functionGroup, node, this as any); + } + let annotationGroupIndex = this.getAnnotationGroupsIndex(n); + _.each(annotationGroupIndex, (aGroup, hostName) => { + tf_graph_scene_node.stylize(aGroup, node, this as any, tf_graph_scene.Class.Annotation.NODE); + }); + } + + /** + * Handles new node selection. 1) Updates the selected-state of each node, + * 2) triggers input tracing. + * @param selectedNode {string} The name of the newly selected node. + * @param oldSelectedNode {string} The name of the previously selected node. + * @private + */ + _selectedNodeChanged(selectedNode, oldSelectedNode): void { + if (selectedNode === oldSelectedNode) { + return; + } + if (oldSelectedNode) { + this._updateNodeState(oldSelectedNode); + } + if (!selectedNode) { + this.set('linkedNode', ''); + return; + } + let node = this.renderHierarchy.hierarchy.node(selectedNode); + if (!node) { + return; + } + // Update the minimap to reflect the highlighted (selected) node. + (this.minimap as any).update(); + let nodeParents: string[] = []; + // Create list of all metanode parents of the selected node. + while (node.parentNode !== null && node.parentNode.name !== tf_graph.ROOT_NAME) { + node = (node as any).parentNode; + nodeParents.push(node.name); + } + // Ensure each parent metanode is built and expanded. + let topParentNodeToBeExpanded; + _.forEachRight(nodeParents, (parentName) => { + this.renderHierarchy.buildSubhierarchy(parentName); + let renderNode = this.renderHierarchy.getRenderNodeByName(parentName); + if (renderNode.node.isGroupNode && !renderNode.expanded) { + renderNode.expanded = true; + if (!topParentNodeToBeExpanded) { + topParentNodeToBeExpanded = renderNode; + } + } + }); + // If any expansion was needed to display this selected node, then + // inform the scene of the top-most expansion. + if (topParentNodeToBeExpanded) { + this.setNodeExpanded(topParentNodeToBeExpanded); + this._zoomed = true; + } + if (selectedNode) { + this._updateNodeState(selectedNode); + } + // Give time for any expanding to finish before panning to a node. + // Otherwise, the pan will be computed from incorrect measurements. + setTimeout(() => { + this.panToNode(selectedNode); + }, tf_graph_layout.PARAMS.animation.duration); + } + + _highlightedNodeChanged(highlightedNode, oldHighlightedNode): void { + if (highlightedNode === oldHighlightedNode) { + return; + } + if (highlightedNode) { + this._updateNodeState(highlightedNode); + } + if (oldHighlightedNode) { + this._updateNodeState(oldHighlightedNode); + } + } + + _linkedNodeChanged(linkedNode, oldLinkedNode): void { + if (linkedNode === oldLinkedNode) { + return; + } + if (oldLinkedNode) { + this._updateNodeState(oldLinkedNode); + } + if (linkedNode) { + this._updateNodeState(linkedNode); + } + this._build(this.renderHierarchy); + } + + _onZoomChanged(): void { + this._updateLabels(!this._zoomed); + } + + _fireEnableClick(): void { + this.fire('enable-click'); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts new file mode 100644 index 000000000..da6231630 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts @@ -0,0 +1,676 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { customElement, observe, property } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import * as d3 from 'd3'; +import * as _ from 'lodash'; +import '../polymer/irons_and_papers'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import * as tb_debug from '../tb_debug'; +import * as tf_graph from '../tf_graph_common/graph'; +import * as tf_graph_hierarchy from '../tf_graph_common/hierarchy'; +import * as tf_graph_render from '../tf_graph_common/render'; +import * as tf_graph_scene from '../tf_graph_common/scene'; +import * as tf_graph_util from '../tf_graph_common/util'; +import * as tf_graph_layout from '../tf_graph_common/layout'; +import './tf-graph-scene'; +import './components/legend/index'; +import { Selection } from '../tf_graph_controls/tf-graph-controls'; +import { fetchPbTxt, parseGraphPbTxt } from '../tf_graph_common/parser'; +import * as tf_hierarchy from '../tf_graph_common/hierarchy'; +import * as tf_graph_parser from '../tf_graph_common/parser'; + +import { BENCH_PREFIX } from '../tf_graph_common/common'; + +let _isRankJump = ''; + +export function setRankJump(value: string): void { + _isRankJump = value; +} + +@customElement('tf-graph') +class TfGraph extends LegacyElementMixin(PolymerElement) { + static readonly template = html` + + +
    +
    + + +
    + +
    + `; + + @property({ + type: Object, + notify: true, + observer: '_graphChanged', + }) + graphHierarchy: tf_graph_hierarchy.MergedHierarchy; + + @property({ type: Object }) + hierarchyParams: tf_graph_hierarchy.HierarchyParams; + + @property({ type: Object, notify: true }) + progress: object; + + @property({ type: String }) + override title: string; + + @property({ type: String, notify: true }) + selectedNode: string; + + @property({ type: String, notify: true }) + linkedNode: string; + + @property({ type: Object, notify: true }) + selectedEdge: object; + + @property({ type: Object }) + _lastSelectedEdgeGroup: any; + + @property({ type: Object }) + _lastHighlightedEdgeGroup: any; + + @property({ type: String, notify: true }) + highlightedNode: string; + + @property({ type: Object, notify: true }) + highlightedEdge: tf_graph_render.EdgeData; + + @property({ + type: Object, + readOnly: true, + notify: true, + }) + renderHierarchy: tf_graph_render.MergedRenderGraphInfo; + + @property({ type: Boolean }) + traceInputs: boolean; + + @property({ type: Array }) + nodeContextMenuItems: unknown[]; + + @property({ type: Number }) + _renderDepth: number = 1; + + @property({ type: Boolean }) + _allowGraphSelect: boolean = true; + + @property({ type: Object }) + edgeWidthFunction: any = ''; + + @property({ type: Object }) + handleNodeSelected: any = ''; + + @property({ type: Object }) + edgeLabelFunction: any = ''; + + @property({ type: Object }) + handleEdgeSelected: any = ''; + + @property({ type: Object }) + selection: Selection; + + @observe('graphHierarchy', 'edgeWidthFunction', 'handleNodeSelected', 'edgeLabelFunction', 'handleEdgeSelected') + _buildNewRenderHierarchy(): void { + let graphHierarchy = this.graphHierarchy; + if (!graphHierarchy) return; + this._buildRenderHierarchy(graphHierarchy); + } + + @observe('selectedNode') + // Called when the selected node changes, ie there is a new selected node or + // the current one is unselected. + _selectedNodeChanged(): void { + let selectedNode = this.selectedNode; + if (this.handleNodeSelected) { + // A higher-level component provided a callback. Run it. + this.handleNodeSelected(selectedNode); + } + if (!selectedNode) { + return; + } + const [selectedHierarchy, linkedHierarchy] = ( + selectedNode.startsWith(BENCH_PREFIX) + ? [this.renderHierarchy.bench, this.renderHierarchy.npu] + : [this.renderHierarchy.npu, this.renderHierarchy.bench] + ) as tf_graph_render.RenderGraphInfo[]; + let node = selectedHierarchy.hierarchy.node(selectedNode); + if (!node) { + return; + } + const linkNodes = node.nodeAttributes._linked_node; + if (Array.isArray(linkNodes)) { + let tempNode = ''; + let lastRenderNode: tf_graph_render.RenderNodeInfo | undefined; + let lastExpandStatus = false; + for (let linkNode of linkNodes) { + const renderLinkedNode = linkedHierarchy.getRenderNodeByName(linkNode); + // Expand all ancestors of the linked node. + if (renderLinkedNode) { + lastRenderNode = renderLinkedNode; + lastExpandStatus = renderLinkedNode.expanded; + renderLinkedNode.expanded = true; + tempNode = linkNode; + } else { + break; + } + } + if (lastRenderNode) { + lastRenderNode.expanded = lastExpandStatus; + } + this.set('linkedNode', tempNode); + } else { + this.set('linkedNode', ''); + } + } + + @observe('selectedNode') + async _menuSelectedNodeExpand(): Promise { + function shouldSkip(renderHierarchy: any, selectedNode: any): boolean { + const hasRenderHierarchy = !!renderHierarchy; + const isNodeRendered = + renderHierarchy.npu.renderedOpNames.includes(selectedNode) || + renderHierarchy.bench?.renderedOpNames.includes(selectedNode); + const hasSelectedNode = !!selectedNode; + + return !hasRenderHierarchy || isNodeRendered || !hasSelectedNode; + } + if (shouldSkip(this.renderHierarchy, this.selectedNode)) { + return; + } else { + const current = this.selectedNode; + const tempHierarchy = ( + current.startsWith(BENCH_PREFIX) ? this.renderHierarchy.bench : this.renderHierarchy.npu + ) as tf_graph_render.RenderGraphInfo; + const params = new URLSearchParams(); + if (this.selection.run) { + params.set('run', this.selection.run); + } + if (this.selection.tag) { + params.set('tag', this.selection.tag); + } + params.set('node', this.selectedNode); + const nodeMap = tempHierarchy.hierarchy.getNodeMap(); + const expandnodesPath = `expandnodes?${String(params)}`; + + let nodeName = ''; + try { + const expandnodeStr = await tf_graph_parser.fetchPbTxt(expandnodesPath); + let expandnodes; + try { + expandnodes = JSON.parse(new TextDecoder().decode(expandnodeStr).replace(/'/g, '"')) as object; + } catch (e) { + console.error('Parse tooltips failed, please check the format of tooltips in the input vis file'); + } + if (expandnodes[1].length === 0 && expandnodes[2].length === 0) { + return; + } + for (const i of expandnodes[1]) { + nodeName = expandnodes[0] + i; + const renderNode = tempHierarchy.getRenderNodeByName(nodeName); + if (nodeName in nodeMap && !renderNode.expanded) { + await this._nodeToggleExpand({ detail: { name: nodeName } }); + } + } + this.async(() => { + try { + this.set('selectedNode', ''); // 临时清空 + this.set('selectedNode', current); // 恢复原值 + } catch (e) { + console.error('Error during async set operation:', e); + } + }, 175); // 代码会在延迟 175 毫秒后执行, 给浏览器足够的时间来处理多层展开带来的渲染和状态变化 + } catch (error) { + console.error('Error fetching expandnodesPath:', error); + } + } + } + + @observe('selectedEdge') + // Called when the selected edge changes, ie there is a new selected edge or + // the current one is unselected. + _selectedEdgeChanged(): void { + let selectedEdge = this.selectedEdge; + this._deselectPreviousEdge(); + // Visually mark this new edge as selected. + if (selectedEdge) { + this._lastSelectedEdgeGroup.classed(tf_graph_scene.Class.Edge.SELECTED, true); + // Update the color of the marker too if the edge has one. + this._updateMarkerOfSelectedEdge(selectedEdge, true); + } + if (this.handleEdgeSelected) { + // A higher-level component provided a callback. Run it. + this.handleEdgeSelected(selectedEdge); + } + } + + @observe('highlightedEdge') + // Called when the highlighted edge changes. + _highlightedEdgeChange(): void { + let highlightedEdge = this.highlightedEdge; + this._lastHighlightedEdgeGroup.classed(tf_graph_scene.Class.Edge.HIGHLIGHTED, !!highlightedEdge); + + if (highlightedEdge) { + this._updateMarkerOfSelectedEdge(highlightedEdge, false); + } else { + this._lastHighlightedEdgeGroup + .selectAll(`path.${tf_graph_scene.Class.Edge.LINE}`) + .each((d: tf_graph_render.EdgeData, i) => { + function areEdgesEqual(edge1: any, edge2: any): boolean { + return edge1.v === edge2.v && edge1.w === edge2.w && edge1.id === edge2.id; + } + // Reset its marker. + if (d.label && !areEdgesEqual(d, this.selectedEdge)) { + const paths = this._lastHighlightedEdgeGroup.selectAll('path.edgeline'); + if (d.label.startMarkerId) { + paths.style('marker-start', `url(#${d.label.startMarkerId.replace('highlighted', 'dataflow')})`); + } + if (d.label.endMarkerId) { + paths.style('marker-end', `url(#${d.label.endMarkerId.replace('highlighted', 'dataflow')})`); + } + } + }); + } + } + + /** + * Pans to a node. Assumes that the node exists. + * @param nodeName {string} The name of the node to pan to. + */ + panToNode(nodeName): void { + (this.$$('tf-graph-scene') as any).panToNode(nodeName); + } + + ready(): void { + super.ready(); + + this.addEventListener('graph-select', this._graphSelected.bind(this)); + this.addEventListener('disable-click', this._disableClick.bind(this)); + this.addEventListener('enable-click', this._enableClick.bind(this)); + // Nodes + this.addEventListener('node-toggle-expand', this._nodeToggleExpand.bind(this)); + document.addEventListener('menu-expand-node-changed', this._handleMenuExpandNodeChanged.bind(this)); + document.addEventListener('parent-node-toggle-expand', this._parentNodeToggleExpand.bind(this)); + this.addEventListener('node-select', this._nodeSelected.bind(this)); + this.addEventListener('node-highlight', this._nodeHighlighted.bind(this)); + this.addEventListener('node-unhighlight', this._nodeUnhighlighted.bind(this)); + this.addEventListener('node-toggle-extract', this._nodeToggleExtract.bind(this)); + // Edges + this.addEventListener('edge-select', this._edgeSelected.bind(this)); + this.addEventListener('edge-highlight', this._edgeHighlighted.bind(this)); + this.addEventListener('edge-unhighlight', this._edgeUnhighlighted.bind(this)); + + // Annotations + + /* Note: currently highlighting/selecting annotation node has the same + * behavior as highlighting/selecting actual node so we point to the same + * set of event listeners. However, we might redesign this to be a bit + * different. + */ + this.addEventListener('annotation-select', this._nodeSelected.bind(this)); + this.addEventListener('annotation-highlight', this._nodeHighlighted.bind(this)); + this.addEventListener('annotation-unhighlight', this._nodeUnhighlighted.bind(this)); + } + + _buildRenderHierarchy(graphHierarchy: tf_graph_hierarchy.MergedHierarchy): void { + if ( + graphHierarchy.npu.root.type !== tf_graph.NodeType.META && + graphHierarchy.bench?.root.type !== tf_graph.NodeType.META + ) { + // root must be metanode but sometimes Polymer's dom-if has not + // remove tf-graph element yet in + // and thus mistakenly pass non-metanode to this module. + return; + } + + // Certain Polymer property setter are dynamically generated and is not properly + // typed. + const anyThis = this as any; + + const renderGraph = tf_graph_util.time( + 'new tf_graph_render.Hierarchy', + () => { + const npuRenderGraph = new tf_graph_render.RenderGraphInfo(graphHierarchy.npu); + const mergedRenderGraph: tf_graph_render.MergedRenderGraphInfo = { npu: npuRenderGraph }; + if (graphHierarchy.bench) { + const benchRenderGraph = new tf_graph_render.RenderGraphInfo(graphHierarchy.bench); + mergedRenderGraph.bench = benchRenderGraph; + } + return mergedRenderGraph; + }, + tb_debug.GraphDebugEventId.RENDER_BUILD_HIERARCHY, + ); + setTimeout(() => { + if (_isRankJump) { + this.fire('node-select', { name: _isRankJump }); + _isRankJump = ''; + } + }, tf_graph_layout.PARAMS.animation.duration); + anyThis._setRenderHierarchy(renderGraph); + } + + _getVisible(name: string): string { + if (!name) { + return name; + } + const tempHierarchy = ( + name.startsWith(BENCH_PREFIX) ? this.renderHierarchy.bench : this.renderHierarchy.npu + ) as tf_graph_render.RenderGraphInfo; + return tempHierarchy.getNearestVisibleAncestor(name); + } + + fit(): void { + (this.$.scene as any).fit(); + (this.$$('#bench') as any).fit(); + } + + getImageBlob(): Promise { + return (this.$.scene as any).getImageBlob(); + } + + _graphChanged(): void { + if (!this.graphHierarchy) { + return; + } + + // When a new graph is loaded, fire this event so that there is no + // info-card being displayed for the previously-loaded graph. + this.fire('graph-select'); + } + + _graphSelected(event): void { + // Graph selection is not allowed during an active zoom event, as the + // click seen during a zoom/pan is part of the zooming and does not + // indicate a user desire to click on a specific section of the graph. + if (this._allowGraphSelect) { + this.set('selectedEdge', null); + } + // Reset this variable as a bug in d3 zoom behavior can cause zoomend + // callback not to be called if a right-click happens during a zoom event. + this._allowGraphSelect = true; + } + + _disableClick(event): void { + this._allowGraphSelect = false; + } + + _enableClick(event): void { + this._allowGraphSelect = true; + } + + // Called only when a new (non-null) node is selected. + _nodeSelected(event): void { + this.set('selectedNode', event.detail.name); + this.set('selectedEdge', null); + } + + _edgeSelected(event): void { + if (this._allowGraphSelect) { + this.set('_lastSelectedEdgeGroup', event.detail.edgeGroup); + this.set('selectedEdge', event.detail.edgeData); + this.set('selectedNode', null); + } + // Reset this variable as a bug in d3 zoom behavior can cause zoomend + // callback not to be called if a right-click happens during a zoom event. + this._allowGraphSelect = true; + } + + _nodeHighlighted(event): void { + this.set('highlightedNode', event.detail.name); + } + + _edgeHighlighted(event): void { + if ( + event.detail.edgeData?.v === (this.selectedEdge as any)?.v && + event.detail.edgeData?.w === (this.selectedEdge as any)?.w && + event.detail.edgeData?.id === (this.selectedEdge as any)?.id + ) { + return; + } + this.set('_lastHighlightedEdgeGroup', event.detail.edgeGroup); + this.set('highlightedEdge', event.detail.edgeData); + } + + _nodeUnhighlighted(event): void { + this.set('highlightedNode', null); + } + + _edgeUnhighlighted(event): void { + this.set('highlightedEdge', null); + } + + async _parentNodeToggleExpand(event): Promise { + const nodeName = event.detail.nodeData.node.name; + const matched_node_link = event.detail.nodeData.node.matchedNodeLink; + if (matched_node_link) { + let matched = matched_node_link[matched_node_link.length - 1]; + this.set('selectedNode', matched); + } else { + const params = new URLSearchParams(); + params.set('run', this.selection.run); + params.set('node', nodeName); + if (this.selection.tag) { + params.set('tag', this.selection.tag); + } + params.set('batch', String(this.selection.batch === -1 ? -1 : this.selection.batch - 1)); + params.set('step', String(this.selection.step === -1 ? -1 : this.selection.step - 1)); + const parentPath = `parent?${String(params)}`; + const parentStr = await tf_graph_parser.fetchPbTxt(parentPath); + const parentNode = new TextDecoder().decode(parentStr).replace(/'/g, '"'); + this.set('selectedNode', parentNode); + } + } + + _handleMenuExpandNodeChanged(event): void { + const nodeName = event.detail.name; + const isBench = nodeName.startsWith(BENCH_PREFIX); + const open = event.detail.open; + const renderNode = isBench + ? this.renderHierarchy.bench?.getRenderNodeByName(nodeName) + : this.renderHierarchy.npu.getRenderNodeByName(nodeName); + if (renderNode) { + if (!renderNode.expanded && open === 'expand') { + this._nodeToggleExpand({ detail: { name: nodeName } }); + } else if (renderNode.expanded && open === 'unexpand') { + this._nodeToggleExpand({ detail: { name: nodeName } }); + } + } + this._nodeSelected({ detail: { name: nodeName } }); + } + + async _nodeToggleExpand(event): Promise { + // Immediately select the node that is about to be expanded. + // Compute the sub-hierarchy scene. + const nodeName = event.detail.name; + const isBench = nodeName.startsWith(BENCH_PREFIX); + const tempHierarchy = ( + isBench ? this.renderHierarchy.bench : this.renderHierarchy.npu + ) as tf_graph_render.RenderGraphInfo; + const renderNode = tempHierarchy.getRenderNodeByName(nodeName); + // Op nodes are not expandable. + if (renderNode.node.type === tf_graph.NodeType.OP) { + return; + } + if (!renderNode.expanded && !tempHierarchy.checkSubhierarchy(nodeName)) { + const params = new URLSearchParams(); + params.set('run', this.selection.run); + params.set('node', renderNode.node.name || ''); + if (this.selection.tag) { + params.set('tag', this.selection.tag); + } + params.set('batch', String(this.selection.batch === -1 ? -1 : this.selection.batch - 1)); + params.set('step', String(this.selection.step === -1 ? -1 : this.selection.step - 1)); + const graphPath = `subgraph?${String(params)}`; + const arrayBuffer = await fetchPbTxt(graphPath); // 等待 fetchPbTxt 完成 + const graphDef = await parseGraphPbTxt(arrayBuffer); // 等待 parseGraphPbTxt 完成 + const slimGraph = await tf_graph.build(graphDef, tf_graph.DefaultBuildParams, undefined); // 等待 tf_graph.build 完成 + tf_hierarchy.update(tempHierarchy.hierarchy, slimGraph, nodeName); + tempHierarchy.buildSubhierarchy(nodeName, slimGraph); + renderNode.expanded = !renderNode.expanded; + this.async(() => { + (isBench ? this.$$('#bench') : (this.$.scene as any)).setNodeExpanded(renderNode); + }, 75); + } else { + renderNode.expanded = !renderNode.expanded; + this.async(() => { + (isBench ? this.$$('#bench') : (this.$.scene as any)).setNodeExpanded(renderNode); + }, 75); + } + } + + _nodeToggleExtract(event): void { + // Toggle the include setting of the specified node appropriately. + const nodeName = event.detail.name; + this.nodeToggleExtract(nodeName); + } + + nodeToggleExtract(nodeName: string): void { + const tempHierarchy = ( + nodeName.startsWith(BENCH_PREFIX) ? this.renderHierarchy.bench : this.renderHierarchy.npu + ) as tf_graph_render.RenderGraphInfo; + const renderNode = tempHierarchy.getRenderNodeByName(nodeName); + if (renderNode.node.include === tf_graph.InclusionType.INCLUDE) { + renderNode.node.include = tf_graph.InclusionType.EXCLUDE; + } else if (renderNode.node.include === tf_graph.InclusionType.EXCLUDE) { + renderNode.node.include = tf_graph.InclusionType.INCLUDE; + } else { + renderNode.node.include = tempHierarchy.isNodeAuxiliary(renderNode) + ? tf_graph.InclusionType.INCLUDE + : tf_graph.InclusionType.EXCLUDE; + } + // Rebuild the render hierarchy. + this._buildRenderHierarchy(this.graphHierarchy); + } + + _deselectPreviousEdge(): void { + const selectedSelector = `.${tf_graph_scene.Class.Edge.SELECTED}`; + const selectedEdge = this.$.scene.shadowRoot?.querySelector(selectedSelector); + const selectedPaths = this.$.scene.shadowRoot?.querySelectorAll('path.edgeline'); + // Visually mark the previously selected edge (if any) as deselected. + if (!!selectedEdge) { + d3.select(selectedEdge) + .classed(tf_graph_scene.Class.Edge.SELECTED, false) + .each((d: any, i) => { + // Reset its marker. + if (d.label && selectedPaths) { + const paths = d3.selectAll(selectedPaths); + if (d.label.startMarkerId) { + paths.style('marker-start', `url(#${d.label.startMarkerId})`); + } + if (d.label.endMarkerId) { + paths.style('marker-end', `url(#${d.label.endMarkerId})`); + } + } + }); + } + } + + _updateMarkerOfSelectedEdge(selectedEdge, isSelected): void { + if (selectedEdge.label) { + const statsName = isSelected ? 'selected-' : 'highlighted-'; + // The marker will vary based on the direction of the edge. + const markerId = selectedEdge.label.startMarkerId || selectedEdge.label.endMarkerId; + if (markerId) { + // Find the corresponding marker for a selected edge. + const selectedMarkerId = markerId.replace('dataflow-', statsName); + let selectedMarker = this.$.scene.shadowRoot?.querySelector(`#${selectedMarkerId}`) as HTMLElement; + if (!selectedMarker) { + // The marker for a selected edge of this size does not exist yet. Create it. + const originalMarker = this.$.scene.shadowRoot?.querySelector(`#${markerId}`); + selectedMarker = originalMarker?.cloneNode(true) as HTMLElement; + selectedMarker.setAttribute('id', selectedMarkerId); + selectedMarker.classList.add(`${statsName}arrowhead`); + originalMarker?.parentNode?.appendChild(selectedMarker); + } + // Make the path use this new marker while it is selected. + const markerAttribute = selectedEdge.label.startMarkerId ? 'marker-start' : 'marker-end'; + if (isSelected) { + this._lastSelectedEdgeGroup.selectAll('path.edgeline').style(markerAttribute, `url(#${selectedMarkerId})`); + } else { + this._lastHighlightedEdgeGroup.selectAll('path.edgeline').style(markerAttribute, `url(#${selectedMarkerId})`); + } + } + } + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts new file mode 100644 index 000000000..39f7ec831 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts @@ -0,0 +1,314 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import { customElement, observe, property } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import '../polymer/irons_and_papers'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import '../tf_graph/tf-graph'; +import * as tf_graph from '../tf_graph_common/graph'; +import * as tf_graph_hierarchy from '../tf_graph_common/hierarchy'; +import * as tf_graph_render from '../tf_graph_common/render'; +import '../tf_graph_node_info/index'; +import * as _ from 'lodash'; +import { BENCH_PREFIX } from '../tf_graph_common/common'; + +/** + * Element for putting tf-graph and tf-graph-info side by side. + * + * Example + * + */ +@customElement('tf-graph-board') +class TfGraphBoard extends LegacyElementMixin(PolymerElement) { + static readonly template = html` + + +
    +
    + +
    +
    + + +
    +
    + `; + + @property({ type: Object }) + graphHierarchy: tf_graph_hierarchy.MergedHierarchy; + + @property({ type: Object }) + graph: tf_graph.MergedSlimGraph; + + @property({ type: Object }) + hierarchyParams: tf_graph_hierarchy.HierarchyParams = tf_graph_hierarchy.DefaultHierarchyParams; + + /** + * A number between 0 and 100 denoting the % of progress + * for the progress bar and the displayed message. + * @type {{value: number, msg: string}} + */ + @property({ type: Object }) + progress: object; + + @property({ type: Boolean }) + traceInputs: boolean; + + @property({ type: Boolean }) + autoExtractNodes: boolean; + + @property({ type: Object, notify: true }) + renderHierarchy: tf_graph_render.MergedRenderGraphInfo; + + // Whether debugger data is enabled for this instance of Tensorboard. + @property({ type: Boolean }) + debuggerDataEnabled: boolean; + + @property({ type: Array, notify: true }) + // An array of alerts (in chronological order) provided by debugging libraries on when bad + // values (NaN, +/- Inf) appear. + debuggerNumericAlerts: unknown[]; + + @property({ type: Boolean, notify: true }) + allStepsModeEnabled: boolean = false; + + @property({ type: Object }) + menu: any; + + @property({ type: Object }) + colorset: any; + + @property({ type: String, notify: true }) + selectedNode: string; + + @property({ type: Object, notify: true }) + selectedEdge: tf_graph_render.EdgeData; + + // A function with signature EdgeThicknessFunction that computes the + // thickness of a given edge. + @property({ type: Object }) + edgeWidthFunction: object; + + @property({ type: String }) + _highlightedNode: string; + + // An optional function that takes a node selected event (whose `detail` + // property is the selected node ... which could be null if a node is + // deselected). Called whenever a node is selected or deselected. + @property({ type: Object }) + handleNodeSelected: object; + + // An optional function that computes the label for an edge. Should + // implement the EdgeLabelFunction signature. + @property({ type: Object }) + edgeLabelFunction: object; + + // An optional callback that implements the tf.graph.edge.EdgeSelectionCallback signature. If + // provided, edges are selectable, and this callback is run when an edge is selected. + @property({ type: Object }) + handleEdgeSelected: object; + + @property({ type: Object }) + selection: object; + + @property({ type: Object }) + tooltips: object; + selectNodeCopy: string = ''; + + ready(): void { + super.ready(); + } + + fit(): void { + (this.$.graph as any).fit(); + } + + async downloadAsImage(filename: string): Promise { + const blob = await (this.$.graph as any).getImageBlob(); + const element = document.createElement('a'); + (element as any).href = (URL as any).createObjectURL(blob); + element.download = filename; + element.click(); + URL.revokeObjectURL(element.href); + } + + /** True if the progress is not complete yet (< 100 %). */ + _isNotComplete(progress): boolean { + return progress.value < 100; + } + + _getContainerClass(progress): string { + let result = 'container'; + if (progress.error) { + result += ' error'; + } + if (this._isNotComplete(progress)) { + result += ' loading'; + } + return result; + } + + _onNodeInclusionToggled(event): void { + (this.$.graph as any).nodeToggleExtract(event.detail.name); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/common.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/common.ts new file mode 100644 index 000000000..5ae3f72ee --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/common.ts @@ -0,0 +1,225 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +/** + * @fileoverview Common interfaces for the tensorflow graph visualizer. + */ +import * as d3 from 'd3'; + +export interface ProgressTracker { + updateProgress: (incrementValue: number) => void; + setMessage: (msg: string) => void; + reportError: (msg: string, err: Error) => void; +} +// Note that tf-graph-control depends on the value of the enum. +// Polymer does not let one use JS variable as a prop. +export enum SelectionType { + OP_GRAPH = 'op_graph', + CONCEPTUAL_GRAPH = 'conceptual_graph', + PROFILE = 'profile', +} + +/** Enums element class of objects in the scene */ +export const Class = { + Node: { + // element that contains nodes. + CONTAINER: 'nodes', + // element that contains detail about a node. + GROUP: 'node', + // element that contains visual elements (like rect, ellipse). + SHAPE: 'nodeshape', + OUTER: 'outer', + // <*> element(s) under SHAPE that should receive color updates. + COLOR_TARGET: 'nodecolortarget', + // element showing the node's label. + LABEL: 'nodelabel', + // element that contains all visuals for the expand/collapse + // button for expandable group nodes. + BUTTON_CONTAINER: 'buttoncontainer', + // element that surrounds expand/collapse buttons. + BUTTON_CIRCLE: 'buttoncircle', + // element of the expand button. + EXPAND_BUTTON: 'expandbutton', + // element of the collapse button. + COLLAPSE_BUTTON: 'collapsebutton', + }, + Edge: { + CONTAINER: 'edges', + GROUP: 'edge', + LINE: 'edgeline', + REFERENCE_EDGE: 'referenceedge', + REF_LINE: 'refline', + SELECTABLE: 'selectableedge', + SELECTED: 'selectededge', + STRUCTURAL: 'structural', + HIGHLIGHTED: 'highlighted', + }, + Annotation: { + OUTBOX: 'out-annotations', + INBOX: 'in-annotations', + GROUP: 'annotation', + NODE: 'annotation-node', + EDGE: 'annotation-edge', + CONTROL_EDGE: 'annotation-control-edge', + LABEL: 'annotation-label', + ELLIPSIS: 'annotation-ellipsis', + }, + Scene: { + GROUP: 'scene', + CORE: 'core', + FUNCTION_LIBRARY: 'function-library', + INEXTRACT: 'in-extract', + OUTEXTRACT: 'out-extract', + }, + Subscene: { GROUP: 'subscene' }, + OPNODE: 'op', + METANODE: 'meta', + SERIESNODE: 'series', + BRIDGENODE: 'bridge', + ELLIPSISNODE: 'ellipsis', + API_LIST: 'api_list', + MULTI_COLLECTION: 'multi_collection', +}; + +// Please keep this in sync with tf-graph-scene.html.ts. +export const FontSizeInPx: Record> = { + Edge: { + LABEL: 3.5, + }, + Annotation: { + LABEL: 5, + }, + Node: { + EXPANDED_LABEL: 9, + SERIES_LABEL: 8, + OP_LABEL: 6, + HEALTH_PILL_STAT_LABEL: 4, + }, +}; + +export const SVG_NAMESPACE = 'http://www.w3.org/2000/svg'; + +/** + * Given a container d3 selection, select a child element of a given tag and + * class. If multiple children matches the tag and class name, returns only + * the first one. + * + * @param container + * @param tagName tag name. + * @param className (optional) Class name or list of class names. + * @return selection of the element, or an empty selection + */ +export function selectChild( + container, + tagName: string, + className?: string | string[], +): d3.Selection { + let children = container.node().childNodes; + for (let i = 0; i < children.length; i++) { + let child = children[i]; + if (child.tagName === tagName) { + if (className instanceof Array) { + let hasAllClasses = true; + for (let j = 0; j < className.length; j++) { + hasAllClasses = hasAllClasses && child.classList.contains(className[j]); + } + if (hasAllClasses) { + return d3.select(child); + } + } else if (!className || child.classList.contains(className)) { + return d3.select(child); + } + } + } + return d3.select(null); +} + +/** + * Given a container d3 selection, select a child svg element of a given tag + * and class if exists or append / insert one otherwise. If multiple children + * matches the tag and class name, returns only the first one. + * + * @param container + * @param tagName tag name. + * @param className (optional) Class name or a list of class names. + * @param before (optional) reference DOM node for insertion. + * @return selection of the element + */ +export function selectOrCreateChild( + container, + tagName: string, + className?: string | string[], + before?, +): d3.Selection { + let child = selectChild(container, tagName, className); + if (!child.empty()) { + return child; + } + let newElement = document.createElementNS('http://www.w3.org/2000/svg', tagName); + if (className instanceof Array) { + for (let i = 0; i < className.length; i++) { + newElement.classList.add(className[i]); + } + } else { + newElement.classList.add(className ?? ''); + } + if (before) { + // if before exists, insert + container.node().insertBefore(newElement, before); + } else { + // otherwise, append + container.node().appendChild(newElement); + } + return ( + d3 + .select(newElement) + // need to bind data to emulate d3_selection.append + .datum(container.datum()) + ); +} + +/** The minimum stroke width of an edge. */ +export const MIN_EDGE_WIDTH = 0.75; +/** The maximum stroke width of an edge. */ +export const MAX_EDGE_WIDTH = 12; +/** The exponent used in the power scale for edge thickness. */ +const EDGE_WIDTH_SCALE_EXPONENT = 0.3; +/** The domain (min and max value) for the edge width. */ +const DOMAIN_EDGE_WIDTH_SCALE = [1, 5000000]; +export const EDGE_WIDTH_SIZE_BASED_SCALE: d3.ScalePower = d3 + .scalePow() + .exponent(EDGE_WIDTH_SCALE_EXPONENT) + .domain(DOMAIN_EDGE_WIDTH_SCALE) + .range([MIN_EDGE_WIDTH, MAX_EDGE_WIDTH]) + .clamp(true); + +export const globalTooltips: { [key: string]: string } = {}; +// NPU侧模型的节点前缀 +export const NPU_PREFIX = 'N___'; +// 标杆侧模型的节点前缀 +export const BENCH_PREFIX = 'B___'; +// 未匹配节点颜色 +export const UNMATCHED_COLOR = '#C7C7C7'; +// 展开对应侧节点 +export const EXPAND_NODE = '展开对应侧节点'; +// 数据发送 +export const DATA_SEND = '数据发送'; +// 数据接收 +export const DATA_RECEIVE = '数据接收'; +// 数据发送接收 +export const DATA_SEND_RECEIVE = '数据发送接收'; +// 数据读取时间 +export const DATA_LOAD_TIME = 3000; +// 数据过大提示时间 +export const DATA_NOTICE_TIME = 600; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/contextmenu.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/contextmenu.ts new file mode 100644 index 000000000..5f0e1d2e6 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/contextmenu.ts @@ -0,0 +1,255 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as d3 from 'd3'; +import { TfGraphScene } from './tf-graph-scene'; +import * as tf_graph_parser from '../tf_graph_common/parser'; +import { getColorByPrecisionIndex } from './node'; +import { setRankJump } from '../tf_graph/tf-graph'; +import { BENCH_PREFIX, NPU_PREFIX, EXPAND_NODE, DATA_SEND, DATA_RECEIVE, DATA_SEND_RECEIVE } from './common'; + +export interface TitleFunction { + (data: any): string; +} +/** Function that takes action based on item clicked in the context menu. */ +export interface ActionFunction { + (data: any): string; +} +/** + * The interface for an item in the context menu + */ +export interface ContextMenuItem { + title: TitleFunction; + action: ActionFunction; +} +/** + * Returns the top and left distance of the scene element from the top left + * corner of the screen. + */ +function getOffset(sceneElement): { left: number; top: number } { + let leftDistance = 0; + let topDistance = 0; + let currentElement = sceneElement; + while (currentElement && currentElement.offsetLeft >= 0 && currentElement.offsetTop >= 0) { + leftDistance += currentElement.offsetLeft - currentElement.scrollLeft; + topDistance += currentElement.offsetTop - currentElement.scrollTop; + currentElement = currentElement.offsetParent; + } + return { + left: leftDistance, + top: topDistance, + }; +} +/** + * Returns the event listener, which can be used as an argument for the d3 + * selection.on function. Renders the context menu that is to be displayed + * in response to the event. + */ +export function getMenu(sceneElement: TfGraphScene, nodeData): () => Promise { + let selectedNode = ''; + const menuNode = sceneElement.getContextMenu(); + const menuSelection = d3.select(sceneElement.getContextMenu()); + // Function called to populate the context menu. + return async function (): Promise { + // Position and display the menu. + let event = d3.event; + const sceneOffset = getOffset(sceneElement); + menuSelection + .style('display', 'block') + .style('left', `${event.clientX - sceneOffset.left + 1}px`) + .style('top', `${event.clientY - sceneOffset.top + 1}px`); + // Stop the event from propagating further. + event.preventDefault(); + event.stopPropagation(); + function maybeCloseMenu(closeEvent?: any): void { + if (closeEvent?.composedPath().includes(menuNode)) { + return; + } + menuSelection.style('display', 'none'); + document.body.removeEventListener('mousedown', maybeCloseMenu, { + capture: true, + }); + } + // Dismiss and remove the click listener as soon as there is a mousedown + // on the document. We use capture listener so no component can stop + // context menu from dismissing due to stopped propagation. + document.body.addEventListener('mousedown', maybeCloseMenu, { + capture: true, + }); + // Add provided items to the context menu. + menuSelection.text(''); + const { name } = nodeData.node; + let nodePrefix = name.substring(0, 4); + let side = ''; + let nodeName = name; + if (nodePrefix === NPU_PREFIX) { + side = 'NPU'; + nodeName = name.substring(4); + } else if (nodePrefix === BENCH_PREFIX) { + side = 'Bench'; + nodeName = name.substring(4); + } else { + nodePrefix = ''; + } + + // 设置 URL 参数 + const params = new URLSearchParams(); + params.set('side', side); + params.set('node', nodeName); + + // 获取侧路径并解析 + const sidePath = `rank?${String(params)}`; + const sideStr = await tf_graph_parser.fetchPbTxt(sidePath); + const decodedStr = new TextDecoder().decode(sideStr); + const decodedObj = JSON.parse(decodedStr); + // 构建菜单选项 + let communicationsType = decodedObj.communications_type; + const menuOptions = [{ text: EXPAND_NODE, action: 'expand' }]; + if (communicationsType || decodedObj[0]?.communications_type) { + // 定义一个函数来生成 titleText + const getTitleText = (type: string): string => { + if (type === 'send') return DATA_SEND; + if (type === 'receive') return DATA_RECEIVE; + return DATA_SEND_RECEIVE; + }; + + // 如果 communicationsType 存在，直接处理 + if (communicationsType) { + const titleText = getTitleText(communicationsType); + menuOptions.push({ text: titleText, action: 'rank' }); + } + // 如果 decodedObj 中存在 communications_type，遍历处理 + else if (decodedObj[0].communications_type) { + decodedObj.forEach((item) => { + const titleText = getTitleText(item.communications_type); + menuOptions.push({ text: titleText, action: 'rank' }); + }); + } + } + let list = menuSelection.append('ul'); + list + .selectAll('li') + .data(menuOptions) + .enter() + .append('li') + .on('click', (d, i) => { + switch (d.action) { + case 'expand': + sceneElement.fire('parent-node-toggle-expand', { nodeData }); + break; + default: + break; + } + maybeCloseMenu(); + }) + .on('mouseover', (d, i, nodes) => { + if (d.action === 'rank') { + const parentLi = d3.select(nodes[i]); + // 第一项是expand，rank一定从第二项开始，所以是i-1 + const id = decodedObj[i - 1]?.communications_type || decodedObj.communications_type; + // 检查是否已经有子菜单，防止重复添加 + if (!parentLi.select(`#submenu-${id}`).empty()) return; + // 动态生成子菜单 + let nodeInfo: Record; + if (decodedObj[0]?.communications_type) { + nodeInfo = decodedObj[i - 1]?.nodes_info ?? {}; // 如果是 undefined，使用空对象 + } else { + nodeInfo = decodedObj.nodes_info ?? {}; // 如果是 undefined，使用空对象 + } + const subMenuOptions: { text: string; action: string; color: string }[] = []; // 定义 subMenuOptions 数组的类型 + for (const [key, value] of Object.entries(nodeInfo)) { + const rank = `rank${key}`; + const screen = getColorByPrecisionIndex(String(value[0])); + const menuName = value[1]; + subMenuOptions.push({ text: rank, action: menuName, color: screen }); + } + // 定义一个函数来设置样式，减少重复代码 + const setStyle = (element, styles): void => { + Object.keys(styles).forEach((key) => { + element.style(key, styles[key]); + }); + }; + + // 常用样式 + const submenuStyles1 = { + position: 'absolute', + left: '100%', + top: '27px', + background: '#e2e2e2', + color: 'black', + }; + + const submenuStyles2 = { + ...submenuStyles1, + top: '54px', // 第二个项 + }; + + // 创建第三个样式对象，只修改 top 属性 + const submenuStyles3 = { + ...submenuStyles1, + top: '81px', // 第三个项 + }; + + // 鼠标悬停时的样式 + const hoverStyles = { + border: '1px solid #000', + color: 'black', + }; + + // 鼠标离开时的样式 + const normalStyles = { + border: '1px solid rgb(199, 199, 199)', + }; + + const submenuStyles = [submenuStyles1, submenuStyles2, submenuStyles3]; + + // 创建子菜单 + const submenu = parentLi + .append('ul') + .attr('class', 'submenu') + .attr('id', `submenu-${id}`) // 动态生成唯一的 id + .call(setStyle, submenuStyles[i - 1]); + + // 创建子菜单项 + submenu + .selectAll('li') + .data(subMenuOptions) + .enter() + .append('li') + .text((dText) => dText.text) + .style('background-color', (dColor) => dColor.color) + .call(setStyle, normalStyles) + .on('mouseover', function () { + d3.select(this).call(setStyle, hoverStyles); + }) + .on('mouseout', function () { + d3.select(this).call(setStyle, normalStyles); + }) + .on('click', (subD) => { + // 添加子菜单点击逻辑 + selectedNode = `${nodePrefix}${subD.action}`; + setRankJump(selectedNode); + sceneElement.fire('contextMenuTag-changed', parseInt(subD.text.slice(4), 10)); + maybeCloseMenu(); + }); + } + }) + .on('mouseleave', (d, i, nodes) => { + if (d.action === 'rank') { + d3.select(nodes[i]).select('.submenu').remove(); // 隐藏子菜单 + } + }) + .text((d) => d.text); + }; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/edge.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/edge.ts new file mode 100644 index 000000000..0de679a2d --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/edge.ts @@ -0,0 +1,430 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as d3 from 'd3'; +import { graphlib } from 'dagre'; +import * as _ from 'lodash'; +import * as tf_graph_common from './common'; +import { Class, MAX_EDGE_WIDTH, MIN_EDGE_WIDTH } from './common'; +import { BaseEdge, EDGE_KEY_DELIM, Metaedge, OpNode, TensorShape } from './graph'; +import * as render from './render'; +import { EdgeData } from './render'; +import { TfGraphScene } from './tf-graph-scene'; + +/** Delimiter between dimensions when showing sizes of tensors. */ +const TENSOR_SHAPE_DELIM = '\u00D7'; + +let arrowheadMap = d3 + .scaleQuantize() + .domain([MIN_EDGE_WIDTH, MAX_EDGE_WIDTH]) + .range(['small', 'medium', 'large', 'xlarge']); +/** Minimum stroke width to put edge labels in the middle of edges */ +const CENTER_EDGE_LABEL_MIN_STROKE_WIDTH = 2.5; + +/** + * Function run when an edge is selected. + */ +export interface EdgeSelectionCallback { + (edgeData: EdgeData): void; +} +export function getEdgeKey(edgeObj: EdgeData): string { + return `${edgeObj.v}${EDGE_KEY_DELIM}${edgeObj.w}${EDGE_KEY_DELIM}${edgeObj.id}`; +} +/** + * Select or Create a 'g.edges' group to a given sceneGroup + * and builds a number of 'g.edge' groups inside the group. + * + * Structure Pattern: + * + * + * + * + * + * ... + * + * + * + * @param sceneGroup container + * @param graph + * @param sceneElement polymer element. + * @return selection of the created nodeGroups + */ +export function buildGroup(sceneGroup, graph: graphlib.Graph, sceneElement: TfGraphScene): any { + const sceneComponent = sceneElement as any; + let edges: EdgeData[] = []; + edges = _.reduce( + graph.edges(), + (edgesAcc, edgeObj) => { + let edgeLabel = graph.edge(edgeObj); + edgesAcc.push({ + v: edgeObj.v, + w: edgeObj.w, + id: edgeObj.name, + label: edgeLabel, + }); + return edges; + }, + edges, + ); + let container = tf_graph_common.selectOrCreateChild(sceneGroup, 'g', Class.Edge.CONTAINER); + // Select all children and join with data. + // (Note that all children of g.edges are g.edge) + let edgeGroups = (container as any) + .selectAll(function () { + return this.childNodes; + }) + .data(edges, getEdgeKey); + // Make edges a group to support rendering multiple lines for metaedge + edgeGroups + .enter() + .append('g') + .attr('class', Class.Edge.GROUP) + .attr('data-edge', getEdgeKey) + .each(function (d: EdgeData) { + let edgeGroup = d3.select(this); + d.label.edgeGroup = edgeGroup; + // index node group for quick highlighting + sceneComponent._edgeGroupIndex[getEdgeKey(d)] = edgeGroup; + + edgeGroup + .on('click', (dClick) => { + // Stop this event's propagation so that it isn't also considered + // a graph-select. + (d3.event).stopPropagation(); + sceneComponent.fire('edge-select', { + edgeData: dClick, + edgeGroup: edgeGroup, + }); + }) + .on('mouseover', (dMouseOver) => { + sceneElement.fire('edge-highlight', { + edgeData: dMouseOver, + edgeGroup: edgeGroup, + }); + }) + .on('mouseout', (dMouseOut) => { + sceneElement.fire('edge-unhighlight', { + edgeData: dMouseOut, + edgeGroup: edgeGroup, + }); + }); + // Add line during enter because we're assuming that type of line + // normally does not change. + appendEdge(edgeGroup, d, sceneComponent); + }) + .merge(edgeGroups) + .each(function () { + position(sceneElement, this); + }) + .each(function (d) { + stylize(d3.select(this), d, sceneComponent); + }); + edgeGroups + .exit() + .each((d) => { + delete sceneComponent._edgeGroupIndex[getEdgeKey(d)]; + }) + .remove(); + return edgeGroups; +} +/** + * Returns the label for the given base edge. + * The label is the shape of the underlying tensor. + */ +export function getLabelForBaseEdge(baseEdge: BaseEdge, renderInfo: render.RenderGraphInfo): string { + const outTensorKey = baseEdge.outputTensorKey; + let shape: TensorShape = []; + if (outTensorKey?.startsWith('[')) { + shape = JSON.parse(outTensorKey) as TensorShape; + } else { + let node = renderInfo.getNodeByName(baseEdge.v ?? ''); + if (node.outputShapes == null || _.isEmpty(node.outputShapes)) { + return ''; + } + shape = node.outputShapes[baseEdge.outputTensorKey]; + } + if (shape == null) { + return ''; + } + if (shape.length === 0) { + return 'scalar'; + } + return shape + .map((size) => { + return size === -1 ? '?' : size; + }) + .join(TENSOR_SHAPE_DELIM); +} +/** + * Creates the label for the given metaedge. If the metaedge consists + * of only 1 tensor, and it's shape is known, the label will contain that + * shape. Otherwise, the label will say the number of tensors in the metaedge. + */ +export function getLabelForEdge(metaedge: Metaedge, renderInfo: render.RenderGraphInfo): string { + // Compute the label based on either tensor count or size. + let isMultiEdge = metaedge.baseEdgeList.length > 1; + return isMultiEdge + ? `${metaedge.baseEdgeList.length}tensors` + : getLabelForBaseEdge(metaedge.baseEdgeList[0], renderInfo); +} +/** + * Computes the index into a set of points that constitute a path for which the + * distance along the path from the initial point is as large as possible + * without exceeding the length. This function was introduced after the + * native getPathSegAtLength method got deprecated by SVG 2. + * @param points Array of path control points. A point has x and y properties. + * Must be of length at least 2. + * @param length The length (float). + * @param lineFunc A function that takes points and returns the "d" attribute + * of a path made from connecting the points. + * @return The index into the points array. + */ +function getPathSegmentIndexAtLength( + points: render.Point[], + length: number, + lineFunc: (points: render.Point[]) => string, +): number { + const path = document.createElementNS(tf_graph_common.SVG_NAMESPACE, 'path'); + for (let i = 1; i < points.length; i++) { + path.setAttribute('d', lineFunc(points.slice(0, i))); + if (path.getTotalLength() > length) { + // This many points has already exceeded the length. + return i - 1; + } + } + // The entire path is shorter than the specified length. + return points.length - 1; +} +/** + * Shortens the path enought such that the tip of the start/end marker will + * point to the start/end of the path. The marker can be of arbitrary size. + * + * @param points Array of path control points. + * @param marker D3 selection of the svg element. + * @param isStart Is the marker a `start-marker`. If false, the marker is + * an `end-marker`. + * @return The new array of control points. + */ +function adjustPathPointsForMarker( + points: render.Point[], + marker: d3.Selection, + isStart: boolean, +): render.Point[] { + let lineFunc = d3 + .line() + .x((d) => d.x) + .y((d) => d.y); + let path = d3.select(document.createElementNS('http://www.w3.org/2000/svg', 'path')).attr('d', lineFunc(points)); + let markerWidth = Number(marker.attr('markerWidth')); + let viewBox = marker.attr('viewBox').split(' ').map(Number); + let viewBoxWidth = viewBox[2] - viewBox[0]; + let refX = Number(marker.attr('refX')); + let pathNode = path.node(); + if (isStart) { + // The edge flows downwards. Do not make the edge go the whole way, lest we + // clobber the arrowhead. + const fractionStickingOut = 1 - refX / viewBoxWidth; + const length = markerWidth * fractionStickingOut; + const point = pathNode.getPointAtLength(length); + // Figure out how many segments of the path we need to remove in order + // to shorten the path. + // @ts-expect-error TS2345: Argument of type 'Line' is not assignable to parameter of type '(points: Point[]) => string'. + const segIndex = getPathSegmentIndexAtLength(points, length, lineFunc); + // Update the very first segment. + points[segIndex - 1] = { x: point.x, y: point.y }; + // Ignore every point before segIndex - 1. + return points.slice(segIndex - 1); + } else { + // The edge flows upwards. Do not make the edge go the whole way, lest we + // clobber the arrowhead. + const fractionStickingOut = 1 - refX / viewBoxWidth; + const length = pathNode.getTotalLength() - markerWidth * fractionStickingOut; + const point = pathNode.getPointAtLength(length); + // Figure out how many segments of the path we need to remove in order + // to shorten the path. + // @ts-expect-error TS2345: Argument of type 'Line' is not assignable to parameter of type '(points: Point[]) => string'. + const segIndex = getPathSegmentIndexAtLength(points, length, lineFunc); + // Update the very last segment. + points[segIndex] = { x: point.x, y: point.y }; + // Ignore every point after segIndex. + return points.slice(0, segIndex + 1); + } +} +/** + * For a given d3 selection and data object, create a path to represent the + * edge described in d.label. + * + * If d.label is defined, it will be a RenderMetaedgeInfo instance. It + * will sometimes be undefined, for example for some Annotation edges for which + * there is no underlying Metaedge in the hierarchical graph. + */ +export function appendEdge( + edgeGroup, + d: EdgeData, + sceneElement: { + renderHierarchy: render.RenderGraphInfo; + handleEdgeSelected?: () => void; + }, + edgeClass?: string, +): void { + let edgeClassNew = edgeClass ?? Class.Edge.LINE; // set default type + if (d.label?.structural) { + edgeClassNew += ` ${Class.Edge.STRUCTURAL}`; + } + if (d.label?.metaedge?.numRefEdges) { + edgeClassNew += ` ${Class.Edge.REFERENCE_EDGE}`; + } + if (sceneElement.handleEdgeSelected) { + // The user has opted to make edges selectable. + edgeClassNew += ` ${Class.Edge.SELECTABLE}`; + } + // Give the path a unique id, which will be used to link + // the textPath (edge label) to this path. + let pathId = `path_${getEdgeKey(d)}`; + let strokeWidth; + // Encode tensor size within edge thickness. + let size = 1; + if (d.label?.metaedge) { + // There is an underlying Metaedge. + size = d.label.metaedge.totalSize; + } + strokeWidth = sceneElement.renderHierarchy.edgeWidthSizedBasedScale(size); + let path = edgeGroup + .append('path') + .attr('id', pathId) + .attr('class', edgeClassNew) + .style('stroke-width', `${strokeWidth}px`); + // Check if there is a reference edge and add an arrowhead of the right size. + if (d.label?.metaedge) { + if (d.label.metaedge.numRefEdges) { + // We have a reference edge. + const markerId = `reference-arrowhead-${arrowheadMap(strokeWidth)}`; + path.style('marker-start', `url(#${markerId})`); + d.label.startMarkerId = markerId; + } else { + // We have a dataflow edge. + const markerId = `dataflow-arrowhead-${arrowheadMap(strokeWidth)}`; + path.style('marker-end', `url(#${markerId})`); + d.label.endMarkerId = markerId; + } + } + if (d.label == null || d.label.metaedge == null) { + // There is no associated metaedge, thus no text. + // This happens for annotation edges. + return; + } + let labelForEdge = getLabelForEdge(d.label.metaedge, sceneElement.renderHierarchy); + if (labelForEdge == null) { + // We have no information to show on this edge. + return; + } + // Put edge label in the middle of edge only if the edge is thick enough. + let baseline = strokeWidth > CENTER_EDGE_LABEL_MIN_STROKE_WIDTH ? 'central' : 'text-after-edge'; + edgeGroup + .append('text') + .append('textPath') + .attr('xlink:href', `#${pathId}`) + .attr('startOffset', '50%') + .attr('text-anchor', 'middle') + .attr('dominant-baseline', 'central') + .text(labelForEdge); +} +export const interpolate: d3.Line<{ + x: number; + y: number; +}> = d3 + .line<{ + x: number; + y: number; + }>() + .curve(d3.curveBasis) + .x((d) => { + return d.x; + }) + .y((d) => { + return d.y; + }); +/** + * Returns a tween interpolator for the endpoint of an edge path. + */ +function getEdgePathInterpolator( + component: HTMLElement, + renderPath: SVGPathElement, + d: EdgeData, + i: number, + a: SVGPathElement[], +): ((t: number) => string) | ((t: any) => string | null) { + let renderMetaedgeInfo = d.label; + let adjoiningMetaedge = renderMetaedgeInfo.adjoiningMetaedge; + let points = renderMetaedgeInfo.points; + // Adjust the path so that start/end markers point to the end + // of the path. + const { shadowRoot } = component; + if (d.label.startMarkerId) { + points = adjustPathPointsForMarker( + points, + d3.select(shadowRoot?.querySelector(`#${d.label.startMarkerId}`) as Element), + true, + ); + } + if (d.label.endMarkerId) { + points = adjustPathPointsForMarker( + points, + d3.select(shadowRoot?.querySelector(`#${d.label.endMarkerId}`) as Element), + false, + ); + } + if (!adjoiningMetaedge) { + return d3.interpolate(a, interpolate(points) ?? ''); + } + // Get the adjoining path that matches the adjoining metaedge. + let adjoiningPath = (adjoiningMetaedge.edgeGroup.node()).firstChild; + // Find the desired SVGPoint along the adjoining path, then convert those + // coordinates into the space of the renderPath using its Current + // Transformation Matrix (CTM). + let inbound = renderMetaedgeInfo.metaedge?.inbound; + return function (t): string | null { + let adjoiningPoint = adjoiningPath + .getPointAtLength(inbound ? adjoiningPath.getTotalLength() : 0) + .matrixTransform(adjoiningPath.getCTM() as DOMMatrixInit) + .matrixTransform(renderPath.getCTM()?.inverse()); + // Update the relevant point in the renderMetaedgeInfo's points list, then + // re-interpolate the path. + let index = inbound ? 0 : points.length - 1; + points[index].x = adjoiningPoint.x; + points[index].y = adjoiningPoint.y; + let dPath = interpolate(points); + return dPath; + }; +} +function position(component: HTMLElement, edgeGroup: HTMLElement): void { + d3.select(edgeGroup) + .select(`path.${Class.Edge.LINE}`) + .transition() + // @ts-expect-error TS2769: No overload matches this call. complicated return type mismatch issue + .attrTween('d', function (d: EdgeData, i: number, a: SVGPathElement[]) { + return getEdgePathInterpolator(component, this as SVGPathElement, d, i, a); + }); +} +/** + * For a given d3 selection and data object, mark the edge as a control + * dependency if it contains only control edges. + * + * d's label property will be a RenderMetaedgeInfo object. + */ +export function stylize(edgeGroup, d: EdgeData, sceneElement: TfGraphScene): void { + edgeGroup.classed('faded', d.label.isFadedOut); + let metaedge = d.label.metaedge; + edgeGroup.select(`path.${Class.Edge.LINE}`).classed('control-dep', metaedge && !metaedge.numRegularEdges); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/graph.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/graph.ts new file mode 100644 index 000000000..eb37e5a2b --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/graph.ts @@ -0,0 +1,1244 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import { graphlib } from 'dagre'; +import * as _ from 'lodash'; +import * as tb_debug from '../tb_debug'; +import { ProgressTracker } from './common'; +import { Hierarchy } from './hierarchy'; +import * as tf_graph_proto from './proto'; +import * as tf_graph_util from './util'; + +export const NAMESPACE_DELIM = '/'; +export const ROOT_NAME = '__root__'; +export const FUNCTION_LIBRARY_NODE_PREFIX = '__function_library__'; +/** Attribute key used for storing attributes that are too large. */ +export const LARGE_ATTRS_KEY = '_too_large_attrs'; +/** Precision attributes are used to represent the color of nodes. */ +export const NODE_TYPE = 'node_type'; +export const PRECISION_INDEX = 'precision_index'; +export const MATCHED_NODE_LINK = 'matched_node_link'; +export const OVERFLOW_LEVEL = 'overflow_level'; +/** + * Maximum allowed size in bytes, before the attribute is considered large + * and filtered out of the graph. + */ +export const LIMIT_ATTR_SIZE = 1024; +// Separator between the source and the destination name of the edge. +export const EDGE_KEY_DELIM = '--'; +export enum GraphType { + FULL = 0, + EMBEDDED = 1, + META = 2, + SERIES = 3, + CORE = 4, + SHADOW = 5, + BRIDGE = 6, + EDGE = 7, +} +export enum NodeType { + META = 0, + OP = 1, + SERIES = 2, + BRIDGE = 3, + ELLIPSIS = 4, + MULTI_COLLECTION = 8, + API_LIST = 9, +} +/** Indicates if a node is to be included in the main graph when rendered. */ +export enum InclusionType { + INCLUDE = 0, + EXCLUDE = 1, + UNSPECIFIED = 2, +} +/** Indicates if a series is to be grouped in the graph when rendered. */ +export enum SeriesGroupingType { + GROUP = 0, + UNGROUP = 1, +} +/** Attribute key reserved for the shapes of the output tensors. */ +const OUTPUT_SHAPES_KEY = '_output_shapes'; +/** + * A BaseEdge is the label object (in the graphlib sense) for an edge in the + * original, full graph produced after parsing. Subsequent graphs, like those + * which belong to Metanodes, should not use BaseEdge objects, but instead + * contain Metaedges (which in turn may contain any number of BaseEdges). + */ +export interface BaseEdge { + isReferenceEdge: boolean; + /** The index of the output tensor of the source node. */ + outputTensorKey: string; + attr?: { + [key: string]: any; + }; + v?: string; + w?: string; +} +// Including both the NPU and benchmark slimgraph. +export interface MergedSlimGraph { + npu: SlimGraph; + bench?: SlimGraph; +} +/** + * A SlimGraph is inspired by graphlib.Graph, but having only the functionality + * that we need. + */ +export class SlimGraph { + nodes: { + [nodeName: string]: OpNode; + }; + metaNodes: { + [nodeName: string]: Metanode; + }; + edges: BaseEdge[]; + constructor() { + this.nodes = {}; + this.metaNodes = {}; + this.edges = []; + } +} +export interface NormalizedInput { + name: string; + /** The index of the output tensor of the source node. */ + outputTensorKey: string; +} +export interface BuildParams { + enableEmbedding: boolean; + inEmbeddingTypes: string[]; + outEmbeddingTypes: string[]; + refEdges: { + [inputEdge: string]: boolean; + }; +} +/** + * The most basic information about a node in the hierarchical graph. + */ +export interface Node { + /** The name of the node, used frequently to look up nodes by name. */ + name: string; + /** Which type of node this is. */ + type: NodeType; + inputData: { + [key: string]: any; + }; + outputData: { + [key: string]: any; + }; + suggestions: { + [key: string]: string; + }; + /** + * Whether this node is a type that may contain other nodes. Those types + * should extend from GroupNode. + * + * For an OpNode, isGroupNode will be false, even though it may have + * embeddings. These embedding Nodes will have their parentNode set to the + * OpNode. However, embeddings are later rendered as annotations, not as + * children to be made visible on expansion (like a Metanode or SeriesNode). + */ + isGroupNode: boolean; + /** + * The number of nodes this node represents. For OpNodes, this will be 1, and + * for GroupNodes it will be a count of the total number of descendents it + * contains. + */ + cardinality: number; + /** + * The Node which is this Node's parent. This is of type Node and not + * GroupNode because of embeddings, which will have a parent OpNode. + */ + parentNode: Node | null; + /** If the node is to be included or excluded from the main graph when + * rendered. Defaults to UNSPECIFIED, which means that the rendering + * algorithm determines if it will be included or not. Then can be set to + * INCLUDE or EXCLUDE manually by the user. + */ + include: InclusionType; + /** + * Node attributes specify customizable visual aspects of a node and + * application-specific metadata associated with a node. The name + * 'nodeAttributes' is meant to avoid naming-conflicts with the 'attr' in + * subclasses of Node. + */ + nodeAttributes: { + [key: string]: any; + }; +} +export type TensorShape = number[]; +export interface OpNode extends Node { + op: string; + attr: { + key: string; + value: any; + }[]; + inputs: NormalizedInput[]; + inEmbeddings: OpNode[]; + outEmbeddings: OpNode[]; + // The name of the SeriesNode that can contain this node in its series. + // If there is no such node, then this is null. + owningSeries: string; + /** + * Object mapping output channel string to tensor shapes. The output channel + * is a string rather than a number because within TensorFlow functions, an + * output may be a cross between an output variable and a number (combined + * with a colon) such as "foo:2" rather than just a number alone. + * + * Each tensor shape is an array of numbers, or null. Details: + * - null means unknown rank, and therefore entire shape is unknown. + * - [4, 2, 1] means rank-3 tensor of size 4x2x1. + * - [] means a scalar (rank-0 tensor). + * - [1] means rank-1 tensor of size 1 (not the same as scalar). + * - [5, -1, 3] means rank-3 tensor of shape is 5x?x3. The size + * of the middle dimension is unknown (encoded as -1). + */ + outputShapes: { + [key: string]: TensorShape; + }; + inputData: { + [key: string]: any; + }; + outputData: { + [key: string]: any; + }; + stackData: []; + matchedNodeLink: []; + suggestions: { + [key: string]: string; + }; +} +export interface BridgeNode extends Node { + /** + * Whether this bridge node represents edges coming into its parent node. + */ + inbound: boolean; +} +/** + * A node that is used when there are more than the maximum number of allowed + * annotations hanging off of a node. This node represents an ellipsis + * annotation, indicating a number of additional annotations. + */ +export interface EllipsisNode extends Node { + /** + * The number of nodes this ellipsis represents. + */ + numMoreNodes: number; + /** + * Sets the number of nodes this ellipsis represents and changes the node + * name accordingly. + */ + setNumMoreNodes: (numNodes: number) => void; +} +export interface GroupNode extends Node { + /** + * The metagraph contains nodes and metaedges between the immediate children + * of this group. The node label objects may be other GroupNodes (like + * SeriesNodes and Metanodes) or individual OpNodes. All edge label objects + * are Metaedges, each of which contains references to the original + * BaseEdge(s) from which it was created. + */ + metagraph: graphlib.Graph; + /** + * The bridgegraph contains only edges which link immediate children of this + * group with nodes outside of the metagraph. As in the metagraph, all edge + * label objects are Metaedges which contain references to the original + * BaseEdge(s) that contribute to it. + * + * For a Metaedge in the bridgegraph, its external endpoint will be the same + * as the metagraph edge from which it came. This is most easily explained + * by example. + * + * Consider an original graph that contains a BaseEdge A/B/C->Z/Y/X. + * + * +-------+ (BaseEdge) +-------+ + * | A/B/C |>----------------->| Z/Y/X | + * +-------+ +-------+ + * + * When we construct the Root's metagraph, it will contain nodes for A and Z, + * and a Metaedge A->Z. The A->Z Metaedge will contain the original BaseEdge + * A/B/C->Z/Y/X in its baseEdgeGraph. The Root's bridgegraph will always be + * empty. + * + * +---+ (Root.metagraph edge) +---+ + * | A |>--------------------------->| Z | + * +---+ +---+ + * + * Now consider the Metanode A. Its metagraph will contain a Metanode for A/B + * and no edges. A's bridgegraph will have one Metaedge from A/B->Z, which + * was derived from the Root's Metaedge A->Z. That Metaedge will contain the + * original BaseEdge in its baseEdgeGraph. + * + * +---------+ + * | A | + * | +---+ | (A.bridgegraph edge) +---+ + * | | B |>---------------------------->| Z | + * | +---+ | +---+ + * +---------+ + * + * Finally, consider the Metanode A/B. Its metagraph will contain a Metanode + * for A/B/C and again no edges. A/B's bridgegraph will have one Metaedge + * from A/B/C->Z, which was derived from A's bridgegraph Metaedge A/B->Z. + * As before, the A/B/C->Z Metaedge will contain the original BaseEdge in its + * baseEdgeGraph. + * + * +---------------+ + * | A | + * | +---------+ | + * | | B | | + * | | +---+ | | (A/B.bridgegraph edge) +---+ + * | | | C |>----------------------------------->| Z | + * | | +---+ | | +---+ + * | +---------+ | + * +---------------+ + * + * Likewise, under the Metanode Z and Z/Y, to compute the bridgegraph, we'll + * end up with Metaedges A->Z/Y and A->Z/Y/X respectively. So the original + * BaseEdge A/B/C->Z/Y/X becomes four different Metaedges in four different + * bridgegraphs: + * + * + A/B->Z in GroupNode A's bridgegraph, + * + A/B/C->Z in GroupNode A/B's bridgegraph, + * + A->Z/Y in GroupNode Z's bridgegraph, and + * + A->Z/Y/X in GroupNode Z/Y's bridgegraph. + * + * Considering any BaseEdge then, if N is the number of path segments in the + * source and M is the number of path segments in the destination, then the + * total number of bridgegraph edges you could create would be (N-1)(M-1). + * + * For this reason, it is computationally expensive to generate all the + * bridgegraphs for all the Metanodes, and instead they should be computed + * on demand as needed. + */ + bridgegraph: graphlib.Graph; + /** + * Flag indicating whether this GroupNode's metagraph contains any edges that + * are not control edges. Used to quickly determine how to draw a collapsed + * series (vertically or horizontally). + */ + hasNonControlEdges: boolean; +} +export interface Metanode extends GroupNode { + depth: number; + templateId: string; + opHistogram: { + [op: string]: number; + }; + attr: { + key: string; + value: any; + }[]; + // The name of the function this metanode is associated with if any. + associatedFunction: string; + inputData: { + [key: string]: any; + }; + outputData: { + [key: string]: any; + }; + stackData: []; + matchedNodeLink: []; + suggestions: { + [key: string]: string; + }; + getFirstChild: () => GroupNode | OpNode; + getRootOp: () => OpNode; + /** Return name of all leaves inside a metanode. */ + leaves: () => string[]; +} +export interface SeriesNode extends GroupNode { + hasLoop: boolean; + prefix: string; + suffix: string; + clusterId: number; + ids: number[]; + parent: string; +} +export class EllipsisNodeImpl implements EllipsisNode { + name: string; + numMoreNodes: number; + type: NodeType; + isGroupNode: boolean; + cardinality: number; + parentNode: Node | null; + include: InclusionType; + inputData: { + [key: string]: any; + }; + outputData: { + [key: string]: any; + }; + suggestions: { + [key: string]: string; + }; + nodeAttributes: { + [key: string]: any; + }; + + /** + * Constructs a new ellipsis annotation node. + * + * @param numNodes The number of additional annotations this node represents. + */ + constructor(numNodes: number) { + this.type = NodeType.ELLIPSIS; + this.isGroupNode = false; + this.cardinality = 1; + this.parentNode = null; + this.setNumMoreNodes(numNodes); + this.include = InclusionType.UNSPECIFIED; + } + + setNumMoreNodes(numNodes: number): void { + this.numMoreNodes = numNodes; + this.name = `... ${numNodes} more`; + } +} +/** + * A label object for nodes in the full graph and leaf nodes in the render + * graph. + */ +export class OpNodeImpl implements OpNode { + name: string; + op: string; + attr: { + key: string; + value: any; + }[]; + inputs: NormalizedInput[]; + type: NodeType; + isGroupNode: boolean; + cardinality: number; + inEmbeddings: OpNode[]; + outEmbeddings: OpNode[]; + parentNode: Node | null; + include: InclusionType; + owningSeries: string; + outputShapes: { + [key: string]: TensorShape; + }; + inputData: { + [key: string]: any; + }; + outputData: { + [key: string]: any; + }; + stackData: []; + matchedNodeLink: []; + suggestions: { + [key: string]: string; + }; + nodeAttributes: { + [key: string]: any; + }; + + /** + * Constructs a new Op node. + * + * @param rawNode The raw node. + */ + constructor(rawNode: tf_graph_proto.NodeDef) { + this.op = rawNode.op; + this.name = rawNode.name; + this.attr = rawNode.attr; + // An array of normalized inputs that denote the incoming edges to + // the current node. Each input contains the normalized name of the + // source node, whether it has a number part and whether it is a + // control dependency. + this.inputs = normalizeInputs(rawNode.input); + this.outputShapes = extractOutputShapes(rawNode.attr); + // additional properties + this.type = NodeType.OP; + this.isGroupNode = false; + this.cardinality = 1; + this.inEmbeddings = []; + this.outEmbeddings = []; + this.parentNode = null; + this.include = InclusionType.UNSPECIFIED; + this.owningSeries = ''; + this.inputData = rawNode.input_data; + this.outputData = rawNode.output_data; + this.suggestions = rawNode.suggestions; + this.stackData = rawNode.stack_info; + this.matchedNodeLink = rawNode.matched_node_link; + this.nodeAttributes = {}; + } +} + +export function createMetanode(name: string, opt = {}): Metanode { + return new MetanodeImpl(name, opt); +} + +export class MetanodeImpl implements Metanode { + name: string; + type: NodeType; + depth: number; + isGroupNode: boolean; + cardinality: number; + metagraph: graphlib.Graph; + bridgegraph: graphlib.Graph; + templateId: string; + opHistogram: { + [op: string]: number; + }; + parentNode: Node | null; + hasNonControlEdges: boolean; + include: InclusionType; + inputData: { + [key: string]: any; + }; + outputData: { + [key: string]: any; + }; + stackData: []; + matchedNodeLink: []; + suggestions: { + [key: string]: string; + }; + nodeAttributes: { + [key: string]: any; + }; + associatedFunction: string; + attr: { + key: string; + value: any; + }[]; + + /** A label object for meta-nodes in the graph hierarchy */ + constructor(name: string, opt = {}) { + this.name = name; + this.type = NodeType.META; + /** number of levels under this group */ + this.depth = 1; + this.isGroupNode = true; + /** # of leaf nodes (including embedded ones) */ + this.cardinality = 0; + /** graph contains metanodes, nodes, edges + * and metaedges for main items within this metanode + */ + this.metagraph = createGraph(name, GraphType.META, opt); + /** bridgegraph must be constructed lazily-see hierarchy.getBridgegraph() */ + this.bridgegraph = null; + /** + * A dictionary that count ops type of nodes in this metanode + * (op type => count). + */ + this.opHistogram = {}; + /** unique id for a metanode of similar subgraph */ + this.templateId = ''; + /** Metanode which contains this node, if any */ + this.parentNode = null; + this.hasNonControlEdges = false; + this.include = InclusionType.UNSPECIFIED; + this.associatedFunction = ''; + this.attr = []; + this.inputData = {}; + this.outputData = {}; + this.stackData = []; + this.matchedNodeLink = []; + this.suggestions = {}; + this.nodeAttributes = {}; + } + + getFirstChild(): GroupNode | OpNode { + return this.metagraph.node(this.metagraph.nodes()[0]) as any; + } + + /** + * Returns the op node associated with the metanode. + * For example, if the metanode is 'sgd', the associated + * op node is sgd/(sgd). + */ + getRootOp(): OpNode { + let nameSplit = this.name.split('/'); + let rootOpName = `${this.name}/(${nameSplit[nameSplit.length - 1]})`; + return this.metagraph.node(rootOpName) as any; + } + + /** + * Return an array of the names of all the leaves (non-GroupNodes) inside + * this metanode. This performs a breadth-first search of the tree, so + * immediate child leaves will appear earlier in the output array than + * descendant leaves. + */ + leaves(): string[] { + let leaves: string[] = []; + let queue = [this]; + let metagraph; // Defined here due to a limitation of ES6->5 compilation. + while (queue.length) { + let node = queue.shift(); + if (node?.isGroupNode) { + metagraph = (node).metagraph; + _.each(metagraph.nodes(), (name) => queue.push(metagraph.node(name))); + } else { + leaves.push(node?.name ?? ''); + } + } + return leaves; + } +} + +export interface Metaedge { + /** + * Stores the original BaseEdges represented by this Metaedge. + */ + baseEdgeList: BaseEdge[]; + /** + * Whether this edge represents a relationship that is inbound (or outbound) + * to the object which contains this information. For example, in a Metanode's + * bridgegraph, each edge connects an immediate child to something outside + * the Metanode. If the destination of the edge is inside the Metanode, then + * its inbound property should be true. If the destination is outside the + * Metanode, then its inbound property should be false. + * + * The property is optional because not all edges can be described as + * inbound/outbound. For example, in a Metanode's metagraph, all of the edges + * connect immediate children of the Metanode. None should have an inbound + * property, or they should be null/undefined. + */ + inbound?: boolean; + /** + * Number of regular edges (not control dependency edges). + */ + numRegularEdges: number; + /** + * Number of reference edges, which is an edge to an operation + * that takes a reference to its input and changes its value. + */ + numRefEdges: number; + /** + * Total size (number of units) of all the tensors flowing through this edge. + */ + totalSize: number; + addBaseEdge: (edge: BaseEdge, h: Hierarchy) => void; + v?: string; + w?: string; +} + +export function createMetaedge(v: string, w: string): Metaedge { + return new MetaedgeImpl(v, w); +} + +/** + * A label object for edges between metanodes of subgraphs in the render graph. + */ +export class MetaedgeImpl implements Metaedge { + v: string; + w: string; + baseEdgeList: BaseEdge[]; + inbound: boolean; + numRegularEdges: number; + numRefEdges: number; + totalSize: number; + constructor(v: string, w: string) { + this.v = v; + this.w = w; + this.baseEdgeList = []; + this.inbound = false; + this.numRegularEdges = 0; + this.numRefEdges = 0; + this.totalSize = 0; + } + + addBaseEdge(edge: BaseEdge, h: Hierarchy): void { + this.baseEdgeList.push(edge); + this.numRegularEdges += 1; + if (edge.isReferenceEdge) { + this.numRefEdges += 1; + } + // Compute the size of the tensor flowing through this + // base edge. + this.totalSize += (JSON.parse(edge.outputTensorKey) as number[]).reduce((accumulated, currSize) => { + let currSizeNew = currSize; + if (currSize === -1) { + currSizeNew = 1; + } + return accumulated * currSizeNew; + }, 1); + h.maxMetaEdgeSize = Math.max(h.maxMetaEdgeSize, this.totalSize); + } +} +export function createSeriesNode( + prefix: string, + suffix: string, + parent: string, + clusterId: number, + name: string, + graphOptions: LabeledGraphOptions, +): SeriesNode { + return new SeriesNodeImpl(prefix, suffix, parent, clusterId, name, graphOptions); +} + +export function getSeriesNodeName( + prefix: string, + suffix: string, + parent: string, + startId?: number, + endId?: number, +): string { + let numRepresentation = `${typeof startId !== 'undefined' && typeof endId !== 'undefined' ? '[' + startId + '-' + endId + ']' : '#'}`; + let pattern = prefix + numRepresentation + suffix; + return `${parent ? parent + '/' : ''}${pattern}`; +} + +class SeriesNodeImpl implements SeriesNode { + name: string; + type: NodeType; + hasLoop: boolean; + prefix: string; + suffix: string; + clusterId: number; + ids: number[]; + parent: string; + isGroupNode: boolean; + cardinality: number; + metagraph: graphlib.Graph; + bridgegraph: graphlib.Graph; + parentNode: Node | null; + hasNonControlEdges: boolean; + include: InclusionType; + inputData: { + [key: string]: any; + }; + outputData: { + [key: string]: any; + }; + stackData: []; + matchedNodeLink: []; + suggestions: { + [key: string]: string; + }; + nodeAttributes: { + [key: string]: any; + }; + + constructor( + prefix: string, + suffix: string, + parent: string, + clusterId: number, + name: string, + graphOptions: LabeledGraphOptions, + ) { + this.name = name || getSeriesNodeName(prefix, suffix, parent); + this.type = NodeType.SERIES; + this.hasLoop = false; + this.prefix = prefix; + this.suffix = suffix; + this.clusterId = clusterId; + this.ids = []; + this.parent = parent; + this.isGroupNode = true; + this.cardinality = 0; + this.metagraph = createGraph(name, GraphType.SERIES, graphOptions); + // bridgegraph must be constructed lazily-see hierarchy.getBridgegraph() + this.bridgegraph = null; + this.parentNode = null; + this.hasNonControlEdges = false; + this.include = InclusionType.UNSPECIFIED; + } +} + +/** + * Extracts the shapes of the output tensors from the attr property in the + * node proto. + */ +// tslint:disable-next-line:no-any +function extractOutputShapes( + attr: Array<{ + key: string; + value: any; + }>, +): { + [key: string]: TensorShape; +} { + let result = {}; + // We don't know anything about the output tensors. + if (!attr) { + return result; + } + for (let i = 0; i < attr.length; i++) { + let { key, value } = attr[i]; + if (key === OUTPUT_SHAPES_KEY) { + if (!value.list || !value.list.shape) { + // The OUTPUT_SHAPES_KEY lacks a value. We know nothing about the shape. + return {}; + } + // Map all output tensors into array of numbers denoting their shape. + result = value.list.shape.map((shape) => { + if (shape.unknown_rank) { + // This output tensor is of unknown rank. We don't know if it is a + // scalar, or a tensor, or of what shape it is. + return null; + } + if (shape.dim == null || (shape.dim.length === 1 && shape.dim[0].size == null)) { + // This output tensor is a scalar. + return []; + } + // This output tensor has a known rank. Map each dimension size + // into a number. + return shape.dim.map((dim) => { + // Size can be -1 if this particular dimension is unknown. + // If we actually have a 0-dimension tensor `dim.size` returns null, + // so we default to 0 in this case to avoid upstream null-handling + // issues. + return dim.size || 0; + }); + }); + // Since we already processed it, remove the entry from the attribute + // list (saves memory). + attr.splice(i, 1); + return result; + } + } + // We didn't find OUTPUT_SHAPES_KEY in attributes, so we don't know anything + // about the output tensors. + return result; +} + +/** + * Matches node name that encodes output tensor name and/or its index. + * - : + * - :: + */ +const INPUT_NAME_PART_MATCHER = /^(?[^:]+):((?\w+:|)\d+)$/; +/** + * Normalizes the inputs and extracts associated metadata: + * 1) Inputs can contain a colon followed by a suffix of characters. + * That suffix may be a single number (e.g. inputName:1) or several word + * characters separated from a number by a colon (e.g. inputName:foo:1). The + * latter case is used to denote inputs and outputs of functions. + * 2) Control dependency inputs contain caret at the beginning and we + * remove this and annotate the edge as a control dependency. + * @param inputs Array of unnormalized names of input nodes. + */ +function normalizeInputs(inputs?: string[]): NormalizedInput[] { + const normalizedInputs: NormalizedInput[] = []; + let lastName: string | null = null; + for (let inputName of inputs ?? []) { + let name = inputName; + let outputTensorKey = '0'; + const match = inputName.includes(':') && inputName.match(INPUT_NAME_PART_MATCHER); + if (match) { + // The output string consists of optionally several characters and a number + // separated by a colon. + name = match[1]; + outputTensorKey = match[2]; + } + + if (lastName !== name) { + lastName = name; + normalizedInputs.push({ + name: name, + outputTensorKey: outputTensorKey, + }); + } + } + return normalizedInputs; +} + +function addEdgeToGraphByAttr(graph: SlimGraph, node: OpNode | Metanode, edgeInfo: any): void { + const { shape, source, target, ...attr } = edgeInfo; + // Don't allow loops in the graph. + const isTargetAndSourceEmpty = !target && !source; + const isNodeRelated = edgeInfo.target === node.name || edgeInfo.source === node.name; + if (isTargetAndSourceEmpty || isNodeRelated) { + return; + } + let outputTensorKey = shape; + if (!shape || shape === 'N/A') { + outputTensorKey = '[]'; + } + const edge = { + v: !!target ? node.name : source, + w: target || node.name, + outputTensorKey, + isReferenceEdge: false, + attr, + }; + if (!graph.edges.find((item) => JSON.stringify(item) === JSON.stringify(edge))) { + graph.edges.push(edge); + } +} + +export const DefaultBuildParams: BuildParams = { + enableEmbedding: true, + inEmbeddingTypes: ['Const'], + outEmbeddingTypes: ['^[a-zA-Z]+Summary$'], + // This is the whitelist of inputs on op types that are considered + // reference edges. "Assign 0" indicates that the first input to + // an OpNode with operation type "Assign" is a reference edge. + refEdges: { + 'Assign 0': true, + 'AssignAdd 0': true, + 'AssignSub 0': true, + 'assign 0': true, + 'assign_add 0': true, + 'assign_sub 0': true, + 'count_up_to 0': true, + 'ScatterAdd 0': true, + 'ScatterSub 0': true, + 'ScatterUpdate 0': true, + 'scatter_add 0': true, + 'scatter_sub 0': true, + 'scatter_update 0': true, + }, +}; + +export function build( + graphDef: tf_graph_proto.GraphDef, + params: BuildParams, + tracker?: ProgressTracker, +): Promise { + /** + * A dictionary that maps each in-embedding node name to the node + * object. + */ + let inEmbedding: { + [nodeName: string]: OpNode; + } = {}; + /** + * A dictionary that maps each out-embedding node name to the node + * object. + */ + let outEmbedding: { + [nodeName: string]: OpNode; + } = {}; + /** + * A dictionary that maps each node name to an array of the node's + * out-embedding node label objects. + */ + let outEmbeddings: { + [inputName: string]: OpNode[]; + } = {}; + let isInEmbeddedPred = getEmbedPredicate(params.inEmbeddingTypes); + let isOutEmbeddedPred = getEmbedPredicate(params.outEmbeddingTypes); + let embeddingNodeNames: string[] = []; + let rawNodes = graphDef.node; + /** + * A list of all the non-embedding node names which appear in the processed + * list of raw nodes. Here we pre-allocate enough room for all the rawNodes, + * even though there will some number of embeddings. The excess array length + * is spliced off later. + * + * Experimentation shows that around 30% of the array will go unused, and + * even for very large networks that amounts to less than 10k spaces. + */ + let nodeNames = new Array(rawNodes.length); + return tf_graph_util + .runAsyncTask( + 'Normalizing names', + 30, + () => { + let opNodes = new Array(rawNodes.length); + let index = 0; + const processRawNode = (rawNode: tf_graph_proto.NodeDef): OpNodeImpl | MetanodeImpl => { + if (!rawNode.isLeaf) { + let metaNode = new MetanodeImpl(rawNode.name); + metaNode.attr = rawNode.attr; + metaNode.nodeAttributes._order = index; + if (rawNode.matched_node_link && rawNode.matched_node_link.length > 0) { + metaNode.nodeAttributes._linked_node = rawNode.matched_node_link; + } + metaNode.inputData = rawNode.input_data; + metaNode.outputData = rawNode.output_data; + metaNode.stackData = rawNode.stack_info; + metaNode.matchedNodeLink = rawNode.matched_node_link; + metaNode.suggestions = rawNode.suggestions; + if (Number(rawNode.node_type) === 1) { + metaNode.type = 0; + } else { + metaNode.type = Number(rawNode.node_type); + } + opNodes[index] = metaNode; + nodeNames[index] = metaNode.name; + index++; + return metaNode; + } else { + let opNode = new OpNodeImpl(rawNode); + opNode.nodeAttributes._order = index; + if (rawNode.matched_node_link && rawNode.matched_node_link.length > 0) { + opNode.nodeAttributes._linked_node = rawNode.matched_node_link; + } + if (isInEmbeddedPred(opNode)) { + embeddingNodeNames.push(opNode.name); + inEmbedding[opNode.name] = opNode; + return opNode; + } + if (isOutEmbeddedPred(opNode)) { + embeddingNodeNames.push(opNode.name); + outEmbedding[opNode.name] = opNode; + _.each(opNode.inputs, (input) => { + let inputName = input.name; + outEmbeddings[inputName] = outEmbeddings[inputName] || []; + outEmbeddings[inputName].push(opNode); + }); + return opNode; + } + // The node is not an embedding, so add it to the names and nodes + // lists. + opNodes[index] = opNode; + nodeNames[index] = opNode.name; + index++; + return opNode; + } + }; + _.each(rawNodes, processRawNode); + opNodes.splice(index); + nodeNames.splice(index); + return opNodes; + }, + tracker, + tb_debug.GraphDebugEventId.NORMALIZING_NAMES, + ) + .then((opNodes) => { + // Create the graph data structure from the graphlib library. + return tf_graph_util.runAsyncTask( + 'Building the data structure', + 70, + () => { + let normalizedNameDict = mapStrictHierarchy(nodeNames, embeddingNodeNames); + let graph = new SlimGraph(); + // Add the nodes to the graph. + _.each(opNodes, (opNode) => { + if (opNode instanceof OpNodeImpl) { + let normalizedName = normalizedNameDict[opNode.name] || opNode.name; + graph.nodes[normalizedName] = opNode; + // Check if the node has out-embeddings. If yes, add them to the + // node. + if (opNode.name in outEmbeddings) { + opNode.outEmbeddings = outEmbeddings[opNode.name]; + // Normalize the names of the out-embeddings. + _.each(opNode.outEmbeddings, (node) => { + node.name = normalizedNameDict[node.name] || node.name; + }); + } + // Update the name of the node. + opNode.name = normalizedName; + } else { + graph.metaNodes[opNode.name] = opNode as MetanodeImpl; + } + }); + // Visit each node's inputs to add the edges to the graph. If the + // input + // is an in-embedding, then add it to the node's in-embeddings + // instead. + _.each(opNodes, (opNode) => { + _.each(opNode.attr, ({ key, value }) => { + if (key === 'edge_info') { + addEdgeToGraphByAttr(graph, opNode, value); + } + }); + // Removes repeated edge info. + opNode.attr = _.filter(opNode.attr, ({ key, value }) => key !== 'edge_info'); + }); + // Normalize the names of in-embeddings. + _.each(inEmbedding, (node, name) => { + node.name = normalizedNameDict[node.name] || node.name; + }); + return graph; + }, + tracker, + tb_debug.GraphDebugEventId.BUILD_SLIM_GRAPH, + ); + }); +} + +/** + * Create a new graphlib.Graph() instance with default parameters + */ +export function createGraph(name: string, type, graphOptions: LabeledGraphOptions = {}): graphlib.Graph { + const graph = new graphlib.Graph({ ...graphOptions, multigraph: true }); + graph.setGraph({ + name: name, + rankdir: graphOptions.rankdir || 'TB', + type: type, + } as any); + return graph; +} + +/** + * Create a predicate for checking whether a node should be embedded based on + * the specified types. + */ +function getEmbedPredicate(types: string[]) { + return function (node: OpNode): boolean { + // check types + for (let i = 0; i < types.length; i++) { + let regExp = new RegExp(types[i]); + if (typeof node.op === 'string' && node.op.match(regExp)) { + return true; + } + } + return false; + }; +} + +/** + * Returns a strict node name (name => name/(name)) to avoid conflicts + * where the node name is also a namespace. + */ +export function getStrictName(name: string): string { + let parts = name.split(NAMESPACE_DELIM); + return `${name}${NAMESPACE_DELIM}(${parts[parts.length - 1]})`; +} + +/** + * For each op node (embedding or non-embedding), rename it if there is a + * non-embedding node under its namespace. For example, assume node name 'A'. + * If there is a non-embedding node under its namespace (e.g. 'A/B'), 'A' will + * be renamed to 'A/(A)'. Then the namespace 'A' will contain 2 nodes: '(A)' + * and 'B'. If all the nodes under 'A' are embedding nodes (e.g. constant and + * summary), keep 'A' as an Op node and don't create a namespace. + * + * @param nodeNames An array of regular (non-embedding) node names. + * @param embeddingNodeNames An array of embedding node names. + * @return Dictionary object mapping names that need to be renamed to + * new names. + */ +function mapStrictHierarchy( + nodeNames: string[], + embeddingNodeNames: string[], +): { + [oldName: string]: string; +} { + /** Dictionary that maps the old new to the new name */ + let newNameDictionary: { + [oldName: string]: string; + } = {}; + /** Set used to store all namespaces. */ + let namespaceSet: { + [namespace: string]: boolean; + } = {}; + // sort the nodes to make prefix check faster + nodeNames.sort(); + // look for nodes with a prefix a,a/b -> a/(a),a/b + for (let i = 0; i < nodeNames.length - 1; ++i) { + let a = nodeNames[i]; + // Get all the parent namespaces of the current node + // and add them in the namespace set. + _.each(getHierarchicalPath(a).slice(0, -1), (ns) => { + namespaceSet[ns] = true; + }); + for (let j = i + 1; j < nodeNames.length; ++j) { + let b = nodeNames[j]; + if (_.startsWith(b, a)) { + if (b.length > a.length && b.charAt(a.length) === NAMESPACE_DELIM) { + newNameDictionary[a] = getStrictName(a); + break; + } + } else { + break; + } + } + } + // Go through all the embedding node names and rename them in case they + // collide with namespaces. + _.each(embeddingNodeNames, (embeddingName) => { + if (embeddingName in namespaceSet) { + // Rename to follow strict hierarchy. + newNameDictionary[embeddingName] = getStrictName(embeddingName); + } + }); + return newNameDictionary; +} + +/** + * Returns a list of the degrees of each node in the graph. + */ +function degreeSequence(graph: graphlib.Graph): number[] { + let degrees = graph.nodes().map((name) => { + return graph.neighbors(name)?.length; + }); + degrees.sort(); + return degrees; +} + +/** + * Returns if the degree sequence of the two graphs is the same. + */ +export function hasSimilarDegreeSequence(graph1: graphlib.Graph, graph2: graphlib.Graph): boolean { + let dg1 = degreeSequence(graph1); + let dg2 = degreeSequence(graph2); + for (let i = 0; i < dg1.length; i++) { + if (dg1[i] !== dg2[i]) { + return false; + } + } + return true; +} + +/** + * Returns the hierarchical path of the current node, based on the node's name. + * For example, if the name is 'a/b/c', the returned path is + * ['a', 'a/b', 'a/b/c']. + */ +export function getHierarchicalPath( + name: string, + seriesNames?: { + [name: string]: string; + }, +): string[] { + let path: string[] = []; + let i = name.indexOf(NAMESPACE_DELIM); + // Push all parent portions of the path. + while (i >= 0) { + path.push(name.substring(0, i)); + i = name.indexOf(NAMESPACE_DELIM, i + 1); + } + // If the node's path is under a series, then add the series node name to the + // hierarchical path as the parent of the leaf. + if (seriesNames) { + let seriesName = seriesNames[name]; + if (seriesName) { + path.push(seriesName); + } + } + // Push the leaf of the path. + path.push(name); + return path; +} + +export interface Edges { + control: Metaedge[]; + regular: Metaedge[]; +} + +/** + * Class used to store data on library functions. This specifically stores data + * on the library function, not individual calls to those functions. + */ +export interface LibraryFunctionData { + // The metanode representing this function in the library scene group. + node: Metanode; + // A list of nodes that represent calls to this library function. + usages: Node[]; +} + +/** + * An extended variant of the options object for `graphlib.Graph`, used + * to configure a `graphlib.Graph` at its creation. + * + * Dagre's constructor has an `opts` object as a parameter, let's call it + * 'GraphCtorOptions'. The Graph's `setGraph()` has a `label` parameter, + * let's call it `LabelOptions`. + * + * Since both are configured when a `graphlib.Graph` is first initialized, + * TensorBoard's Graph code passes around this hybrid object which includes + * properties from both `GraphCtorOptions` (compound) and `LabelOptions` + * (rankdir). + */ +export interface LabeledGraphOptions { + compound?: boolean; + rankdir?: string; + multigraph?: boolean; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/hierarchy.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/hierarchy.ts new file mode 100644 index 000000000..2a75f20f5 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/hierarchy.ts @@ -0,0 +1,960 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +/** + * Package for the Graph Hierarchy for TensorFlow graph. + */ +import { graphlib } from 'dagre'; +import * as _ from 'lodash'; +import * as tb_debug from '../tb_debug'; +import { ProgressTracker } from './common'; +import * as tf_graph from './graph'; +import { + createGraph, + createMetaedge, + createMetanode, + createSeriesNode, + Edges, + getSeriesNodeName, + GraphType, + GroupNode, + Metaedge, + MetaedgeImpl, + Metanode, + Node, + NodeType, + OpNode, + ROOT_NAME, + SeriesNode, + SlimGraph, + MetanodeImpl, +} from './graph'; +import * as tf_graph_util from './util'; + +export enum HierarchyEvent { + /** + * Fired when the templates may have been updated. No event payload attached. + */ + TEMPLATES_UPDATED = 0, +} + +// A map from the name of a series node to its grouping type. +type SeriesGroupMap = Map; + +// Including both the NPU and the benchmark hierarchy. +export interface MergedHierarchy { + npu: Hierarchy; + bench?: Hierarchy; +} +/** + * Class for the Graph Hierarchy for TensorFlow graph. + */ +export class Hierarchy extends tf_graph_util.Dispatcher { + root: Metanode; + /** + * Whether at least one tensor in the graph has shape information. + */ + hasShapeInfo = false; + /** + * The maximum size across all meta edges. Used for scaling thickness. + */ + maxMetaEdgeSize = 1; + orderings: { + [nodeName: string]: { + [childName: string]: number; + }; + }; + /** + * Options passed to dagre for creating the graph. Note that the + * `compound` argument will be overridden to true. + */ + graphOptions: tf_graph.LabeledGraphOptions = {}; + + private index: { + [nodeName: string]: GroupNode | OpNode; + }; + private readonly seriesGroupMap: SeriesGroupMap; + + constructor(params: HierarchyParams) { + super(); + this.graphOptions.compound = true; + this.graphOptions.rankdir = params.rankDirection; + this.root = createMetanode(ROOT_NAME, this.graphOptions); + this.seriesGroupMap = new Map(params.seriesMap); + /** + * @type {Object} Dictionary object that maps node name to the node + * (could be op-node, metanode, or series-node) + */ + this.index = {}; + this.index[ROOT_NAME] = this.root; + this.orderings = {}; + } + + getSeriesGroupType(nodeName: string): tf_graph.SeriesGroupingType { + // If grouping was not specified, assume it should be grouped by default. + return this.seriesGroupMap.get(nodeName) ?? tf_graph.SeriesGroupingType.GROUP; + } + + setSeriesGroupType(nodeName: string, groupType: tf_graph.SeriesGroupingType): SeriesGroupMap { + return this.seriesGroupMap.set(nodeName, groupType); + } + + buildSeriesGroupMapToggled(nodeName: string): Map { + const newGroupType = + this.getSeriesGroupType(nodeName) === tf_graph.SeriesGroupingType.GROUP + ? tf_graph.SeriesGroupingType.UNGROUP + : tf_graph.SeriesGroupingType.GROUP; + return new Map([...this.seriesGroupMap, [nodeName, newGroupType]]); + } + + getNodeMap(): { + [nodeName: string]: GroupNode | OpNode; + } { + return this.index; + } + + node(name: string): GroupNode | OpNode { + return this.index[name]; + } + + setNode(name: string, node: GroupNode | OpNode): void { + this.index[name] = node; + } + + /** + * Given the name of a node in this hierarchy, get its bridgegraph, creating + * it on the fly if necessary. If the node is not a GroupNode, then this + * method returns null. If the provided name does not map to a node in the + * hierarchy, an error will be thrown. + */ + getBridgegraph(nodeName: string): graphlib.Graph { + let node = this.index[nodeName]; + if (!node) { + throw Error(`Could not find node in hierarchy: ${nodeName}`); + } + if (!('metagraph' in node)) { + return null; + } + let groupNode = node; + if (groupNode.bridgegraph) { + return groupNode.bridgegraph; + } + let bridgegraph = createGraph('BRIDGEGRAPH', GraphType.BRIDGE, this.graphOptions); + groupNode.bridgegraph = bridgegraph; + if (!node.parentNode || !('metagraph' in node.parentNode)) { + return bridgegraph; + } + let parentNode = node.parentNode; + let parentMetagraph = parentNode.metagraph; + let parentBridgegraph = this.getBridgegraph(parentNode.name); + // For each of the parent node's two Metaedge containing graphs, process + // each Metaedge involving this node. + _.each([parentMetagraph, parentBridgegraph], (parentGraph) => { + parentGraph + .edges() + .filter((e) => e.v === nodeName || e.w === nodeName) + .forEach((parentEdgeObj) => { + let inbound = parentEdgeObj.w === nodeName; + let parentMetaedge = parentGraph.edge(parentEdgeObj); + // The parent's Metaedge represents some number of underlying + // BaseEdges from the original full graph. For each of those, we need + // to determine which immediate child is involved and make sure + // there's a Metaedge in the bridgegraph that covers it. + _.each(parentMetaedge.baseEdgeList, (baseEdge) => { + // Based on the direction, figure out which is the descendant node + // and which is the 'other' node (sibling of parent or ancestor). + let [descendantName, otherName] = inbound ? [baseEdge.w, parentEdgeObj.v] : [baseEdge.v, parentEdgeObj.w]; + // Determine the immediate child containing this descendant node. + if (nodeName !== descendantName) { + let childName = this.getChildName(nodeName, descendantName); + if (!childName) { + return; + } + // Look for an existing Metaedge in the bridgegraph (or create a + // new one) that covers the relationship between child and other. + let bridgeEdgeObj = { + v: inbound ? otherName : childName, + w: inbound ? childName : otherName, + }; + let bridgeMetaedge = bridgegraph.edge(bridgeEdgeObj); + if (!bridgeMetaedge) { + bridgeMetaedge = createMetaedge(bridgeEdgeObj.v, bridgeEdgeObj.w) as any; + bridgeMetaedge.inbound = inbound; + bridgegraph.setEdge(bridgeEdgeObj.v, bridgeEdgeObj.w, bridgeMetaedge, baseEdge.attr?.id); + } + // Copy the BaseEdge from the parent's Metaedge into this + // bridgegraph Metaedge. + bridgeMetaedge.addBaseEdge(baseEdge, this); + } + }); + }); + }); + return bridgegraph; + } + + /** Given the name of a node, return its incoming metaedges. */ + getPredecessors(nodeName: string): Edges { + let node = this.index[nodeName]; + if (!node) { + throw Error(`Could not find node with name: ${nodeName}`); + } + let predecessors = this.getOneWayEdges(node, true); + // Add embedded predecessors, such as constants. + if (!node.isGroupNode) { + _.each((node).inEmbeddings, (embeddedNode) => { + _.each((node).inputs, (input) => { + if (input.name === embeddedNode.name) { + // Make a new metaedge holding the edge between the + // node and the in-embedding. + let metaedge = new MetaedgeImpl(embeddedNode.name, nodeName); + metaedge.addBaseEdge( + { + outputTensorKey: input.outputTensorKey, + isReferenceEdge: false, + v: embeddedNode.name, + w: nodeName, + }, + this, + ); + predecessors.regular.push(metaedge); + } + }); + }); + } + return predecessors; + } + + /** + * Given the name of a node, return its outgoing metaedges. + * + * This is the inverse of getPredecessors(). See that method's documentation + * for an in-depth example. + */ + getSuccessors(nodeName: string): Edges { + let node = this.index[nodeName]; + if (!node) { + throw Error(`Could not find node with name: ${nodeName}`); + } + let successors = this.getOneWayEdges(node, false); + // Add embedded successors, such as summaries. + if (!node.isGroupNode) { + _.each((node).outEmbeddings, (embeddedNode) => { + _.each(embeddedNode.inputs, (input) => { + if (input.name === nodeName) { + // Make a new metaedge holding the edge between the + // node and the out-embedding. + let metaedge = new MetaedgeImpl(nodeName, embeddedNode.name); + metaedge.addBaseEdge( + { + outputTensorKey: input.outputTensorKey, + isReferenceEdge: false, + v: nodeName, + w: embeddedNode.name, + }, + this, + ); + successors.regular.push(metaedge); + } + }); + }); + } + return successors; + } + + /** + * For a given GroupNode, get or calculate an object which describes a + * topological ordering of child nodes within that GroupNode's metagraph. + * + * This ordering is used when rendering bridge control edges which are + * sometimes backwards relative to the dataflow. + * + * For example, say we have a graph with two edges A->B and A->C, and we're + * interested in the ordering under ROOT. In this case, any of the following + * would be legitimate return values: + * + * - { 'A': 0, 'B': 1, 'C': 2 } -- most likely + * - { 'A': 0, 'B': 2, 'C': 1 } -- less likely + * - { 'A': 12, 'B': 100, 'C': 99 } -- unlikely, but still OK + * + * The algorithm does not guarantee that all numbers from 0-N (where N is + * the number of nodes) appear exactly once. Rather it guarantees that if + * there is a path between two nodes, the earlier one will have a lower + * number in the ordering hash. + * + * When generating the ordering, we ignore control Metaedges (those which + * represent only BaseEdges that have isControlDependency set to true). + * + * If there is no node with the specified name, an error is thrown. If the + * node with the specified name is not a group node, null is returned. + */ + getTopologicalOrdering(nodeName: string): { + [childName: string]: number; + } { + let node = this.index[nodeName]; + if (!node) { + throw Error(`Could not find node with name: ${nodeName}`); + } + if (!node.isGroupNode) { + return {}; + } + if (nodeName in this.orderings) { + return this.orderings[nodeName]; + } + // Mapping of a child node names to lists of their successors. + let successors: { + [childName: string]: string[]; + } = {}; + // Set of node names which have appeared as a destination. + let destinations: { + [childName: string]: boolean; + } = {}; + let metagraph = (node).metagraph; + _.each(metagraph.edges(), (e: any) => { + if (!metagraph.edge(e).numRegularEdges) { + return; // Skip control edges. + } + // Keep track of successors and destinations. + if (!(e.v in successors)) { + successors[e.v] = []; + } + successors[e.v].push(e.w); + destinations[e.w] = true; + }); + // Seed the queue with true sources (those that are not destinations). + let queue: string[] = _.difference(_.keys(successors), _.keys(destinations)); + // Produce an ordering by traversing the graph breadth first. + this.orderings[nodeName] = {}; + let ordering = this.orderings[nodeName]; + let index = 0; + while (queue.length) { + let childName = queue.shift(); + if (childName) { + ordering[childName] = index++; + _.each(successors[childName], (succName) => queue.push(succName)); + delete successors[childName]; // Prevent cycles from infinite looping. + } + } + return ordering; + } + + /** + * Utility function for determining the name of the immediate child under a + * node for a given descendant path. If the descendant corresponds to no + * immediate child, an error is thrown. + */ + private getChildName(nodeName: string, descendantName: string): string { + // Walk up the hierarchy from the descendant to find the child. + let currentNode: Node | null = this.index[descendantName]; + if (!currentNode) { + return ''; + } + while (currentNode) { + if (currentNode.parentNode && currentNode.parentNode.name === nodeName) { + return currentNode.name; + } + currentNode = currentNode.parentNode; + } + throw Error(`Could not find immediate child for descendant: ${descendantName}`); + } + + /** Helper method for getPredecessors and getSuccessors */ + private getOneWayEdges(node: GroupNode | OpNode, inEdges: boolean): tf_graph.Edges { + let edges: Edges = { control: [], regular: [] }; + // A node with no parent cannot have any edges. + if (!node.parentNode || !node.parentNode.isGroupNode) { + return edges; + } + let parentNode = node.parentNode; + let metagraph = parentNode.metagraph; + let bridgegraph = this.getBridgegraph(parentNode.name); + findEdgeTargetsInGraph(metagraph, node, inEdges, edges); + findEdgeTargetsInGraph(bridgegraph, node, inEdges, edges); + return edges; + } +} + +/** + * Internal utility function - given a graph (should be either a metagraph or a + * bridgegraph) and a node which is known to be in that graph, determine + * the other ends of edges that involve that node in the direction specified + * by whether it's inbound. + * + * For example if you wanted to find the predecessors of a node, you'd call + * this method for the parent's metagraph and bridgegraph, specifying inbound + * as true (look at the source of inbound edges to the specified node). + * + * Discovered target names are appended to the targets array. + */ +function findEdgeTargetsInGraph(graph: graphlib.Graph, node: Node, inbound: boolean, targets: Edges): void { + let edges = inbound ? graph.inEdges(node.name) : graph.outEdges(node.name); + _.each(edges, (e) => { + let metaedge = graph.edge(e); + let targetList = metaedge.numRegularEdges ? targets.regular : targets.control; + targetList.push(metaedge as any); + }); +} + +export interface HierarchyParams { + verifyTemplate: boolean; + seriesNodeMinSize: number; + // The initial map of explicit series group types. + seriesMap: SeriesGroupMap; + // This string is supplied to dagre as the 'rankdir' property for laying out + // the graph. TB, BT, LR, or RL. The default is 'BT' (bottom to top). + rankDirection: string; + // Whether to detect numeric patterns for series nodes using entire names of + // nodes. If false, only uses numeric suffixes to find patterns to collapse + // into series nodes. + useGeneralizedSeriesPatterns: boolean; +} + +export const DefaultHierarchyParams: HierarchyParams = { + verifyTemplate: true, + seriesNodeMinSize: 5, + seriesMap: new Map(), + rankDirection: 'TB', + useGeneralizedSeriesPatterns: false, +}; + +/** + * @param graph The raw graph. + * @param params Parameters used when building a hierarchy. + */ +export function build( + graph: tf_graph.SlimGraph, + params: HierarchyParams, + tracker?: ProgressTracker, +): Promise { + const h = new Hierarchy(params); + const seriesNames: { + [name: string]: string; + } = {}; + return tf_graph_util + .runAsyncTask( + 'Adding nodes', + 30, + () => { + addNodesInVis(h, graph, ROOT_NAME); + }, + tracker, + tb_debug.GraphDebugEventId.HIERARCHY_ADD_NODES, + ) + .then(() => { + return tf_graph_util.runAsyncTask( + 'Detect series', + 30, + () => { + if (params.seriesNodeMinSize > 0) { + groupSeries( + h.root, + h, + seriesNames, + params.seriesNodeMinSize, + params.seriesMap, + params.useGeneralizedSeriesPatterns, + ); + } + }, + tracker, + tb_debug.GraphDebugEventId.HIERARCHY_DETECT_SERIES, + ); + }) + .then(() => { + return tf_graph_util.runAsyncTask( + 'Adding edges', + 40, + () => { + addEdgesInVis(h, graph, ROOT_NAME); + }, + tracker, + tb_debug.GraphDebugEventId.HIERARCHY_ADD_EDGES, + ); + }) + .then(() => { + return h; + }); +} + +/** + * Updates hierarchy when the subgraph of a node is built. + * @param oldGraph + * @param slimGraph + */ +export function update(oldGraph: Hierarchy, slimGraph: tf_graph.SlimGraph, nodeName: string): void { + let node = oldGraph.node(nodeName) as Metanode; + if (node) { + addNodesInVis(oldGraph, slimGraph, nodeName); + addEdgesInVis(oldGraph, slimGraph, nodeName); + } +} + +/** + * Creates the metanodes in the hierarchical graph and assigns parent-child + * relationship between them in vis mode. + * @param h + * @param graph + * @param parentName + */ +function addNodesInVis(h: Hierarchy, graph: SlimGraph, parentName: string): void { + const parentNode = h.node(parentName); + if (!(parentNode instanceof MetanodeImpl)) { + return; + } + const orderedNodes: Array<{ idx: number; name: string; node: any }> = []; + _.each([graph.nodes, graph.metaNodes], (nodes) => { + _.each(nodes, (node) => { + node.parentNode = parentNode; + orderedNodes.push({ + idx: node.nodeAttributes._order ?? 0, + name: node.name, + node, + }); + h.setNode(node.name, node); + }); + }); + _.each( + orderedNodes.sort((a, b) => a.idx - b.idx), + (item) => { + parentNode.metagraph.setNode(item.name, item.node); + }, + ); +} + +/** + * Create edges in the metanode. + * @param h + * @param graph + * @param nodeName + */ +function addEdgesInVis(h: Hierarchy, graph: SlimGraph, nodeName: string): void { + const metaNode = h.node(nodeName); + if (!(metaNode instanceof MetanodeImpl)) { + return; + } + _.each(graph.edges, (baseEdge) => { + if (!baseEdge.v || !baseEdge.w) { + return; + } + if (!(baseEdge.w?.includes(tf_graph.NAMESPACE_DELIM) || baseEdge.v?.includes(tf_graph.NAMESPACE_DELIM))) { + const isVInNodes = baseEdge.v in graph.nodes; + const isVInMetaNodes = baseEdge.v in graph.metaNodes; + const isWInNodes = baseEdge.w in graph.nodes; + const isWInMetaNodes = baseEdge.w in graph.metaNodes; + const shouldSkip = !(isVInNodes || isVInMetaNodes) || !(isWInNodes || isWInMetaNodes); + if (shouldSkip) { + return; + } + } + const srcName = baseEdge.v; + const dstName = baseEdge.w; + let metaedge = metaNode.metagraph.edge(srcName, dstName, baseEdge.attr?.id); + if (!metaedge) { + metaedge = createMetaedge(srcName, dstName) as any; + metaNode.metagraph.setEdge(srcName, dstName, metaedge, baseEdge.attr?.id); + } + metaedge.addBaseEdge(baseEdge, h, true); + }); +} + +/** + * Using the hierarchy template information, detect series in the provided + * metanode. For each detected series, create a new SeriesNode + * and remove series members from the metanode's metagraph and move them to + * the new series node's metagraph. + * + * @param metanode + * @param hierarchy + * @param seriesNames Map of node names to their series they are contained in. + * This should be provided empty and is populated by this method. + * @param threshold If the series has this many nodes or more, then group them + * into a series. + * @param map Map of series names to their series grouping type, if one has + * been set. + * @param useGeneralizedSeriesPatterns Whether to use find patterns for series + * nodes using any parts of names of nodes. If false, only uses patterns + * discovered within numeric suffixes of nodes names. + * @return A dictionary from node name to series node name that contains the + * node. + */ +function groupSeries( + metanode: Metanode, + hierarchy: Hierarchy, + seriesNames: { + [name: string]: string; + }, + threshold: number, + seriesMap: SeriesGroupMap, + useGeneralizedSeriesPatterns: boolean, +): void { + let metagraph = metanode.metagraph; + _.each(metagraph.nodes(), (n) => { + let child = metagraph.node(n); + if (child.type === (tf_graph.NodeType.META || tf_graph.NodeType.MULTI_COLLECTION || tf_graph.NodeType.API_LIST)) { + groupSeries( + child as unknown as Metanode, + hierarchy, + seriesNames, + threshold, + seriesMap, + useGeneralizedSeriesPatterns, + ); + } + }); + let clusters = clusterNodes(metagraph); + const detectSeriesMethod = useGeneralizedSeriesPatterns + ? detectSeriesAnywhereInNodeName + : detectSeriesUsingNumericSuffixes; + let seriesDict = detectSeriesMethod(clusters, metagraph, hierarchy.graphOptions); + // Add each series node to the graph and add its grouped children to its own + // metagraph. + _.each(seriesDict, function (seriesNode: SeriesNode, seriesName: string) { + let nodeMemberNames = seriesNode.metagraph.nodes(); + _.each(nodeMemberNames, (n) => { + let child = metagraph.node(n) as any; + if (!child.owningSeries) { + child.owningSeries = seriesName; + } + }); + // If the series contains less than the threshold number of nodes, then set + // this series to be shown ungrouped in the map. + if ( + nodeMemberNames.length < threshold && + hierarchy.getSeriesGroupType(seriesNode.name) === tf_graph.SeriesGroupingType.GROUP + ) { + hierarchy.setSeriesGroupType(seriesNode.name, tf_graph.SeriesGroupingType.UNGROUP); + } + // If the series is in the map as ungrouped then do not group the series. + if (hierarchy.getSeriesGroupType(seriesNode.name) === tf_graph.SeriesGroupingType.UNGROUP) { + return; + } + hierarchy.setNode(seriesName, seriesNode); // add to the index + metagraph.setNode(seriesName, seriesNode); + _.each(nodeMemberNames, (n) => { + let child = metagraph.node(n) as any; + seriesNode.metagraph.setNode(n, child); + seriesNode.parentNode = child.parentNode; + seriesNode.cardinality++; + child.parentNode = seriesNode; + seriesNames[n] = seriesName; + // Remove now-grouped node from its original parent's metagraph. + metagraph.removeNode(n); + }); + }); +} + +/** + * Cluster op-nodes with similar op. This examines only the direct children of + * the metagraph, does not recursively check descendants. + * @return A map from op to a list of node names. + */ +function clusterNodes(metagraph: graphlib.Graph): { + [clusterId: string]: string[]; +} { + let result: { + [clusterId: string]: string[]; + } = {}; + return _.reduce( + metagraph.nodes(), + ( + clusters: { + [clusterId: string]: string[]; + }, + n: string, + ) => { + let child = metagraph.node(n); + if (child.type === (NodeType.META || NodeType.MULTI_COLLECTION || NodeType.API_LIST)) { + // skip metanodes + return clusters; + } + let template = (child as any).op; + if (template) { + clusters[template] = clusters[template] || []; + clusters[template].push(child.name); + } + return clusters; + }, + result, + ); +} + +/** + * For each cluster of op-nodes based op type, try to detect groupings. + * Infer series name using by trying to find pattern '' towards the end + * of node names. + * + * @param clusters Dictionary output from clusterNodes(). + * @param metagraph + * @return A dictionary from series name => seriesNode + */ +function detectSeriesUsingNumericSuffixes( + clusters: { + [clusterId: string]: string[]; + }, + metagraph: graphlib.Graph, + graphOptions: tf_graph.LabeledGraphOptions, +): { + [seriesName: string]: SeriesNode; +} { + let seriesDict: { + [seriesName: string]: SeriesNode; + } = {}; + _.each(clusters, function (members, clusterId: string) { + if (members.length <= 1) { + return; + } // isolated clusters can't make series + /** @type {Object} A dictionary mapping seriesName to seriesInfoArray, + * which is an array that contains objects with name, id, prefix, suffix, + * and parent properties. + */ + let candidatesDict: { + [seriesName: string]: SeriesNode[]; + } = {}; + // Group all nodes that have the same name, with the exception of a + // number at the end of the name after an underscore, which is allowed to + // vary. + _.each(members, function (name: string) { + const isGroup = name.charAt(name.length - 1) === '*'; + const namepath = name.split('/'); + const leaf = namepath[namepath.length - 1]; + const parent = namepath.slice(0, namepath.length - 1).join('/'); + const matches = leaf.match(/^((?\D*))(\d+)$/); + + let prefix; + let id; + let suffix = ''; + if (matches) { + // if found '' in the name, assign id. + prefix = matches[1]; // the front non-numeric characters + id = matches[2]; // the digits + } else { + // for node without '_', make them zero-th items. + prefix = isGroup ? leaf.substr(0, leaf.length - 1) : leaf; + id = 0; + suffix = isGroup ? '*' : ''; + } + const seriesName = getSeriesNodeName(prefix, suffix, parent); + candidatesDict[seriesName] = candidatesDict[seriesName] || []; + const seriesNode = createSeriesNode(prefix, suffix, parent, Number(id), name, graphOptions); + candidatesDict[seriesName].push(seriesNode); + }); + // In each group of nodes, group nodes in bunches that have monotonically + // increasing numbers in their names. Each of these bunches is a series. + _.each(candidatesDict, function (seriesInfoArray: SeriesNode[], seriesName) { + if (seriesInfoArray.length < 2) { + return; + } + seriesInfoArray.sort(function (a, b) { + return Number(a.clusterId) - Number(b.clusterId); + }); + // Loop through the nodes sorted by its detected series number, grouping + // all nodes with monotonically-increasing series numbers. + let seriesNodes = [seriesInfoArray[0]]; + for (let index = 1; index < seriesInfoArray.length; index++) { + let nextNode = seriesInfoArray[index]; + if (nextNode.clusterId === seriesNodes[seriesNodes.length - 1].clusterId + 1) { + seriesNodes.push(nextNode); + continue; + } + addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); + seriesNodes = [nextNode]; + } + addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); + }); + }); + return seriesDict; +} + +/** + * For each cluster of op-nodes based op type, try to detect groupings. + * Infer series name using by trying to find a pattern of numbers + * anywhere within node names. + * + * @param clusters Dictionary output from clusterNodes(). + * @param metagraph + * @return A dictionary from series name => seriesNode + */ +function detectSeriesAnywhereInNodeName( + clusters: { + [clusterId: string]: string[]; + }, + metagraph: graphlib.Graph, + graphOptions: tf_graph.LabeledGraphOptions, +): { + [seriesName: string]: SeriesNode; +} { + let seriesDict: { + [seriesName: string]: SeriesNode; + } = {}; + _.each(clusters, function (members, clusterId: string) { + if (members.length <= 1) { + return; + } // isolated clusters can't make series + /** + * @type {Object} A dictionary mapping a series name to a SeriesNode. + */ + let forwardDict: { + [seriesName: string]: SeriesNode; + } = {}; + /** + * @type {Object} A dictionary mapping member name to an array of series + * names this member could potentially be grouped under and the + * corresponding ids. + */ + let reverseDict: { + [seriesName: string]: any[]; + } = {}; + // Group all nodes that have the same name, with the exception of a + // number at the end of the name after an underscore, which is allowed to + // vary. + _.each(members, function (name: string) { + let isGroup = name.charAt(name.length - 1) === '*'; + let namepath = name.split('/'); + let leaf = namepath[namepath.length - 1]; + let parent = namepath.slice(0, namepath.length - 1).join('/'); + const numRegex = /(?\d+)/g; + let matches = []; + let matchResult; + let prefix; + let id; + let suffix; + let seriesName; + let matched = 0; + // Scan over the entire leaf name and match any possible numbers, + // and put the results into corresponding dictionaries. + while ((matchResult = numRegex.exec(leaf))) { + ++matched; + prefix = leaf.slice(0, matchResult.index); + id = matchResult[0]; + suffix = leaf.slice(matchResult.index + matchResult[0].length); + seriesName = getSeriesNodeName(prefix, suffix, parent); + forwardDict[seriesName] = forwardDict[seriesName]; + if (!forwardDict[seriesName]) { + forwardDict[seriesName] = createSeriesNode(prefix, suffix, parent, Number(id), name, graphOptions); + } + forwardDict[seriesName].ids.push(id); + reverseDict[name] = reverseDict[name] || []; + reverseDict[name].push([seriesName, id]); + } + if (matched < 1) { + prefix = isGroup ? leaf.substr(0, leaf.length - 1) : leaf; + id = 0; + suffix = isGroup ? '*' : ''; + seriesName = getSeriesNodeName(prefix, suffix, parent); + forwardDict[seriesName] = forwardDict[seriesName]; + if (!forwardDict[seriesName]) { + forwardDict[seriesName] = createSeriesNode(prefix, suffix, parent, Number(id), name, graphOptions); + } + forwardDict[seriesName].ids.push(id); + reverseDict[name] = reverseDict[name] || []; + reverseDict[name].push([seriesName, id]); + } + }); + /** @type {Object} A dictionary mapping seriesName to seriesInfoArray, + * which is an array that contains objects with name, id, prefix, suffix, + * and parent properties. + */ + let candidatesDict: { + [seriesName: string]: SeriesNode[]; + } = {}; + // For each of the member, put it into the maximum possible series, + // and create candidatesDict accordingly. + _.each(reverseDict, function (seriesNameIdArray, name) { + seriesNameIdArray.sort(function (a, b) { + return forwardDict[b[0]].ids.length - forwardDict[a[0]].ids.length; + }); + let seriesName = seriesNameIdArray[0][0]; + let id = seriesNameIdArray[0][1]; + candidatesDict[seriesName] = candidatesDict[seriesName] || []; + const namepath = name.split('/'); + const leaf = namepath[namepath.length - 1]; + const parent = namepath.slice(0, namepath.length - 1).join('/'); + let seriesNode = createSeriesNode( + forwardDict[seriesName].prefix, + forwardDict[seriesName].suffix, + parent, + Number(id), + name, + graphOptions, + ); + candidatesDict[seriesName].push(seriesNode); + }); + // In each group of nodes, group nodes in bunches that have monotonically + // increasing numbers in their names. Each of these bunches is a series. + _.each(candidatesDict, (seriesInfoArray: SeriesNode[], seriesName) => { + if (seriesInfoArray.length < 2) { + return; + } + seriesInfoArray.sort((a, b) => { + return Number(a.clusterId) - Number(b.clusterId); + }); + // Loop through the nodes sorted by its detected series number, grouping + // all nodes with monotonically-increasing series numbers. + let seriesNodes = [seriesInfoArray[0]]; + for (let index = 1; index < seriesInfoArray.length; index++) { + let nextNode = seriesInfoArray[index]; + if (nextNode.clusterId === seriesNodes[seriesNodes.length - 1].clusterId + 1) { + seriesNodes.push(nextNode); + continue; + } + addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); + seriesNodes = [nextNode]; + } + addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); + }); + }); + return seriesDict; +} + +/** + * Add a series to the provided dictionary mapping series names to series. + * + * @param seriesNodes the nodes in the series. Contains + * name, id, prefix, suffix and parent properties of the node. + * @param seriesDict the dictionary of series + * @param clusterId ID of the template of the nodes of the series + * @param metagraph + * @param graphOptions + */ +function addSeriesToDict( + seriesNodes: SeriesNode[], + seriesDict: { + [seriesName: string]: SeriesNode; + }, + clusterId: number, + metagraph: graphlib.Graph, + graphOptions: tf_graph.LabeledGraphOptions, +): void { + if (seriesNodes.length > 1) { + let curSeriesName = getSeriesNodeName( + seriesNodes[0].prefix, + seriesNodes[0].suffix, + seriesNodes[0].parent, + seriesNodes[0].clusterId, + seriesNodes[seriesNodes.length - 1].clusterId, + ); + let curSeriesNode = createSeriesNode( + seriesNodes[0].prefix, + seriesNodes[0].suffix, + seriesNodes[0].parent, + clusterId, + curSeriesName, + graphOptions, + ); + _.each(seriesNodes, (node) => { + curSeriesNode.ids.push(node.clusterId); + curSeriesNode.metagraph.setNode(node.name, metagraph.node(node.name)); + }); + seriesDict[curSeriesName] = curSeriesNode; + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/layout.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/layout.ts new file mode 100644 index 000000000..d37f852ee --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/layout.ts @@ -0,0 +1,668 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as d3 from 'd3'; +import * as dagre from 'dagre'; +import { graphlib } from 'dagre'; +import * as _ from 'lodash'; +import { NodeType } from './graph'; +import * as render from './render'; + +export const PARAMS = { + animation: { + /** Default duration for graph animations in ms. */ + duration: 250, + }, + graph: { + /** Graph parameter for metanode. */ + meta: { + /** + * Dagre's nodesep param - number of pixels that + * separate nodes horizontally in the layout. + * + */ + nodeSep: 5, + /** + * Dagre's edgesep param - number of pixels that separate + * edges horizontally in the layout. + */ + edgeSep: 5, + }, + /** Graph parameter for metanode. */ + series: { + /** + * Dagre's nodesep param - number of pixels that + * separate nodes horizontally in the layout. + * + */ + nodeSep: 5, + /** + * Dagre's ranksep param - number of pixels + * between each rank in the layout. + * + */ + rankSep: 25, + /** + * Dagre's edgesep param - number of pixels that separate + * edges horizontally in the layout. + */ + edgeSep: 5, + }, + /** + * Padding is used to correctly position the graph SVG inside of its parent + * element. The padding amounts are applied using an SVG transform of X and + * Y coordinates. + */ + padding: { paddingTop: 40, paddingLeft: 20 }, + }, + subscene: { + meta: { + paddingTop: 5, + paddingBottom: 5, + paddingLeft: 8, + paddingRight: 8, + /** + * Used to leave room for the label on top of the highest node in + * the core graph. + */ + labelHeight: 20, + /** X-space between each extracted node and the core graph. */ + extractXOffset: 15, + /** Y-space between each extracted node. */ + extractYOffset: 20, + }, + series: { + paddingTop: 10, + paddingBottom: 10, + paddingLeft: 10, + paddingRight: 10, + labelHeight: 10, + }, + }, + nodeSize: { + /** Size of meta nodes. */ + meta: { + radius: 5, + width: 60, + maxLabelWidth: 200, + /** A scale for the node's height based on number of nodes inside */ + // Hack - set this as an any type to avoid issues in exporting a type + // from an external module. + height: (d3 as any).scaleLinear().domain([1, 200]).range([15, 60]).clamp(true), + /** The radius of the circle denoting the expand button. */ + expandButtonRadius: 3, + }, + multi_collection: { + radius: 5, + width: 60, + maxLabelWidth: 200, + /** A scale for the node's height based on number of nodes inside */ + // Hack - set this as an any type to avoid issues in exporting a type + // from an external module. + height: (d3 as any).scaleLinear().domain([1, 200]).range([15, 60]).clamp(true), + /** The radius of the circle denoting the expand button. */ + expandButtonRadius: 3, + }, + api_list: { + radius: 5, + width: 60, + maxLabelWidth: 200, + /** A scale for the node's height based on number of nodes inside */ + // Hack - set this as an any type to avoid issues in exporting a type + // from an external module. + height: (d3 as any).scaleLinear().domain([1, 200]).range([15, 60]).clamp(true), + /** The radius of the circle denoting the expand button. */ + expandButtonRadius: 3, + }, + /** Size of op nodes. */ + op: { + width: 30, + height: 12, + radius: 6, + labelOffset: -12, + maxLabelWidth: 40, + }, + /** Size of series nodes. */ + series: { + expanded: { + // For expanded series nodes, width and height will be + // computed to account for the subscene. + radius: 10, + labelOffset: 0, + }, + vertical: { + // When unexpanded, series whose underlying metagraphs contain + // one or more non-control edges will show as a vertical stack + // of ellipses. + width: 16, + height: 13, + labelOffset: -13, + }, + horizontal: { + // When unexpanded, series whose underlying metagraphs contain + // no non-control edges will show as a horizontal stack of + // ellipses. + width: 24, + height: 8, + radius: 10, + labelOffset: -10, + }, + }, + /** Size of bridge nodes. */ + bridge: { + // NOTE: bridge nodes will normally be invisible, but they must + // take up some space so that the layout step leaves room for + // their edges. + width: 20, + height: 20, + radius: 2, + labelOffset: 0, + }, + }, + shortcutSize: { + /** Size of shortcuts for op nodes */ + op: { width: 10, height: 4 }, + /** Size of shortcuts for meta nodes */ + meta: { width: 12, height: 4, radius: 1 }, + /** Size of shortcuts for series nodes */ + series: { width: 14, height: 4 }, + multi_collection: { width: 12, height: 4, radius: 1 }, + api_list: { width: 12, height: 4, radius: 1 }, + }, + annotations: { + /** Maximum possible width of the bounding box for in annotations */ + inboxWidth: 50, + /** Maximum possible width of the bounding box for out annotations */ + outboxWidth: 50, + /** X-space between the shape and each annotation-node. */ + xOffset: 10, + /** Y-space between each annotation-node. */ + yOffset: 3, + /** X-space between each annotation-node and its label. */ + labelOffset: 2, + /** Defines the max width for annotation label */ + maxLabelWidth: 40, + }, + constant: { size: { width: 4, height: 4 } }, + series: { + /** Maximum number of repeated item for unexpanded series node. */ + maxStackCount: 3, + /** + * Positioning offset ratio for collapsed stack + * of parallel series (series without edges between its members). + */ + parallelStackOffsetRatio: 0.2, + /** + * Positioning offset ratio for collapsed stack + * of tower series (series with edges between its members). + */ + towerStackOffsetRatio: 0.5, + }, + minimap: { + /** The maximum width/height the minimap can have. */ + size: 150, + }, +}; +/** + * The minimum width we confer upon the auxiliary nodes section if functions + * also appear. Without enforcing this minimum, metanodes in the function + * library section could jut into the auxiliary nodes section because the + * title "Auxiliary Nodes" is longer than the width of the auxiliary nodes + * section itself. + */ +export const MIN_AUX_WIDTH = 140; +/** + * Keep this number as the same as 'maxMetanodeLabelLength' in 'tf-graph-scene' + */ +export const MAX_TEXT_LENGTH = 50; +/** + * 6 pixels per character. + */ +export const CHARACTER_WIDTH = 6; +/** Calculate layout for a scene of a group node. */ +export function layoutScene(renderNodeInfo: render.RenderGroupNodeInfo): void { + // Update layout, size, and annotations of its children nodes and edges. + if (renderNodeInfo.node.isGroupNode) { + layoutChildren(renderNodeInfo); + } + // Update position of its children nodes and edges + if (renderNodeInfo.node.type === NodeType.META) { + layoutMetanode(renderNodeInfo, 10); + } else if (renderNodeInfo.node.type === NodeType.SERIES) { + layoutSeriesNode(renderNodeInfo); + } else if (renderNodeInfo.node.type === NodeType.MULTI_COLLECTION) { + layoutMetanode(renderNodeInfo, 10); + } else if (renderNodeInfo.node.type === NodeType.API_LIST) { + layoutMetanode(renderNodeInfo, 32); + } else { + } +} +/** + * Updates the total width of an unexpanded node which includes the size of its + * in and out annotations. + */ +function updateTotalWidthOfNode(renderInfo: render.RenderNodeInfo): void { + renderInfo.inboxWidth = renderInfo.inAnnotations.list.length > 0 ? PARAMS.annotations.inboxWidth : 0; + renderInfo.outboxWidth = renderInfo.outAnnotations.list.length > 0 ? PARAMS.annotations.outboxWidth : 0; + // Assign the width of the core box (the main shape of the node). + renderInfo.coreBox.width = renderInfo.width; + renderInfo.coreBox.height = renderInfo.height; + let labelLength = renderInfo.displayName.length; + // Compute the total width of the node. + if (renderInfo.node.type === NodeType.OP) { + renderInfo.width = PARAMS.nodeSize.op.maxLabelWidth; + } else { + renderInfo.width = Math.max( + renderInfo.coreBox.width + renderInfo.inboxWidth + renderInfo.outboxWidth, + Math.min(labelLength * CHARACTER_WIDTH, PARAMS.nodeSize.meta.maxLabelWidth), + ); + } +} +/** + * Update layout, size, and annotations of its children nodes and edges. + */ +function layoutChildren(renderNodeInfo: render.RenderGroupNodeInfo): void { + let children = renderNodeInfo.coreGraph + .nodes() + .map((n) => { + return renderNodeInfo.coreGraph.node(n); + }) + .concat( + renderNodeInfo.isolatedInExtract, + renderNodeInfo.isolatedOutExtract, + renderNodeInfo.libraryFunctionsExtract, + ); + _.each(children, (childNodeInfo) => { + // Set size of each child + switch (childNodeInfo.node.type) { + case NodeType.OP: + _.extend(childNodeInfo, PARAMS.nodeSize.op); + break; + case NodeType.BRIDGE: + _.extend(childNodeInfo, PARAMS.nodeSize.bridge); + break; + case NodeType.META: + case NodeType.MULTI_COLLECTION: + case NodeType.API_LIST: + if (!childNodeInfo.expanded) { + // Set fixed width and scalable height based on cardinality + _.extend(childNodeInfo, PARAMS.nodeSize.meta); + childNodeInfo.height = PARAMS.nodeSize.meta.height(childNodeInfo.node.cardinality); + childNodeInfo.width = Math.max( + childNodeInfo.width, + Math.min(childNodeInfo.displayName.length, MAX_TEXT_LENGTH) * CHARACTER_WIDTH, + ); + } else { + let childGroupNodeInfo = childNodeInfo; + layoutScene(childGroupNodeInfo); // Recursively layout its subscene. + } + break; + case NodeType.SERIES: + if (childNodeInfo.expanded) { + _.extend(childNodeInfo, PARAMS.nodeSize.series.expanded); + let childGroupNodeInfo = childNodeInfo; + layoutScene(childGroupNodeInfo); // Recursively layout its subscene. + } else { + let childGroupNodeInfo = childNodeInfo; + let seriesParams = childGroupNodeInfo.node.hasNonControlEdges + ? PARAMS.nodeSize.series.vertical + : PARAMS.nodeSize.series.horizontal; + _.extend(childNodeInfo, seriesParams); + } + break; + default: + throw Error(`Unrecognized node type: ${childNodeInfo.node.type}`); + } + // Compute total width of un-expanded nodes. Width of expanded nodes + // has already been computed. + if (!childNodeInfo.expanded) { + updateTotalWidthOfNode(childNodeInfo); + } + // Layout each child's annotations + layoutAnnotation(childNodeInfo); + }); +} +/** + * Calculate layout for a graph using dagre + * @param graph the graph to be laid out + * @param params layout parameters + * @return width and height of the core graph + */ +function dagreLayout(graph: graphlib.Graph, params): { height: number; width: number } { + _.extend(graph.graph(), { + nodesep: params.nodeSep, + ranksep: params.rankSep, + edgesep: params.edgeSep, + }); + let bridgeNodeNames: any[] = []; + let nonBridgeNodeNames: any[] = []; + // Split out nodes into bridge and non-bridge nodes, and calculate the total + // width we should use for bridge nodes. + _.each(graph.nodes(), (nodeName) => { + let nodeInfo = graph.node(nodeName); + if (nodeInfo.node.type === NodeType.BRIDGE) { + bridgeNodeNames.push(nodeName); + } else { + nonBridgeNodeNames.push(nodeName); + } + }); + // If there are no non-bridge nodes, then the graph has zero size. + if (!nonBridgeNodeNames.length) { + return { + width: 0, + height: 0, + }; + } + dagre.layout(graph); + // Calculate the true bounding box of the graph by iterating over nodes and + // edges rather than accepting dagre's word for it. In particular, we should + // ignore the extra-wide bridge nodes and bridge edges, and allow for + // annotation boxes and labels. + let minX = Infinity; + let minY = Infinity; + let maxX = -Infinity; + let maxY = -Infinity; + _.each(nonBridgeNodeNames, (nodeName) => { + let nodeInfo = graph.node(nodeName); + let w = 0.5 * nodeInfo.width; + let x1 = nodeInfo.x - w; + let x2 = nodeInfo.x + w; + minX = x1 < minX ? x1 : minX; + maxX = x2 > maxX ? x2 : maxX; + let h = 0.5 * nodeInfo.height; + let y1 = nodeInfo.y - h; + let y2 = nodeInfo.y + h; + minY = y1 < minY ? y1 : minY; + maxY = y2 > maxY ? y2 : maxY; + }); + + _.each(graph.nodes(), (nodeName) => { + let nodeInfo = graph.node(nodeName); + nodeInfo.x -= minX; + nodeInfo.y -= minY; + }); + return { + width: maxX - minX, + height: maxY - minY, + }; +} +/** Layout a metanode. Only called for an expanded node. */ +function layoutMetanode(renderNodeInfo: render.RenderGroupNodeInfo, rankSep: number): void { + // First, copy params specific to meta nodes onto this render info object. + let params = PARAMS.subscene.meta; + _.extend(renderNodeInfo, params); + // Invoke dagre.layout() on the core graph and record the bounding box + // dimensions. + _.extend(renderNodeInfo.coreBox, dagreLayout(renderNodeInfo.coreGraph, { ...PARAMS.graph.meta, rankSep })); + // Calculate the position of nodes in isolatedInExtract relative to the + // top-left corner of inExtractBox (the bounding box for all inExtract nodes) + // and calculate the size of the inExtractBox. + let maxInExtractWidth = renderNodeInfo.isolatedInExtract.length + ? _.maxBy(renderNodeInfo.isolatedInExtract, (renderNode) => renderNode.width)?.width + : null; + renderNodeInfo.inExtractBox.width = maxInExtractWidth != null ? maxInExtractWidth : 0; + renderNodeInfo.inExtractBox.height = _.reduce( + renderNodeInfo.isolatedInExtract, + (height, child, i) => { + let yOffset = i > 0 ? params.extractYOffset : 0; + // use width/height here to avoid overlaps between extracts + child.x = 0; + child.y = height + yOffset + child.height / 2; + return height + yOffset + child.height; + }, + 0, + ); + // Calculate the position of nodes in isolatedOutExtract relative to the + // top-left corner of outExtractBox (the bounding box for all outExtract + // nodes) and calculate the size of the outExtractBox. + let maxOutExtractWidth = renderNodeInfo.isolatedOutExtract.length + ? _.maxBy(renderNodeInfo.isolatedOutExtract, (renderNode) => renderNode.width)?.width + : null; + renderNodeInfo.outExtractBox.width = maxOutExtractWidth != null ? maxOutExtractWidth : 0; + renderNodeInfo.outExtractBox.height = _.reduce( + renderNodeInfo.isolatedOutExtract, + (height, child, i) => { + let yOffset = i > 0 ? params.extractYOffset : 0; + // use width/height here to avoid overlaps between extracts + child.x = 0; + child.y = height + yOffset + child.height / 2; + return height + yOffset + child.height; + }, + 0, + ); + // Calculate the position of nodes in libraryFunctionsExtract relative to the + // top-left corner of libraryFunctionsBox (the bounding box for all library + // function nodes) and calculate the size of the libraryFunctionsBox. + let maxLibraryFunctionsWidth = renderNodeInfo.libraryFunctionsExtract.length + ? _.maxBy(renderNodeInfo.libraryFunctionsExtract, (renderNode) => renderNode.width)?.width + : null; + renderNodeInfo.libraryFunctionsBox.width = maxLibraryFunctionsWidth != null ? maxLibraryFunctionsWidth : 0; + renderNodeInfo.libraryFunctionsBox.height = _.reduce( + renderNodeInfo.libraryFunctionsExtract, + (height, child, i) => { + let yOffset = i > 0 ? params.extractYOffset : 0; + // use width/height here to avoid overlaps between extracts + child.x = 0; + child.y = height + yOffset + child.height / 2; + return height + yOffset + child.height; + }, + 0, + ); + // Compute the total padding between the core graph, in-extract and + // out-extract boxes. + let numParts = 0; + if (renderNodeInfo.isolatedInExtract.length > 0) { + numParts++; + } + if (renderNodeInfo.isolatedOutExtract.length > 0) { + numParts++; + } + if (renderNodeInfo.libraryFunctionsExtract.length > 0) { + numParts++; + } + if (renderNodeInfo.coreGraph.nodeCount() > 0) { + numParts++; + } + let offset = PARAMS.subscene.meta.extractXOffset; + let padding = numParts <= 1 ? 0 : numParts * offset; + // Add the in-extract and out-extract width to the core box width. Do not let + // the auxiliary width be too small, lest it be smaller than the title. + renderNodeInfo.coreBox.width += padding + renderNodeInfo.libraryFunctionsBox.width + padding; + renderNodeInfo.coreBox.height = + params.labelHeight + + Math.max( + renderNodeInfo.inExtractBox.height, + renderNodeInfo.coreBox.height, + renderNodeInfo.libraryFunctionsBox.height, + renderNodeInfo.outExtractBox.height, + ); + // Determine the whole metanode's width (from left to right). + renderNodeInfo.width = + Math.max(renderNodeInfo.displayName.length * CHARACTER_WIDTH, renderNodeInfo.coreBox.width) + + params.paddingLeft + + params.paddingRight; + // Determine the whole metanode's height (from top to bottom). + renderNodeInfo.height = renderNodeInfo.paddingTop + renderNodeInfo.coreBox.height + renderNodeInfo.paddingBottom; +} +/** + * Calculate layout for series node's core graph. Only called for an expanded + * series. + */ +function layoutSeriesNode(node: render.RenderGroupNodeInfo): void { + let graph = node.coreGraph; + let params = PARAMS.subscene.series; + _.extend(node, params); + // Layout the core. + _.extend(node.coreBox, dagreLayout(node.coreGraph, PARAMS.graph.series)); + _.each(graph.nodes(), (nodeName) => { + graph.node(nodeName).excluded = false; + }); + // Series do not have in/outExtractBox so no need to include them here. + node.width = node.coreBox.width + params.paddingLeft + params.paddingRight; + node.height = node.coreBox.height + params.paddingTop + params.paddingBottom; +} +/** + * Calculate layout for annotations of a given node. + * This will modify positions of the given node and its annotations. + * + * @see tf.graph.render.Node and tf.graph.render.Annotation + * for description of each property of each render node. + * + */ +function layoutAnnotation(renderNodeInfo: render.RenderNodeInfo): void { + // If the render node is an expanded metanode, then its annotations will not + // be visible and we should skip the annotation calculations. + if (renderNodeInfo.expanded) { + return; + } + let inAnnotations = renderNodeInfo.inAnnotations.list; + let outAnnotations = renderNodeInfo.outAnnotations.list; + // Calculate size for in-annotations + _.each(inAnnotations, (a) => sizeAnnotation(a)); + // Calculate size for out-annotations + _.each(outAnnotations, (a) => sizeAnnotation(a)); + let params = PARAMS.annotations; + // Calculate annotation node position (a.dx, a.dy) + // and total height for in-annotations + // After this chunk of code: + // inboxHeight = sum of annotation heights+ (annotation.length - 1 * yOffset) + let inboxHeight = _.reduce( + inAnnotations, + (height, a, i) => { + let yOffset = i > 0 ? params.yOffset : 0; + a.dx = -((renderNodeInfo.coreBox.width + a.width) / 2) - params.xOffset; + a.dy = height + yOffset + a.height / 2; + return height + yOffset + a.height; + }, + 0, + ); + _.each(inAnnotations, (a) => { + a.dy -= inboxHeight / 2; + a.labelOffset = params.labelOffset; + }); + // Calculate annotation node position (a.dx, a.dy) + // and total height for out-annotations + // After this chunk of code: + // outboxHeight = sum of annotation heights + + // (annotation.length - 1 * yOffset) + let outboxHeight = _.reduce( + outAnnotations, + (height, a, i) => { + let yOffset = i > 0 ? params.yOffset : 0; + a.dx = (renderNodeInfo.coreBox.width + a.width) / 2 + params.xOffset; + a.dy = height + yOffset + a.height / 2; + return height + yOffset + a.height; + }, + 0, + ); + _.each(outAnnotations, (a) => { + // adjust by (half of ) the total height + // so dy is relative to the host node's center. + a.dy -= outboxHeight / 2; + a.labelOffset = params.labelOffset; + }); + // Creating scales for touch point between the in-annotation edges + // and their hosts. + let inTouchHeight = Math.min(renderNodeInfo.height / 2 - renderNodeInfo.radius, inboxHeight / 2); + + inTouchHeight = inTouchHeight < 0 ? 0 : inTouchHeight; + let inY = d3 + .scaleLinear() + .domain([0, inAnnotations.length - 1]) + .range([-inTouchHeight, inTouchHeight]); + // Calculate annotation edge position + _.each(inAnnotations, (a, i) => { + a.points = [ + // The annotation node end + { + dx: a.dx + a.width / 2, + dy: a.dy, + }, + // The host node end + { + dx: -renderNodeInfo.coreBox.width / 2, + // only use scale if there are more than one, + // otherwise center it vertically + dy: inAnnotations.length > 1 ? inY(i) : 0, + }, + ]; + }); + // Creating scales for touch point between the out-annotation edges + // and their hosts. + let outTouchHeight = Math.min(renderNodeInfo.height / 2 - renderNodeInfo.radius, outboxHeight / 2); + outTouchHeight = outTouchHeight < 0 ? 0 : outTouchHeight; + let outY = d3 + .scaleLinear() + .domain([0, outAnnotations.length - 1]) + .range([-outTouchHeight, outTouchHeight]); + _.each(outAnnotations, (a, i) => { + // Add point from the border of the annotation node + a.points = [ + // The host node end + { + dx: renderNodeInfo.coreBox.width / 2, + // only use scale if there are more than one, + // otherwise center it vertically + dy: outAnnotations.length > 1 ? outY(i) : 0, + }, + // The annotation node end + { + dx: a.dx - a.width / 2, + dy: a.dy, + }, + ]; + }); + renderNodeInfo.height = Math.max(renderNodeInfo.height, inboxHeight, outboxHeight); +} +/** + * Set size of an annotation node. + */ +function sizeAnnotation(a: render.Annotation): void { + switch (a.annotationType) { + case render.AnnotationType.CONSTANT: + _.extend(a, PARAMS.constant.size); + break; + case render.AnnotationType.SHORTCUT: + if (a.node.type === NodeType.OP) { + _.extend(a, PARAMS.shortcutSize.op); + } else if (a.node.type === NodeType.META) { + _.extend(a, PARAMS.shortcutSize.meta); + } else if (a.node.type === NodeType.SERIES) { + _.extend(a, PARAMS.shortcutSize.series); + } else if (a.node.type === NodeType.MULTI_COLLECTION) { + _.extend(a, PARAMS.shortcutSize.multi_collection); + } else if (a.node.type === NodeType.API_LIST) { + _.extend(a, PARAMS.shortcutSize.api_list); + } else { + throw Error(`Invalid node type: ${a.node.type}`); + } + break; + case render.AnnotationType.SUMMARY: + _.extend(a, PARAMS.constant.size); + break; + default: + break; + } +} +/** + * Determines the center position of the node's shape. The position depends + * on if the node has in and out-annotations. + */ +export function computeCXPositionOfNodeShape(renderInfo: render.RenderNodeInfo): number { + if (renderInfo.expanded) { + return renderInfo.x; + } + let dx = renderInfo.inAnnotations.list.length ? renderInfo.inboxWidth : 0; + return renderInfo.x - renderInfo.width / 2 + dx + renderInfo.coreBox.width / 2; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/loader.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/loader.ts new file mode 100644 index 000000000..fb11fff7d --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/loader.ts @@ -0,0 +1,82 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import { NPU_PREFIX, BENCH_PREFIX, type ProgressTracker } from './common'; +import * as tf_graph from './graph'; +import * as hierarchy from './hierarchy'; +import * as parser from './parser'; +import { GraphDef } from './proto'; +import * as tf_graph_util from './util'; + +export interface GraphAndHierarchy { + graph: tf_graph.MergedSlimGraph; + graphHierarchy: hierarchy.MergedHierarchy; +} +export function fetchAndConstructHierarchicalGraph( + tracker: ProgressTracker, + remotePath: string | null, + pbTxtFile: Blob | null, + hierarchyParams: hierarchy.HierarchyParams = hierarchy.DefaultHierarchyParams, +): Promise { + const dataTracker = tf_graph_util.getSubtaskTracker(tracker, 30, 'Data'); + const graphTracker = tf_graph_util.getSubtaskTracker(tracker, 20, 'Graph'); + const hierarchyTracker = tf_graph_util.getSubtaskTracker(tracker, 50, 'Namespace hierarchy'); + return parser + .fetchAndParseGraphData(remotePath as string, pbTxtFile, dataTracker) + .then( + (graph): any => { + if (graph.node.length !== 2) { + return tf_graph.build(graph, tf_graph.DefaultBuildParams, graphTracker); + } + const npuGraph: GraphDef = { node: [] }; + const benchGraph: GraphDef = { node: [] }; + if (graph.node[0].name.startsWith(NPU_PREFIX) && graph.node[1].name.startsWith(BENCH_PREFIX)) { + npuGraph.node.push(graph.node[0]); + benchGraph.node.push(graph.node[1]); + } + if (graph.node[0].name.startsWith(BENCH_PREFIX) && graph.node[1].name.startsWith(NPU_PREFIX)) { + npuGraph.node.push(graph.node[1]); + benchGraph.node.push(graph.node[0]); + } + return Promise.all([ + tf_graph.build(npuGraph, tf_graph.DefaultBuildParams, graphTracker), + tf_graph.build(benchGraph, tf_graph.DefaultBuildParams, graphTracker), + ]); + }, + () => { + throw new Error( + 'Malformed GraphDef. This can sometimes be caused by ' + + 'a bad network connection or invalid inputting files ', + ); + }, + ) + .then(async (graph) => { + if (Array.isArray(graph)) { + const mergedGraph: tf_graph.MergedSlimGraph = { npu: graph[0], bench: graph[1] }; + const npuHierarchy = await hierarchy.build(graph[0], hierarchyParams, hierarchyTracker); + const benchHierarchy = await hierarchy.build(graph[1], hierarchyParams, hierarchyTracker); + return { graph: mergedGraph, graphHierarchy: { npu: npuHierarchy, bench: benchHierarchy } }; + } + const graphHierarchy = await hierarchy.build(graph, hierarchyParams, hierarchyTracker); + return { graph: { npu: graph }, graphHierarchy: { npu: graphHierarchy } }; + }) + .catch((e) => { + // Generic error catch, for errors that happened outside + // asynchronous tasks. + const msg = `Graph visualization failed.\n\n${e}`; + tracker.reportError(msg, e); + // Don't swallow the error. + throw e; + }); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/minimap.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/minimap.ts new file mode 100644 index 000000000..1725dbd75 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/minimap.ts @@ -0,0 +1,314 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as d3 from 'd3'; + +const FRAC_VIEWPOINT_AREA: number = 0.8; +export class Minimap { + /** The minimap container. */ + private minimap: HTMLElement; + /** The canvas used for drawing the mini version of the svg. */ + private canvas: HTMLCanvasElement; + /** A buffer canvas used for temporary drawing to avoid flickering. */ + private canvasBuffer: HTMLCanvasElement; + private downloadCanvas: HTMLCanvasElement; + /** The minimap svg used for holding the viewpoint rectangle. */ + private minimapSvg: SVGSVGElement; + /** The rectangle showing the current viewpoint. */ + private viewpoint: SVGRectElement; + /** + * The scale factor for the minimap. The factor is determined automatically + * so that the minimap doesn't violate the maximum width/height specified + * in the constructor. The minimap maintains the same aspect ratio as the + * original svg. + */ + private scaleMinimap: number; + /** The main svg element. */ + private svg: SVGSVGElement; + /** The svg group used for panning and zooming the main svg. */ + private zoomG: SVGGElement; + /** The zoom behavior of the main svg. */ + private mainZoom: d3.ZoomBehavior; + /** The maximum width and height for the minimap. */ + private maxWandH: number; + /** The last translation vector used in the main svg. */ + private translate: [number, number]; + /** The last scaling factor used in the main svg. */ + private scaleMain: number; + /** The coordinates of the viewpoint rectangle. */ + private viewpointCoord: { + x: number; + y: number; + }; + /** The current size of the minimap */ + private minimapSize: { + width: number; + height: number; + }; + /** Padding (px) due to the main labels of the graph. */ + private labelPadding: number; + /** + * Constructs a new minimap. + * + * @param svg The main svg element. + * @param zoomG The svg group used for panning and zooming the main svg. + * @param mainZoom The main zoom behavior. + * @param minimap The minimap container. + * @param maxWandH The maximum width/height for the minimap. + * @param labelPadding Padding in pixels due to the main graph labels. + */ + constructor( + svg: SVGSVGElement, + zoomG: SVGGElement, + mainZoom: d3.ZoomBehavior, + minimap: HTMLElement, + maxWandH: number, + labelPadding: number, + ) { + this.svg = svg; + this.labelPadding = labelPadding; + this.zoomG = zoomG; + this.mainZoom = mainZoom; + this.maxWandH = maxWandH; + let $shadowRoot = d3.select(minimap.shadowRoot as unknown as Element); + // The minimap will have 2 main components: the canvas showing the content + // and an svg showing a rectangle of the currently zoomed/panned viewpoint. + let $minimapSvg = $shadowRoot.select('svg'); + // Make the viewpoint rectangle draggable. + let $viewpoint = $minimapSvg.select('rect'); + let dragmove = (d): void => { + this.viewpointCoord.x = (d3.event).x; + this.viewpointCoord.y = (d3.event).y; + this.updateViewpoint(); + }; + this.viewpointCoord = { x: 0, y: 0 }; + let drag = d3.drag().subject(Object).on('drag', dragmove); + $viewpoint.datum(this.viewpointCoord as any).call(drag); + // Make the minimap clickable. + $minimapSvg.on('click', (): void => { + if ((d3.event).defaultPrevented) { + // This click was part of a drag event, so suppress it. + return; + } + // Update the coordinates of the viewpoint. + let width = Number($viewpoint.attr('width')); + let height = Number($viewpoint.attr('height')); + let clickCoords = d3.mouse($minimapSvg.node() as any); + this.viewpointCoord.x = clickCoords[0] - width / 2; + this.viewpointCoord.y = clickCoords[1] - height / 2; + this.updateViewpoint(); + }); + this.viewpoint = $viewpoint.node(); + this.minimapSvg = $minimapSvg.node(); + this.minimap = minimap; + this.canvas = $shadowRoot.select('canvas.first').node(); + this.canvasBuffer = $shadowRoot.select('canvas.second').node(); + this.downloadCanvas = $shadowRoot.select('canvas.download').node(); + d3.select(this.downloadCanvas).style('display', 'none'); + this.update(); + } + + /** + * Takes a snapshot of the graph's image as a Blob. + */ + getImageBlob(): Promise { + return new Promise((resolve) => { + this.downloadCanvas.toBlob((blob) => { + resolve(blob as Blob); + }, 'image/png'); + }); + } + + /** + * Redraws the minimap. Should be called whenever the main svg + * was updated (e.g. when a node was expanded). + */ + update(): void { + let sceneSize: DOMRect | null = null; + try { + // Get the size of the entire scene. + sceneSize = this.zoomG.getBBox(); + if (sceneSize.width === 0) { + // There is no scene anymore. We have been detached from the dom. + return; + } + } catch (e) { + // Firefox produced NS_ERROR_FAILURE if we have been + // detached from the dom. + return; + } + let $svg = d3.select(this.svg); + // Read all the style rules in the document and embed them into the svg. + // The svg needs to be self contained, i.e. all the style rules need to be + // embedded so the canvas output matches the origin. + let stylesText = ''; + const anySvg = this.svg as any; + // MSEdge does not have `getRootNode`. In that case, manually get the root + // node. This is more brittle than the getRootNode as changing DOM structure + // will break this. + const rootNode = anySvg.getRootNode ? anySvg.getRootNode() : this.svg.parentNode; + const styleSheets = rootNode.styleSheets; + for (let k = 0; k < styleSheets.length; k++) { + try { + let cssRules = (styleSheets[k]).cssRules || (styleSheets[k]).rules; + if (cssRules == null) { + continue; + } + for (let i = 0; i < cssRules.length; i++) { + // Remove tf-* selectors from the styles. + stylesText += `${cssRules[i].cssText.replace(/ ?tf-[\w-]+ ?/g, '')}\n`; + } + } catch (e: any) { + if (e.name !== 'SecurityError') { + throw e; + } + } + } + // Temporarily add the css rules to the main svg. + let svgStyle = $svg.append('style'); + svgStyle.text(stylesText); + // Temporarily remove the zoom/pan transform from the main svg since we + // want the minimap to show a zoomed-out and centered view. + let $zoomG = d3.select(this.zoomG); + let zoomTransform = $zoomG.attr('transform'); + $zoomG.attr('transform', null); + // Account for SVG content shift. SVGGraphicsElement.getBBox().width returns + // width in pixel value of very tight bounding box of non-empty content. + // Since we want to measure the sceneSize from the origin to the right most + // edge of the right most node, we need to account for distance from the + // origin to the left edge of the bounding box. + sceneSize.height += sceneSize.y; + sceneSize.width += sceneSize.x; + // Since we add padding, account for that here. + sceneSize.height += this.labelPadding * 2; + sceneSize.width += this.labelPadding * 2; + // Temporarily assign an explicit width/height to the main svg, since + // it doesn't have one (uses flex-box), but we need it for the canvas + // to work. + $svg.attr('width', sceneSize.width).attr('height', sceneSize.height); + // Since the content inside the svg changed (e.g. a node was expanded), + // the aspect ratio have also changed. Thus, we need to update the scale + // factor of the minimap. The scale factor is determined such that both + // the width and height of the minimap are <= maximum specified w/h. + this.scaleMinimap = this.maxWandH / Math.max(sceneSize.width, sceneSize.height); + this.minimapSize = { + width: sceneSize.width * this.scaleMinimap, + height: sceneSize.height * this.scaleMinimap, + }; + // Update the size of the minimap's svg, the buffer canvas and the + // viewpoint rect. + d3.select(this.minimapSvg).attr(this.minimapSize); + d3.select(this.canvasBuffer).attr(this.minimapSize); + // Download canvas width and height are multiples of the style width and + // height in order to increase pixel density of the PNG for clarity. + const downloadCanvasSelection = d3.select(this.downloadCanvas); + downloadCanvasSelection.style('width', sceneSize.width); + downloadCanvasSelection.style('height', sceneSize.height); + downloadCanvasSelection.attr('width', 3 * sceneSize.width); + downloadCanvasSelection.attr('height', 3 * sceneSize.height); + if (this.translate != null && this.zoom != null) { + // Update the viewpoint rectangle shape since the aspect ratio of the + // map has changed. + requestAnimationFrame(() => this.zoom()); + } + let svgXml = new XMLSerializer().serializeToString(this.svg); + // Now that the svg is serialized for rendering, remove the temporarily + // assigned styles, explicit width and height and bring back the pan/zoom + // transform. + svgStyle.remove(); + $svg.attr('width', null).attr('height', null); + $zoomG.attr('transform', zoomTransform); + let image = new Image(); + image.onload = (): void => { + // Draw the svg content onto the buffer canvas. + let context = this.canvasBuffer.getContext('2d'); + context?.clearRect(0, 0, this.canvasBuffer.width, this.canvasBuffer.height); + context?.drawImage(image, 0, 0, this.minimapSize.width, this.minimapSize.height); + requestAnimationFrame(() => { + // Hide the old canvas and show the new buffer canvas. + d3.select(this.canvasBuffer).style('display', null); + d3.select(this.canvas).style('display', 'none'); + // Swap the two canvases. + [this.canvas, this.canvasBuffer] = [this.canvasBuffer, this.canvas]; + }); + let downloadContext = this.downloadCanvas.getContext('2d'); + downloadContext?.clearRect(0, 0, this.downloadCanvas.width, this.downloadCanvas.height); + downloadContext?.drawImage(image, 0, 0, this.downloadCanvas.width, this.downloadCanvas.height); + }; + image.onerror = (): void => { + let blob = new Blob([svgXml], { type: 'image/svg+xml;charset=utf-8' }); + image.src = (URL as any).createObjectURL(blob); + }; + image.src = `data:image/svg+xml;charset=utf-8,${encodeURIComponent(svgXml)}`; + } + /** + * Handles changes in zooming/panning. Should be called from the main svg + * to notify that a zoom/pan was performed and this minimap will update it's + * viewpoint rectangle. + * + * @param translate The translate vector, or none to use the last used one. + * @param scale The scaling factor, or none to use the last used one. + */ + zoom(transform?: d3.ZoomTransform): void { + if (this.scaleMinimap == null) { + // Scene is not ready yet. + return; + } + // Update the new translate and scale params, only if specified. + if (transform) { + this.translate = [transform.x, transform.y]; + this.scaleMain = transform.k; + } + // Update the location of the viewpoint rectangle. + let svgRect = this.svg.getBoundingClientRect(); + let $viewpoint = d3.select(this.viewpoint); + this.viewpointCoord.x = (-this.translate[0] * this.scaleMinimap) / this.scaleMain; + this.viewpointCoord.y = (-this.translate[1] * this.scaleMinimap) / this.scaleMain; + let viewpointWidth = (svgRect.width * this.scaleMinimap) / this.scaleMain; + let viewpointHeight = (svgRect.height * this.scaleMinimap) / this.scaleMain; + $viewpoint + .attr('x', this.viewpointCoord.x) + .attr('y', this.viewpointCoord.y) + .attr('width', viewpointWidth) + .attr('height', viewpointHeight); + // Show/hide the minimap depending on the viewpoint area as fraction of the + // whole minimap. + let mapWidth = this.minimapSize.width; + let mapHeight = this.minimapSize.height; + let x = this.viewpointCoord.x; + let y = this.viewpointCoord.y; + let w = Math.min(Math.max(0, x + viewpointWidth), mapWidth) - Math.min(Math.max(0, x), mapWidth); + let h = Math.min(Math.max(0, y + viewpointHeight), mapHeight) - Math.min(Math.max(0, y), mapHeight); + let fracIntersect = (w * h) / (mapWidth * mapHeight); + if (fracIntersect < FRAC_VIEWPOINT_AREA) { + this.minimap.classList.remove('hidden'); + } else { + this.minimap.classList.add('hidden'); + } + } + + /** + * Updates the position and the size of the viewpoint rectangle. + * It also notifies the main svg about the new panned position. + */ + private updateViewpoint(): void { + // Update the coordinates of the viewpoint rectangle. + d3.select(this.viewpoint).attr('x', this.viewpointCoord.x).attr('y', this.viewpointCoord.y); + // Update the translation vector of the main svg to reflect the + // new viewpoint. + let mainX = (-this.viewpointCoord.x * this.scaleMain) / this.scaleMinimap; + let mainY = (-this.viewpointCoord.y * this.scaleMain) / this.scaleMinimap; + d3.select(this.svg).call(this.mainZoom.transform, d3.zoomIdentity.translate(mainX, mainY).scale(this.scaleMain)); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts new file mode 100644 index 000000000..3a1d9f2e1 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts @@ -0,0 +1,1348 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as d3 from 'd3'; +import * as _ from 'lodash'; +import * as tf_graph_common from './common'; +import { Class, FontSizeInPx, selectChild, selectOrCreateChild } from './common'; +import * as contextmenu from './contextmenu'; +import { ContextMenuItem } from './contextmenu'; +import * as edge from './edge'; +import * as tf_graph from './graph'; +import { MetanodeImpl, Node, NodeType, OpNode, OpNodeImpl, SeriesNode } from './graph'; +import * as layout from './layout'; +import * as render from './render'; +import { RenderNodeInfo } from './render'; +import * as tf_graph_scene from './scene'; +import { positionEllipse, positionRect } from './scene'; +import { TfGraphScene } from './tf-graph-scene'; +import * as tf_graph_util from './util'; + +/** + * Select or Create a 'g.nodes' group to a given sceneGroup + * and builds a number of 'g.node' groups inside the group. + * + * Structure Pattern: + * + * + * + * + * ... + * + * + * ... + * + * + * + * + * node name + * + * + * + * + * ... + * + * + * + * @param sceneGroup selection of the container + * @param nodeData array of render node information to map + * @param sceneElement polymer element + * @return selection of the created nodeGroups + */ +let colorStorage: { [key: string]: string } = {}; +export function buildGroup(sceneGroup, nodeData: render.RenderNodeInfo[], sceneElement): void { + let container = tf_graph_common.selectOrCreateChild(sceneGroup, 'g', Class.Node.CONTAINER); + // Select all children and join with data. + // (Note that all children of g.nodes are g.node) + let nodeGroups = (container as any) + .selectAll(function () { + return this.childNodes; + }) + .data(nodeData, (d) => { + // make sure that we don't have to swap shape type + return `${d.node.name}:${d.node.type}`; + }); + // ENTER + nodeGroups + .enter() + .append('g') + .attr('data-name', (d) => { + return d.node.name; + }) + .each(function (d) { + let nodeGroup = d3.select(this); + // index node group for quick stylizing + sceneElement.addNodeGroup(d.node.name, nodeGroup); + }) + .merge(nodeGroups) + // ENTER + UPDATE + .attr('class', (d: render.RenderNodeInfo) => { + return `${Class.Node.GROUP} ${nodeClass(d)}`; + }) + .each(function (d: render.RenderNodeInfo) { + let nodeGroup = d3.select(this); + // Add g.in-annotations (always add -- to keep layer order + // consistent.) + let inAnnotationBox = tf_graph_common.selectOrCreateChild(nodeGroup, 'g', Class.Annotation.INBOX); + buildGroupForAnnotation(inAnnotationBox, d.inAnnotations, d, sceneElement); + // Add g.out-annotations (always add -- to keep layer order + // consistent.) + let outAnnotationBox = tf_graph_common.selectOrCreateChild(nodeGroup, 'g', Class.Annotation.OUTBOX); + buildGroupForAnnotation(outAnnotationBox, d.outAnnotations, d, sceneElement); + // Build .shape first (background of the node). + let shape = buildShape(nodeGroup, d, Class.Node.SHAPE); + let shape1 = buildShape(nodeGroup, d, Class.Node.OUTER); + if (d.node.isGroupNode) { + addButton(shape, d, sceneElement); + } + if (d.node.isGroupNode) { + addButton(shape1, d, sceneElement); + } + addInteraction(shape, d, sceneElement); + addInteraction(shape1, d, sceneElement); + // Build subscene on the top. + subsceneBuild(nodeGroup, d, sceneElement); + // Build label last. Should be on top of everything else. + let label = labelBuild(nodeGroup, d, sceneElement); + // Do not add interaction to metanode labels as they live inside the + // metanode shape which already has the same interactions. + addInteraction(label, d, sceneElement, d.node.type === NodeType.META); + stylize(nodeGroup, d, sceneElement); + position(nodeGroup, d); + }); + // EXIT + nodeGroups + .exit() + .each(function (d) { + // remove all indices on remove + sceneElement.removeNodeGroup(d.node.name); + let nodeGroup = d3.select(this); + if (d.inAnnotations.list.length > 0) { + nodeGroup + .select(`.${Class.Annotation.OUTBOX}`) + .selectAll(`.${Class.Annotation.GROUP}`) + .each((a) => { + sceneElement.removeAnnotationGroup(a, d); + }); + } + if (d.outAnnotations.list.length > 0) { + nodeGroup + .select('.' + Class.Annotation.OUTBOX) + .selectAll('.' + Class.Annotation.GROUP) + .each((a) => { + sceneElement.removeAnnotationGroup(a, d); + }); + } + }) + .remove(); +} +/** + * Update or remove the subscene of a render group node depending on whether it + * is a expanded. If the node is not a group node, this method has no effect. + * + * @param nodeGroup selection of the container + * @param renderNodeInfo the render information for the node. + * @param sceneElement polymer element. + * @return Selection of the subscene group, or null if node group does not have + * a subscene. Op nodes, bridge nodes and unexpanded group nodes will + * not have a subscene. + */ +function subsceneBuild(nodeGroup, renderNodeInfo: render.RenderGroupNodeInfo, sceneElement: TfGraphScene): void { + if (renderNodeInfo.node.isGroupNode) { + if (renderNodeInfo.expanded) { + // Recursively build the subscene. + buildGroupForScene(nodeGroup, renderNodeInfo, sceneElement, Class.Subscene.GROUP); + return; + } + // Clean out existing subscene if the node is not expanded. + tf_graph_scene.selectChild(nodeGroup, 'g', Class.Subscene.GROUP).remove(); + } +} +/** + * Translate the subscene of the given node group + */ +function subscenePosition(nodeGroup, d: render.RenderNodeInfo): void { + // Translate the subscene to the middle of the parent node in vertical direction. + let x0 = d.x - d.coreBox.width / 2; + let y0 = d.y - d.height / 2 + d.paddingTop; + let subscene = tf_graph_scene.selectChild(nodeGroup, 'g', Class.Subscene.GROUP); + tf_graph_scene.translate(subscene, x0, y0); +} +/** + * Add an expand/collapse button to a group node + * + * @param selection The group node selection. + * @param d Info about the node being rendered. + * @param sceneElement polymer element. + */ +function addButton(selection, d: render.RenderNodeInfo, sceneElement): void { + let group = tf_graph_common.selectOrCreateChild(selection, 'g', Class.Node.BUTTON_CONTAINER); + tf_graph_common.selectOrCreateChild(group, 'circle', Class.Node.BUTTON_CIRCLE); + tf_graph_common.selectOrCreateChild(group, 'path', Class.Node.EXPAND_BUTTON).attr('d', 'M0,-2.2 V2.2 M-2.2,0 H2.2'); + tf_graph_common.selectOrCreateChild(group, 'path', Class.Node.COLLAPSE_BUTTON).attr('d', 'M-2.2,0 H2.2'); + (group as any).on('click', (dGroup: any) => { + // Stop this event's propagation so that it isn't also considered a + // node-select. + (d3.event).stopPropagation(); + sceneElement.fire('node-toggle-expand', { name: dGroup.node.name }); + }); + tf_graph_scene.positionButton(group, d); +} +/** + * Fire node-* events when the selection is interacted. + * + * @param disableInteraction When true, have the provided selection + * ignore all pointer events. Used for text labels inside of metanodes, which + * don't need interaction as their surrounding shape has interaction, and if + * given interaction would cause conflicts with the expand/collapse button. + */ +function addInteraction( + selection, + d: render.RenderNodeInfo, + sceneElement: TfGraphScene, + disableInteraction?: boolean, +): void { + if (disableInteraction) { + selection.attr('pointer-events', 'none'); + return; + } + let contextMenuFunction = contextmenu.getMenu(sceneElement, d); + let time = 0; + let timeOut; + let mouseMoved = false; + let startX; + let startY; + const movementThreshold = 5; + selection + .on('dblclick', (dDbClick) => { + clearTimeout(timeOut); + sceneElement.fire('node-toggle-expand', { name: dDbClick.node.name }); + }) + .on('mouseover', (dMouseover) => { + // don't send mouseover over expanded group, + // otherwise it is causing too much glitches + if (sceneElement.isNodeExpanded(dMouseover)) { + return; + } + sceneElement.fire('node-highlight', { name: dMouseover.node.name }); + }) + .on('mouseout', (dMouseOut) => { + // don't send mouseover over expanded group, + // otherwise it is causing too much glitches + if (sceneElement.isNodeExpanded(dMouseOut)) { + return; + } + sceneElement.fire('node-unhighlight', { name: dMouseOut.node.name }); + }) + .on('mousedown', () => { + startX = d3.event.clientX; + startY = d3.event.clientY; + mouseMoved = false; // 重置标志变量 + }) + + // 监听鼠标抬起事件，检查是否超过浮动阈值 + .on('mouseup', () => { + const deltaX = Math.abs(d3.event.clientX - startX); + const deltaY = Math.abs(d3.event.clientY - startY); + if (deltaX > movementThreshold || deltaY > movementThreshold) { + mouseMoved = true; + } + }) + + .on('click', (dClick) => { + clearTimeout(timeOut); // 清除第一个单击事件 + if (mouseMoved) { + mouseMoved = false; // 重置标志变量 + return; + } + timeOut = setTimeout(() => { + sceneElement.fire('node-select', { name: dClick.node.name }); + }, time); + }) + + .on('contextmenu', (dCtx, i) => { + sceneElement.fire('node-select', { name: dCtx.node.name }); + contextMenuFunction.call(dCtx, i); + }); +} + +/** + * Append svg text for label and assign data. + * @param nodeGroup + * @param renderNodeInfo The render node information for the label. + * @param sceneElement polymer element. + */ +function labelBuild(nodeGroup, renderNodeInfo: render.RenderNodeInfo, sceneElement): d3.Selection { + let text = renderNodeInfo.displayName; + // Truncate long labels for unexpanded Metanodes. + let useFontScale = + renderNodeInfo.node.type === (NodeType.META || NodeType.MULTI_COLLECTION || NodeType.API_LIST) && + !renderNodeInfo.expanded; + let label = tf_graph_common.selectOrCreateChild(nodeGroup, 'text', Class.Node.LABEL); + // Make sure the label is visually on top among its siblings. + let labelNode = label.node(); + labelNode.parentNode?.appendChild(labelNode); + label.attr('dy', '.35em').attr('text-anchor', 'middle'); + + // In tf-graph-scene styles, fontSizes are defined to vary from 6px to 9px. Since we + // do not want to invoke computedStyles or hardcode the fontSize that would be + // duplicated in styles, we are rounding it to 8px which does not cause any visible + // jank. + let fontSize = 8; + + switch (renderNodeInfo.node.type) { + case NodeType.META: + case NodeType.MULTI_COLLECTION: + case NodeType.API_LIST: + fontSize = renderNodeInfo.expanded ? FontSizeInPx.Node.EXPANDED_LABEL : FontSizeInPx.Node.SERIES_LABEL; + break; + case NodeType.OP: + fontSize = FontSizeInPx.Node.OP_LABEL; + break; + default: + break; + } + + if (useFontScale) { + if (text.length > sceneElement.maxMetanodeLabelLength) { + text = `${text.substr(0, sceneElement.maxMetanodeLabelLength - 2)}…`; + } + let scale = getLabelFontScale(sceneElement); + label.attr('font-size', `${scale(text.length)}px`); + fontSize = scale(text.length); + } + let txtElement = >label.text(text); + enforceLabelWidth(txtElement, renderNodeInfo.node.type, fontSize, renderNodeInfo); + return label; +} + +/** + * This function shortens text which would exceed the maximum pixel width of + * a label. + * + * @param txtElementSelection The text element containing the label's text as d3 + * selection. + * @param nodeType The type of the node the label belongs to. If the node is + * an annotation, the value is -1. Label widths are defined in + * layout.PARAMS.nodeSize.{meta|op|...}.maxLabelWidth for nodes and + * layout.PARAMS.annotations.labelWidth for annotations. + * @param renderNodeInfo The render information about the node, required to + * determine whether META nodes are collapsed or expanded. + */ +export function enforceLabelWidth( + txtElementSelection: d3.Selection, + nodeType: NodeType | number, + fontSize: number, + renderNodeInfo?: render.RenderNodeInfo, +): void { + // Get text element itself and its on-screen width. + let txtNode = txtElementSelection.node(); + let labelContent = txtNode.textContent; + + // Get maximum length from settings. + let maxLength: number | null = null; + switch (nodeType) { + case NodeType.META: + case NodeType.MULTI_COLLECTION: + case NodeType.API_LIST: + if (renderNodeInfo && !renderNodeInfo.expanded) { + // Only trim text if + // node expanded. + maxLength = layout.PARAMS.nodeSize.meta.maxLabelWidth; + } + break; + case NodeType.OP: + maxLength = layout.PARAMS.nodeSize.op.maxLabelWidth; + break; + case -1: + maxLength = layout.PARAMS.annotations.maxLabelWidth; + break; + default: + break; + } + if (maxLength === null) return null; + + txtNode.textContent = tf_graph_util.maybeTruncateString(txtNode.textContent ?? '', fontSize, maxLength); + // Add tooltip with full name and return. + txtElementSelection.append('title').text(labelContent); +} +/** + * d3 scale used for sizing font of labels, used by labelBuild, + * initialized once by getLabelFontScale. + */ +let fontScale: any = null; +function getLabelFontScale(sceneElement): any { + if (!fontScale) { + fontScale = d3 + .scaleLinear() + .domain([sceneElement.maxMetanodeLabelLengthLargeFont, sceneElement.maxMetanodeLabelLength]) + .range([sceneElement.maxMetanodeLabelLengthFontSize, sceneElement.minMetanodeLabelLengthFontSize]) + .clamp(true); + } + return fontScale; +} +/** + * Set label position of a given node group + */ +function labelPosition(nodeGroup, cx: number, cy: number, yOffset: number): void { + tf_graph_scene + .selectChild(nodeGroup, 'text', Class.Node.LABEL) + .transition() + .attr('x', cx) + .attr('y', cy + yOffset); +} +/** + * Select or append/insert shape for a node and assign renderNode + * as the shape's data. + * + * @param nodeGroup + * @param d Render node information. + * @param nodeClass class for the element. + * @return Selection of the shape. + */ +export function buildShape(nodeGroup, d, nodeClassName: string): d3.Selection { + // Create a group to house the underlying visual elements. + let shapeGroup = tf_graph_common.selectOrCreateChild(nodeGroup, 'g', nodeClassName); + // TODO: DOM structure should be templated in HTML somewhere, not JS. + switch (d.node.type) { + case NodeType.OP: { + const opNode = d.node as OpNode; + tf_graph_common.selectOrCreateChild(shapeGroup, 'ellipse', Class.Node.COLOR_TARGET); + break; + } + case NodeType.SERIES: { + // Choose the correct stamp to use to represent this series. + let stampType = 'annotation'; + let groupNodeInfo = d; + if (groupNodeInfo.coreGraph) { + stampType = groupNodeInfo.node.hasNonControlEdges ? 'vertical' : 'horizontal'; + } + let classList = [Class.Node.COLOR_TARGET]; + if (groupNodeInfo.isFadedOut) { + classList.push('faded-ellipse'); + } + tf_graph_common + .selectOrCreateChild(shapeGroup, 'use', classList) + .attr('xlink:href', `#op-series-${stampType}-stamp`); + tf_graph_common + .selectOrCreateChild(shapeGroup, 'rect', Class.Node.COLOR_TARGET) + .attr('rx', d.radius) + .attr('ry', d.radius); + break; + } + case NodeType.META: + case NodeType.MULTI_COLLECTION: + case NodeType.API_LIST: + tf_graph_common + .selectOrCreateChild(shapeGroup, 'rect', Class.Node.COLOR_TARGET) + .attr('rx', d.radius) + .attr('ry', d.radius); + break; + default: + throw Error(`Unrecognized node type: ${d.node.type}`); + } + return shapeGroup; +} +export function nodeClass(d: render.RenderNodeInfo): string { + switch (d.node.type) { + case NodeType.OP: + return Class.OPNODE; + case NodeType.META: + return Class.METANODE; + case NodeType.SERIES: + return Class.SERIESNODE; + case NodeType.BRIDGE: + return Class.BRIDGENODE; + case NodeType.ELLIPSIS: + return Class.ELLIPSISNODE; + case NodeType.MULTI_COLLECTION: + return Class.MULTI_COLLECTION; + case NodeType.API_LIST: + return Class.API_LIST; + default: + return ''; + } +} +/** Modify node and its subscene and its label's positional attributes */ +function position(nodeGroup, d: render.RenderNodeInfo): void { + let shapeGroup = tf_graph_scene.selectChild(nodeGroup, 'g', Class.Node.SHAPE); + let shapeGroupHeader = tf_graph_scene.selectChild(nodeGroup, 'g', Class.Node.OUTER); + let cx = layout.computeCXPositionOfNodeShape(d); + switch (d.node.type) { + case NodeType.OP: { + // position shape + let shape = tf_graph_scene.selectChild(shapeGroup, 'ellipse'); + tf_graph_scene.positionEllipse(shape, cx, d.y, d.coreBox.width, d.coreBox.height); + labelPosition(nodeGroup, cx, d.y, d.labelOffset); + break; + } + case NodeType.META: { + // position shape + let shapes = shapeGroup.selectAll('rect'); + let INSIDE_RECT_OFFSET = 0; + // y值为定位值 取值为（15(色块高度)/2 (中心点y值) + 0.6 (向下偏移值, 不偏移会覆盖边及其颜色)）得出 + // 偏移值为8.1 + let OFFSET_VALUE = 8.1; + if (d.expanded) { + tf_graph_scene.positionRect(shapes, d.x, d.y, d.width, d.height); + INSIDE_RECT_OFFSET = d.y - d.height / 2 + OFFSET_VALUE; + subscenePosition(nodeGroup, d); + // Put the label on top. + labelPosition(nodeGroup, cx, d.y, -d.height / 2 + d.labelHeight / 2); + } else { + tf_graph_scene.positionRect(shapes, cx, d.y, d.coreBox.width, d.coreBox.height); + // Place the label in the middle. + labelPosition(nodeGroup, cx, d.y, 0); + } + let shapesHeader = shapeGroupHeader.selectAll('rect'); + if (d.expanded) { + tf_graph_scene.positionRect(shapesHeader, d.x, INSIDE_RECT_OFFSET, d.width - 1, 15); + subscenePosition(nodeGroup, d); + // Put the label on top. + labelPosition(nodeGroup, cx, d.y, -d.height / 2 + d.labelHeight / 2); + } else { + tf_graph_scene.positionRect(shapesHeader, cx, d.y, d.coreBox.width, d.coreBox.height); + // Place the label in the middle. + labelPosition(nodeGroup, cx, d.y, 0); + } + break; + } + case NodeType.SERIES: { + let shape = tf_graph_scene.selectChild(shapeGroup, 'use'); + if (d.expanded) { + tf_graph_scene.positionRect(shape, d.x, d.y, d.width, d.height); + subscenePosition(nodeGroup, d); + // put label on top + labelPosition(nodeGroup, cx, d.y, -d.height / 2 + d.labelHeight / 2); + } else { + tf_graph_scene.positionRect(shape, cx, d.y, d.coreBox.width, d.coreBox.height); + labelPosition(nodeGroup, cx, d.y, d.labelOffset); + } + break; + } + case NodeType.BRIDGE: { + // position shape + // NOTE: In reality, these will not be visible, but it helps to put them + // in the correct position for debugging purposes. + let shape = tf_graph_scene.selectChild(shapeGroup, 'rect'); + tf_graph_scene.positionRect(shape, d.x, d.y, d.width, d.height); + break; + } + case NodeType.MULTI_COLLECTION: + case NodeType.API_LIST: { + // position shape + let shapes = shapeGroup.selectAll('rect'); + if (d.expanded) { + tf_graph_scene.positionRect(shapes, d.x, d.y, d.width, d.height); + subscenePosition(nodeGroup, d); + // Put the label on top. + labelPosition(nodeGroup, cx, d.y, -d.height / 2 + d.labelHeight / 2); + } else { + tf_graph_scene.positionRect(shapes, cx, d.y, d.coreBox.width, d.coreBox.height); + // Place the label in the middle. + labelPosition(nodeGroup, cx, d.y, 0); + } + break; + } + default: { + throw Error(`Unrecognized node type: ${d.node.type}`); + } + } +} + +export function removeGradientDefinitions(svgRoot: SVGElement): void { + d3.select(svgRoot).select('defs#_graph-gradients').remove(); +} + +export function getColorByPrecisionIndex(precisionStr: string): string { + if (['medium', 'high', 'critical'].includes(precisionStr)) { + switch (precisionStr) { + case 'medium': + return '#B6C7FC'; + case 'high': + return '#7E96F0'; + case 'critical': + return '#4668B8'; + default: + break; + } + } + const precision = Number(precisionStr); + if (isNaN(precision)) { + return 'white'; + } + if (Object.entries(colorStorage).length !== 0) { + for (const [color, details] of Object.entries(colorStorage)) { + const detailsArray: any[] = [details]; + const [start, end] = detailsArray[0].value; + //进入md5模式 + const isPrecisionInRange = precision >= start && precision < end; + const isPrecisionAtEnd = precision === end && end === 1; + if (start === end) { + if (precision === start) { + return color; + } + } + //其他区间模式, 最后一个区间的右侧一定为1，所以特化precision == 1的情况 + else if (isPrecisionInRange || isPrecisionAtEnd) { + return color; + } + } + return 'white'; + } else { + const colorMap = [ + { precision: 0.2, color: '#ff704d' }, + { precision: 0.4, color: '#FFC62E' }, + { precision: 0.6, color: '#FFDC7F' }, + { precision: 0.8, color: '#FFEDBE' }, + { precision: 1, color: '#FFFCF3' }, + ]; + for (const range of colorMap) { + if (precision <= range.precision) { + return range.color; + } + } + return 'white'; + } +} +/** + * Returns the fill color for the node given its state and the 'color by' + * option. + * Takes in optional svgRoot, when passed, that populates SVG definitions + * for the fill inside the svgRoot when necessary. + */ +export function getFillForNode(renderInfo: render.RenderNodeInfo): string { + if (renderInfo.node instanceof OpNodeImpl || renderInfo.node instanceof MetanodeImpl) { + const precisionItem = renderInfo.node.attr.find((item) => item.key === tf_graph.PRECISION_INDEX); + const overflowLevelItem = renderInfo.node.attr.find((item) => item.key === tf_graph.OVERFLOW_LEVEL); + const matchedNodeLink = renderInfo.node.matchedNodeLink; // 标杆侧没有任何颜色 + // 以前缀来判断是单图节点还是对比图节点 + if ( + renderInfo.node.name.startsWith(tf_graph_common.BENCH_PREFIX) || + renderInfo.node.name.startsWith(tf_graph_common.NPU_PREFIX) + ) { + if (_.isEmpty(matchedNodeLink)) { + return '#C7C7C7'; + } + } + if (overflowLevelItem) { + switch (overflowLevelItem.value) { + case 'medium': + return '#B6C7FC'; + case 'high': + return '#7E96F0'; + case 'critical': + return '#4668B8'; + default: + console.error('Unknown overflow level.'); + // 处理未知情况 + return 'transparent'; + } + } else if (precisionItem) { + return getColorByPrecisionIndex(precisionItem.value); + } else { + return 'transparent'; + } + } else { + // Other nodes are white. + return 'transparent'; + } +} +/** + * Modify node style by toggling class and assign attributes (only for things + * that can't be done in css). + */ +export function stylize( + nodeGroup, + renderInfo: render.RenderNodeInfo, + sceneElement: TfGraphScene, + nodeClassName?, +): void { + nodeClassName = nodeClassName || Class.Node.SHAPE || Class.Node.OUTER; + const isHighlighted = sceneElement.isNodeHighlighted(renderInfo.node.name); + const isSelected = sceneElement.isNodeSelected(renderInfo.node.name); + const isExtract = renderInfo.isInExtract || renderInfo.isOutExtract || renderInfo.isLibraryFunction; + const isExpanded = renderInfo.expanded && nodeClassName !== Class.Annotation.NODE; + const isFadedOut = renderInfo.isFadedOut; + const isLinked = sceneElement.isNodeLinked(renderInfo.node.name); + nodeGroup.classed('highlighted', isHighlighted); + nodeGroup.classed('selected', isSelected); + nodeGroup.classed('extract', isExtract); + nodeGroup.classed('expanded', isExpanded); + nodeGroup.classed('faded', isFadedOut); + nodeGroup.classed('linked', isLinked); + // Main node always exists here and it will be reached before subscene, + // so d3 selection is fine here.OLOR_TARGET) + const node = nodeGroup.select(`.${nodeClassName} .${Class.Node.COLOR_TARGET}`); + const outerNode = nodeGroup.select(`.${Class.Node.OUTER} .${Class.Node.COLOR_TARGET}`); + const text = nodeGroup.select(`.${nodeClassName}`); + const fillColor = getFillForNode(renderInfo); + if ( + renderInfo.node.type === tf_graph.NodeType.META || + renderInfo.node.type === tf_graph.NodeType.MULTI_COLLECTION || + renderInfo.node.type === tf_graph.NodeType.API_LIST + ) { + node.style('fill', 'white'); + outerNode.style('fill', fillColor); + } else { + node.style('fill', fillColor); + } + // Choose outline to be darker version of node color if the node is a single + // color and is not selected. + node.style('stroke', isSelected ? null : getStrokeForFill(fillColor === 'transparent' ? 'white' : fillColor)); +} +/** + * Given a node's fill color/gradient, determine the stroke for the node. + */ +export function getStrokeForFill(fill: string): string { + // If node is colored by a gradient, then use a dark gray outline. + if (fill.substring(0, 3) === 'url') { + return render.MetanodeColors.GRADIENT_OUTLINE; + } else if (fill.startsWith('rgba')) { + return 'rgb(167, 167, 167)'; + } else { + return d3.rgb(fill).darker().toString(); + } +} +/** + * Finds selected node and highlights all nodes which are providing direct + * or indirect input to the node and all edges connecting these nodes + * together and to the selected node. + */ +export function updateInputTrace( + svgRoot: SVGElement, + renderGraphInfo: render.RenderGraphInfo, + selectedNodeName: string, + traceInputs: boolean, +): void { + // Reset all styling. + const svg = d3.select(svgRoot); + svg.selectAll('.input-highlight').classed('input-highlight', false); + svg.selectAll('.non-input').classed('non-input', false); + svg.selectAll('.input-parent').classed('input-parent', false); + svg.selectAll('.input-child').classed('input-child', false); + svg.selectAll('.input-edge-highlight').classed('input-edge-highlight', false); + svg.selectAll('.non-input-edge-highlight').classed('non-input-edge-highlight', false); + svg.selectAll('.input-highlight-selected').classed('input-highlight-selected', false); + // Extract currently selected node. Return if input tracing disabled or no + // node is selected. + if (!renderGraphInfo || !traceInputs || !selectedNodeName) { + return; + } + let opNodes = _getAllContainedOpNodes(selectedNodeName, renderGraphInfo); + let allTracedNodes = {}; + _.each(opNodes, function (nodeInstance) { + allTracedNodes = traceAllInputsOfOpNode(svgRoot, renderGraphInfo, nodeInstance, allTracedNodes); + }); + // Highlight all parent nodes of each OpNode as input parent to allow + // specific highlighting. + let highlightedNodes = Object.keys(allTracedNodes); + let visibleNodes = _findVisibleParentsFromOpNodes(renderGraphInfo, highlightedNodes); + _markParentsOfNodes(svgRoot, visibleNodes); + // Attach class to all non-input nodes and edges for styling. + svg + .selectAll('g.node:not(.selected):not(.input-highlight)' + ':not(.input-parent):not(.input-children)') + .classed('non-input', true) + .each(function (d: RenderNodeInfo) { + // Mark all nodes with the specified name as non-inputs. This + // results in Annotation nodes which are attached to inputs to be + // tagged as well. + let nodeName = d.node.name; + svg.selectAll(`[data-name="${nodeName}"]`).classed('non-input', true); + }); + svg.selectAll('g.edge:not(.input-edge-highlight)').classed('non-input-edge-highlight', true); +} +/** + * Recursively find all op nodes contained by the node identified by the + * provided name. + * @param nodeName The meta or op node of which the OpNode instances are + * required. + * @param renderGraphInfo The rendered graph information object. + * @returns {Array} An array of OpNodeImpl instances. + */ +function _getAllContainedOpNodes(nodeName: string, renderGraphInfo: render.RenderGraphInfo): ReadonlyArray { + let opNodes: OpNodeImpl[] = []; + // Get current node. + let node = renderGraphInfo.getNodeByName(nodeName) as tf_graph.GroupNode | tf_graph.OpNode; + // If node is already OpNode then return the node plus its input embeddings. + if (node instanceof tf_graph.OpNodeImpl) { + return [node].concat(node.inEmbeddings); + } + // Otherwise, make recursive call for each node contained by the GroupNode. + let childNodeNames = (node as tf_graph.GroupNode).metagraph.nodes(); + _.each(childNodeNames, function (childNodeName) { + opNodes = opNodes.concat(_getAllContainedOpNodes(childNodeName, renderGraphInfo)); + }); + return opNodes; +} +/** + * When resolving inputs of a node the visible parent node of each input + * node (i.e. the first parent which is rendered to the screen) needs to be + * found, and since such a node may contain several input OpNodes a map + * of the visible parent to all the input OpNodes it contains is provided by + * opNodes. + */ +interface VisibleParent { + visibleParent: Node; + opNodes: OpNode[]; +} +function traceAllInputsOfOpNode( + svgRoot: SVGElement, + renderGraphInfo: render.RenderGraphInfo, + startNode: OpNode, + allTracedNodes: Record, +): any { + // To prevent infinite loops due to cyclical relationships and improving + // performance by tracing OpNode which is input to 2+ nodes only once. + if (allTracedNodes[startNode.name]) { + return allTracedNodes; + } else { + allTracedNodes[startNode.name] = true; + } + // Extract the inputs. + let inputs = startNode.inputs; + // Get visible parent. + let currentVisibleParent = getVisibleParent(renderGraphInfo, startNode); + // Mark as input node. + d3.select(svgRoot).select(`.node[data-name="${currentVisibleParent.name}"]`).classed('input-highlight', true); + // Find the visible parent of each input. + let visibleInputs = {}; + _.each(inputs, function (nodeInstance) { + let resolvedNode = renderGraphInfo.getNodeByName(nodeInstance.name); + if (resolvedNode === undefined) { + // Node could not be found in rendered Hierarchy, which happens when + // tracing inputs of a SummaryNode. + return; + } + // Ensure node is resolved to OpNode if name collision with Metanode exists. + if (resolvedNode instanceof MetanodeImpl) { + let resolvedNodeName = tf_graph.getStrictName(resolvedNode.name); + resolvedNode = renderGraphInfo.getNodeByName(resolvedNodeName) as OpNode; + } + let visibleParent = getVisibleParent(renderGraphInfo, resolvedNode); + // Append OpNode to visible parent entry. + let visibleInputsEntry = visibleInputs[visibleParent.name]; + if (visibleInputsEntry) { + visibleInputsEntry.opNodes.push(resolvedNode); + } else { + // Create new entry. + visibleInputs[visibleParent.name] = { + visibleParent: visibleParent, + opNodes: [resolvedNode], + } as VisibleParent; + } + }); + // Find all parents of the start node. + let startNodeParents = {}; + let indexedStartNodeParents = [currentVisibleParent]; + startNodeParents[currentVisibleParent.name] = { + traced: false, + index: 0, + connectionEndpoints: [], + }; + let currentNode = currentVisibleParent as Node; + for (let index = 1; currentNode.name !== tf_graph.ROOT_NAME; index++) { + if (currentNode.parentNode) { + currentNode = currentNode.parentNode; + } + startNodeParents[currentNode.name] = { + traced: false, + index: index, + connectionEndpoints: [], + }; + indexedStartNodeParents[index] = currentNode; + } + // Find first mutual parent of each input node and highlight connection. + _.forOwn(visibleInputs, function (visibleParentInfo: VisibleParent, key) { + let nodeInstance = visibleParentInfo.visibleParent; + // Make recursive call for each input-OpNode contained by the visible + // parent. + _.each(visibleParentInfo.opNodes, function (opNode: OpNode) { + allTracedNodes = traceAllInputsOfOpNode(svgRoot, renderGraphInfo, opNode, allTracedNodes); + }); + if (nodeInstance.name !== currentVisibleParent.name) { + _createVisibleTrace(svgRoot, nodeInstance, startNodeParents, indexedStartNodeParents); + } + }); + return allTracedNodes; +} +/** + * Colors the edges to connect the passed node to the start node. This is + * done by: + * + * a) Finding the first (visible) common parent in the rendered + * hierarchy. + * NB: There are 2 types of connections: + * 1) Direct connections between node A + * and B, marked below as II, + * 2) Connections from any node A to its parent, A'. Marked below as I and III. + * For type 2 connection you need to know the inner-nested node, the + * direct parent, and the ultimate destination of the connection. + * + * A_parent B_parent + * +--------+ +---------+ + * | | | | + * | +--+ I| II |III+--+ | + * | |A +---------->+B | | + * | +--+ | | +--+ | + * | | | | + * +--------+ +---------+ + * + * + * b) Highlighting the direct connection between the parents of A and B, + * called A_parent and B_parent, s.t. A_parent and B_parent are children of the + * mutual parent of A and B found in a), marked above as II. + * + * c) Highlighting the connection from A to A_parent and B to B_parent + * (through all layers of parents between A and A_parent and B and B_parent, + * respectively). Marked above as I and III. + * + * @param nodeInstance The instance of the node to use as destination node, B. + * @param startNodeParents Map of startNodeParent names to information objects + * about the parent. + * @param indexedStartNodeParents An array of all parents of the start node. + * This is required to find the child of the mutual parent which is a parent + * of the start node. + * @private + */ +function _createVisibleTrace( + svgRoot: SVGElement, + nodeInstance: Node, + startNodeParents, + indexedStartNodeParents: Node[], +): void { + let currentNode = nodeInstance; + let previousNode = nodeInstance; + // Ascend through parents until a mutual parent is found with the start + // node. + let destinationParentPairs: Node[][] = []; + while (!startNodeParents[currentNode.name]) { + if (previousNode.name !== currentNode.name) { + destinationParentPairs.push([previousNode, currentNode]); + } + previousNode = currentNode; + if (currentNode.parentNode) { + currentNode = currentNode.parentNode; + } + } + // Connection between nodes is drawn between the parents of each + // respective node, both of which share the mutual parent. + let startNodeIndex = startNodeParents[currentNode.name].index; + let startNodeName = indexedStartNodeParents[Math.max(startNodeIndex - 1, 0)].name; + let startNodeTopParentName = startNodeName; + let targetNodeTopParentName = previousNode.name; + let endNodeName = previousNode.name; + const svg = d3.select(svgRoot); + svg.selectAll(`[data-edge="${endNodeName}--${startNodeName}"]`).classed('input-edge-highlight', true); + // Trace up the parents of the input. + _.each(destinationParentPairs, function (value) { + let inner = value[0]; + let outer = value[1]; + let edgeSelector = `[data-edge="${inner.name}--${startNodeTopParentName}` + `~~${outer.name}~~OUT"]`; + svg.selectAll(edgeSelector).classed('input-edge-highlight', true); + }); + // Trace up the parents of the start node. + for (let index = 1; index < startNodeIndex; index++) { + let inner = indexedStartNodeParents[index - 1]; + let outer = indexedStartNodeParents[index]; + let edgeSelector = `[data-edge="${targetNodeTopParentName}~~${outer.name}` + `~~IN--${inner.name}"]`; + svg.selectAll(edgeSelector).classed('input-edge-highlight', true); + } +} +/** + * Creates map { [name: string] -> Node } of all visible / rendered parents + * of the nodes identified by the node names passed in. + * + * @param renderGraphInfo The information on the rendered graph. + * @param nodeNames String array of node names. + * @returns {[nodeName: string]: Node} + * @private + */ +function _findVisibleParentsFromOpNodes(renderGraphInfo, nodeNames: string[]): { [nodeName: string]: tf_graph.Node } { + let visibleParents: { + [nodeName: string]: Node; + } = {}; + _.each(nodeNames, function (nodeName) { + let currentNode = renderGraphInfo.getNodeByName(nodeName); + let visibleParent = getVisibleParent(renderGraphInfo, currentNode); + visibleParents[visibleParent.name] = visibleParent; + }); + return visibleParents; +} +/** + * Traverse through the parents of all nodes in the list and mark each + * encountered node as input-parent. + * @param visibleNodes Map of input nodes, have to be visible/rendered when + * called. + * @private + */ +function _markParentsOfNodes( + svgRoot: SVGElement, + visibleNodes: { + [nodeName: string]: Node; + }, +): void { + _.forOwn(visibleNodes, function (nodeInstance: Node) { + // Mark all parents of the node as input-parents. + let currentNode = nodeInstance; + function shouldSkip(renderedElementSelection: any): boolean { + return ( + !renderedElementSelection.nodes().length || + renderedElementSelection.classed('input-highlight') || + renderedElementSelection.classed('selected') || + renderedElementSelection.classed('op') + ); + } + while (currentNode.name !== tf_graph.ROOT_NAME) { + const renderedElementSelection = d3.select(svgRoot).select(`.node[data-name="${currentNode.name}"]`); + // Only mark the element as a parent node to an input if it is not + // marked as input node itself. + if (shouldSkip(renderedElementSelection)) { + renderedElementSelection.classed('input-parent', true); + } + if (currentNode.parentNode) { + currentNode = currentNode.parentNode; + } + } + }); +} +/** + * Find the parent of the passed in op node which is expanded. This is done + * by going through all parents until the parent's parent is expanded, thus + * finding the first unexpanded parent which is rendered on the screen. + * @param renderGraphInfo The graph info object used to gain access to the + * render info of the parents. + * @param currentNode The node whose parent is to be found. + * @returns Node + */ +export function getVisibleParent(renderGraphInfo: render.RenderGraphInfo, currentNode: tf_graph.Node): tf_graph.Node { + let found = false; + let currentParent = currentNode; + while (!found) { + // Get parent element, to extract name. + currentNode = currentParent; + currentParent = currentNode.parentNode; + if (currentParent === undefined) { + found = true; + } else { + let renderNode = renderGraphInfo.getRenderNodeByName(currentParent.name); + // Found if node is rendered on the screen (renderNode truthy), and + // the parent is either expanded (i.e. it is a metanode or seriesnode) + // or the parent is an OpNode in which case currentNode is an embedded + // node which has another OpNode as parent. + if (renderNode && (renderNode.expanded || currentParent instanceof tf_graph.OpNodeImpl)) { + found = true; + } + } + } // Close while loop. + return currentNode; +} + +/** + * Annotations. + */ +export function buildGroupForAnnotation( + container: d3.Selection, + annotationData: render.AnnotationList, + d: render.RenderNodeInfo, + sceneElement, +): void { + // Select all children and join with data. + let annotationGroups = container + .selectAll(function () { + return this.childNodes; + }) + .data(annotationData.list, (dNode) => { + return dNode.node.name; + }); + annotationGroups + .enter() + .append('g') + .attr('data-name', (a) => { + return a.node.name; + }) + .each(function (a) { + let aGroup = d3.select(this); + // Add annotation to the index in the scene + sceneElement.addAnnotationGroup(a, d, aGroup); + // Append annotation edge + let edgeType = Class.Annotation.EDGE; + let metaedge = a.renderMetaedgeInfo?.metaedge; + if (metaedge && !metaedge.numRegularEdges) { + edgeType += ` ${Class.Annotation.CONTROL_EDGE}`; + } + // If any edges are reference edges, add the reference edge class. + if (metaedge?.numRefEdges) { + edgeType += ` ${Class.Edge.REF_LINE}`; + } + edge.appendEdge(aGroup, a, sceneElement, edgeType); + if (a.annotationType !== render.AnnotationType.ELLIPSIS) { + addAnnotationLabelFromNode(aGroup, a); + buildShapeForAnnotation(aGroup, a); + } else { + addAnnotationLabel(aGroup, a.node.name, a, Class.Annotation.ELLIPSIS); + } + }) + .merge(annotationGroups) + .attr('class', (a) => { + return `${Class.Annotation.GROUP} ${annotationToClassName(a.annotationType)} ${nodeClass(a)}`; + }) + .each(function (a) { + let aGroup = d3.select(this); + update(aGroup, d, a, sceneElement); + if (a.annotationType !== render.AnnotationType.ELLIPSIS) { + addInteractionForAnnotation(aGroup, d, a, sceneElement); + } + }); + annotationGroups + .exit() + .each(function (a) { + // Remove annotation from the index in the scene + sceneElement.removeAnnotationGroup(a, d); + }) + .remove(); +} +/** + * Maps an annotation enum to a class name used in css rules. + */ +function annotationToClassName(annotationType: render.AnnotationType): string | null { + return (render.AnnotationType[annotationType] || '').toLowerCase() || null; +} +function buildShapeForAnnotation(aGroup, a: render.Annotation): void { + if (a.annotationType === render.AnnotationType.SUMMARY) { + let summary = selectOrCreateChild(aGroup, 'use'); + summary.attr('class', 'summary').attr('xlink:href', '#summary-icon').attr('cursor', 'pointer'); + } else { + let shape = buildShape(aGroup, a, Class.Annotation.NODE); + // add title tag to get native tooltips + selectOrCreateChild(shape, 'title').text(a.node.name); + } +} +function addAnnotationLabelFromNode(aGroup, a: render.Annotation): void { + let namePath = a.node.name.split('/'); + let text = namePath[namePath.length - 1]; + addAnnotationLabel(aGroup, text, a, null); +} +function addAnnotationLabel(aGroup, label: string, a: render.Annotation, additionalClassNames): void { + let classNames = Class.Annotation.LABEL; + if (additionalClassNames) { + classNames += ` ${additionalClassNames}`; + } + let txtElement = aGroup + .append('text') + .attr('class', classNames) + .attr('dy', '.35em') + .attr('text-anchor', a.isIn ? 'end' : 'start') + .text(label); + enforceLabelWidth(txtElement, -1, FontSizeInPx.Annotation.LABEL); +} +function addInteractionForAnnotation( + selection, + d: render.RenderNodeInfo, + annotation: render.Annotation, + sceneElement, +): void { + selection + .on('mouseover', (a) => { + sceneElement.fire('annotation-highlight', { + name: a.node.name, + hostName: d.node.name, + }); + }) + .on('mouseout', (a) => { + sceneElement.fire('annotation-unhighlight', { + name: a.node.name, + hostName: d.node.name, + }); + }) + .on('click', (a) => { + // Stop this event's propagation so that it isn't also considered a + // graph-select. + (d3.event).stopPropagation(); + sceneElement.fire('annotation-select', { + name: a.node.name, + hostName: d.node.name, + }); + }); + if ( + annotation.annotationType !== render.AnnotationType.SUMMARY && + annotation.annotationType !== render.AnnotationType.CONSTANT + ) { + selection.on('contextmenu', contextmenu.getMenu(sceneElement, d)); + } +} +/** + * Adjust annotation's position. + * + * @param aGroup selection of a 'g.annotation' element. + * @param d Host node data. + * @param a annotation node data. + * @param sceneElement polymer element. + */ +function update(aGroup, d: render.RenderNodeInfo, a: render.Annotation, sceneElement): void { + let cx = layout.computeCXPositionOfNodeShape(d); + // Annotations that point to embedded nodes (constants,summary) + // don't have a render information attached so we don't stylize these. + // Also we don't stylize ellipsis annotations (the string '... and X more'). + if (a.renderNodeInfo && a.annotationType !== render.AnnotationType.ELLIPSIS) { + stylize(aGroup, a.renderNodeInfo, sceneElement, Class.Annotation.NODE); + } + if (a.annotationType === render.AnnotationType.SUMMARY) { + // Update the width of the annotation to give space for the image. + a.width += 10; + } + // label position + aGroup + .select(`text.${Class.Annotation.LABEL}`) + .transition() + .attr('x', cx + a.dx + (a.isIn ? -1 : 1) * (a.width / 2 + a.labelOffset)) + .attr('y', d.y + a.dy); + // Some annotations (such as summary) are represented using a 12x12 image tag. + // Purposely omitted units (e.g. pixels) since the images are vector graphics. + // If there is an image, we adjust the location of the image to be vertically + // centered with the node and horizontally centered between the arrow and the + // text label. + aGroup + .select('use.summary') + .transition() + .attr('x', cx + a.dx - 3) + .attr('y', d.y + a.dy - 6); + // Node position (only one of the shape selection will be non-empty.) + positionEllipse(aGroup.select(`.${Class.Annotation.NODE} ellipse`), cx + a.dx, d.y + a.dy, a.width, a.height); + positionRect(aGroup.select(`.${Class.Annotation.NODE} rect`), cx + a.dx, d.y + a.dy, a.width, a.height); + positionRect(aGroup.select(`.${Class.Annotation.NODE} use`), cx + a.dx, d.y + a.dy, a.width, a.height); + // Edge position + aGroup + .select(`path.${Class.Annotation.EDGE}`) + .transition() + .attr('d', (aItem) => { + // map relative position to absolute position + let points = aItem.points.map((p) => { + return { x: p.dx + cx, y: p.dy + d.y }; + }); + return edge.interpolate(points); + }); +} + +/** + * Scene. + */ + +/** + * Select or create a sceneGroup and build/update its nodes and edges. + * + * Structure Pattern: + * + * + * + * + * ... stuff from tf.graph.scene.edges.build ... + * + * + * ... stuff from tf.graph.scene.nodes.build ... + * + * + * + * + * ... stuff from tf.graph.scene.nodes.build ... + * + * + * + * + * ... stuff from tf.graph.scene.nodes.build ... + * + * + * + * + * @param container D3 selection of the parent. + * @param renderNode render node of a metanode or series node. + * @param sceneElement polymer element. + * @param sceneClass class attribute of the scene (default='scene'). + */ +export function buildGroupForScene( + container, + renderNode: render.RenderGroupNodeInfo, + sceneElement: TfGraphScene, + sceneClass?: string, +): void { + sceneClass = sceneClass ?? Class.Scene.GROUP; + let isNewSceneGroup = selectChild(container, 'g', sceneClass).empty(); + let sceneGroup = selectOrCreateChild(container, 'g', sceneClass); + // core + let coreGroup = selectOrCreateChild(sceneGroup, 'g', Class.Scene.CORE); + let coreNodes = _.reduce( + renderNode.coreGraph.nodes(), + (nodes, name) => { + let node = renderNode.coreGraph.node(name); + if (!node.excluded) { + nodes.push(node); + } + return nodes; + }, + Array(), + ); + if (renderNode.node.type === NodeType.SERIES) { + // For series, we want the first item on top, so reverse the array so + // the first item in the series becomes last item in the top, and thus + // is rendered on the top. + coreNodes.reverse(); + } + // Create the layer of edges for this scene (paths). + edge.buildGroup(coreGroup, renderNode.coreGraph, sceneElement); + // Create the layer of nodes for this scene (ellipses, rects etc). + buildGroup(coreGroup, coreNodes, sceneElement); + // In-extract + if (renderNode.isolatedInExtract.length > 0) { + let inExtractGroup = selectOrCreateChild(sceneGroup, 'g', Class.Scene.INEXTRACT); + buildGroup(inExtractGroup, renderNode.isolatedInExtract, sceneElement); + } else { + selectChild(sceneGroup, 'g', Class.Scene.INEXTRACT).remove(); + } + // Out-extract + if (renderNode.isolatedOutExtract.length > 0) { + let outExtractGroup = selectOrCreateChild(sceneGroup, 'g', Class.Scene.OUTEXTRACT); + buildGroup(outExtractGroup, renderNode.isolatedOutExtract, sceneElement); + } else { + selectChild(sceneGroup, 'g', Class.Scene.OUTEXTRACT).remove(); + } + // Library functions + if (renderNode.libraryFunctionsExtract.length > 0) { + let outExtractGroup = selectOrCreateChild(sceneGroup, 'g', Class.Scene.FUNCTION_LIBRARY); + buildGroup(outExtractGroup, renderNode.libraryFunctionsExtract, sceneElement); + } else { + selectChild(sceneGroup, 'g', Class.Scene.FUNCTION_LIBRARY).remove(); + } + tf_graph_scene.position(sceneGroup, renderNode); + // Fade in the scene group if it didn't already exist. + if (isNewSceneGroup) { + sceneGroup.attr('opacity', 0).transition().attr('opacity', 1); + } +} +export function getColors(colors): void { + colorStorage = colors; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/parser.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/parser.ts new file mode 100644 index 000000000..758d925f0 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/parser.ts @@ -0,0 +1,343 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as tb_debug from '../tb_debug'; +import { ProgressTracker } from './common'; +import * as tf_graph_proto from './proto'; +import * as tf_graph_util from './util'; + +function parseValue(value: string): string | number | boolean { + if (value === 'true') { + return true; + } + if (value === 'false') { + return false; + } + let firstChar = value[0]; + if (firstChar === '"') { + return value.substring(1, value.length - 1); + } + let num = parseFloat(value); + return isNaN(num) ? value : num; +} +/** + * Fetches a text file and returns a promise of the result. + */ +export function fetchPbTxt(filepath: string): Promise { + return new Promise((resolve, reject) => { + fetch(filepath).then((res) => { + // Fetch does not reject for 400+. + if (res.ok) { + res.arrayBuffer().then(resolve, reject); + } else { + res.text().then(reject, reject); + } + }); + }); +} +/** + * Fetches the metadata file, parses it and returns a promise of the result. + */ +export function fetchAndParseMetadata( + path: string, + tracker: ProgressTracker, +): Promise { + return tf_graph_util + .runTask( + 'Reading metadata pbtxt', + 40, + () => { + if (path == null) { + return Promise.resolve(null); + } + return fetchPbTxt(path); + }, + tracker, + tb_debug.GraphDebugEventId.FETCH_METADATA_PBTXT_BYTES, + ) + .then((arrayBuffer: ArrayBuffer | null) => { + return tf_graph_util.runAsyncPromiseTask( + 'Parsing metadata.pbtxt', + 60, + () => { + return arrayBuffer != null ? parseStatsPbTxt(arrayBuffer) : Promise.resolve(null); + }, + tracker, + tb_debug.GraphDebugEventId.PARSE_METADATA_PBTXT_INTO_OBJECT, + ); + }); +} +/** + * Fetches the graph file, parses it and returns a promise of the result. The + * result will be undefined if the graph is empty. + */ +export function fetchAndParseGraphData( + path: string, + pbTxtFile: Blob | null, + tracker: ProgressTracker, +): Promise { + return tf_graph_util + .runAsyncPromiseTask( + 'Reading graph pbtxt', + 40, + async () => { + if (pbTxtFile) { + const result = await new Promise((resolve, reject) => { + let fileReader = new FileReader(); + fileReader.onload = (): void => resolve(fileReader.result as ArrayBuffer); + fileReader.onerror = (): void => reject(fileReader.error); + fileReader.readAsArrayBuffer(pbTxtFile); + }); + return result; + } + + const result = await fetchPbTxt(path); + return result; + }, + tracker, + tb_debug.GraphDebugEventId.FETCH_PBTXT_BYTES, + ) + .then((arrayBuffer: ArrayBuffer) => { + return tf_graph_util.runAsyncPromiseTask( + 'Parsing graph.pbtxt', + 60, + () => { + return parseGraphPbTxt(arrayBuffer); + }, + tracker, + tb_debug.GraphDebugEventId.PARSE_PBTXT_INTO_OBJECT, + ); + }); +} +/** + * Parse a file object in a streaming fashion line by line (or custom delim). + * Can handle very large files. + * @param input The file object as an array buffer. + * @param callback The callback called on each line + * @param chunkSize The size of each read chunk. (optional) + * @param delim The delimiter used to split a line. (optional) + * @returns Promise that resolves with true when it is finished. + */ +export function streamParse( + arrayBuffer: ArrayBuffer, + callback: (string) => void, + chunkSize: number = 1000000, + delim: string = '\n', +): Promise { + return new Promise((resolve, reject) => { + function readChunk(oldData: string, newData: string, offset: number): void { + const doneReading = offset >= arrayBuffer.byteLength; + const parts = newData.split(delim); + parts[0] = oldData + parts[0]; + // The last part may be part of a longer string that got cut off + // due to the chunking. + const remainder = doneReading ? '' : parts.pop(); + for (let part of parts) { + try { + callback(part); + } catch (e) { + reject(e); + return; + } + } + if (doneReading) { + resolve(true); + return; + } + const nextChunk = new Blob([arrayBuffer.slice(offset, offset + chunkSize)]); + const file = new FileReader(); + file.onload = function (e: any): void { + readChunk(remainder ?? '', e.target.result, offset + chunkSize); + }; + file.readAsText(nextChunk); + } + readChunk('', '', 0); + }); +} +/** + * Since proto-txt doesn't explicitly say whether an attribute is repeated + * (an array) or not, we keep a hard-coded list of attributes that are known + * to be repeated. This list is used in parsing time to convert repeated + * attributes into arrays even when the attribute only shows up once in the + * object. + * Repeated fields have to be in sync with graph.proto and all of its + * dependencies. + */ +const GRAPH_REPEATED_FIELDS: { + [attrPath: string]: boolean; +} = { + 'library.function': true, + 'library.function.node_def': true, + 'library.function.node_def.input': true, + 'library.function.node_def.attr': true, + 'library.function.node_def.attr.value.list.b': true, + 'library.function.node_def.attr.value.list.f': true, + 'library.function.node_def.attr.value.list.func': true, + 'library.function.node_def.attr.value.list.i': true, + 'library.function.node_def.attr.value.list.s': true, + 'library.function.node_def.attr.value.list.shape': true, + 'library.function.node_def.attr.value.list.shape.dim': true, + 'library.function.node_def.attr.value.list.tensor': true, + 'library.function.node_def.attr.value.list.type': true, + 'library.function.node_def.attr.value.shape.dim': true, + 'library.function.node_def.attr.value.tensor.string_val': true, + 'library.function.node_def.attr.value.tensor.tensor_shape.dim': true, + 'library.function.signature.input_arg': true, + 'library.function.signature.output_arg': true, + 'library.versions': true, + node: true, + 'node.input': true, + 'node.attr.value.list.b': true, + 'node.attr.value.list.f': true, + 'node.attr.value.list.func': true, + 'node.attr.value.list.i': true, + 'node.attr.value.list.s': true, + 'node.attr.value.list.shape': true, + 'node.attr.value.list.shape.dim': true, + 'node.attr.value.list.tensor': true, + 'node.attr.value.list.type': true, + 'node.attr.value.shape.dim': true, + 'node.attr.value.tensor.string_val': true, + 'node.attr.value.tensor.tensor_shape.dim': true, +}; +const METADATA_REPEATED_FIELDS: { + [attrPath: string]: boolean; +} = { + 'step_stats.dev_stats': true, + 'step_stats.dev_stats.node_stats': true, + 'step_stats.dev_stats.node_stats.output': true, + 'step_stats.dev_stats.node_stats.memory': true, + 'step_stats.dev_stats.node_stats.output.tensor_description.shape.dim': true, +}; +/** + * Parses an ArrayBuffer of a proto txt file into a raw Graph object. + */ +export function parseGraphPbTxt(input: ArrayBuffer): Promise { + return parsePbtxtFile(input, GRAPH_REPEATED_FIELDS); +} +/** + * Parses an ArrayBuffer of a proto txt file into a StepStats object. + */ +export function parseStatsPbTxt(input: ArrayBuffer): Promise { + return parsePbtxtFile(input, METADATA_REPEATED_FIELDS).then((obj) => obj.step_stats); +} +/** + * Parses a ArrayBuffer of a proto txt file into javascript object. + * + * @param input The ArrayBuffer or file object implementing slice. + * @param repeatedFields Map (Set) of all the repeated fields, since you can't + * tell directly from the pbtxt if a field is repeated or not. + * @returns The parsed object. + */ +function parsePbtxtFile( + input: ArrayBuffer, + repeatedFields: { + [attrPath: string]: boolean; + }, +): Promise { + let output: { + [name: string]: any; + } = {}; + let stack: Array<{ [name: string]: any }> = []; + let path: string[] = []; + let current: { + [name: string]: any; + } = output; + function splitNameAndValueInAttribute(line: string): { name: string; value: any } { + let colonIndex = line.indexOf(':'); + let name = line.substring(0, colonIndex).trim(); + let value: any = parseValue(line.substring(colonIndex + 2).trim()); + if (name === 'input_data' || name === 'output_data') { + value = JSON.parse((value as string).replace(/'{/g, '{').replace(/}'/g, '}').replace(/'/g, '"')) as object; + } else if (name === 'matched_node_link') { + value = JSON.parse((value as string).replace(/'/g, '"')) as string[]; + } else if (name === 'subnodes') { + value = JSON.parse((value as string).replace(/'/g, '"')) as string[]; + } else if (name === 'suggestions') { + value = JSON.parse((value as string).replace(/'{/g, '{').replace(/}'/g, '}').replace(/'/g, '"')) as object; + } else { + } + if (name === 'attr') { + const valueObj = JSON.parse((value as string).replace(/'/g, '"')) as object; + value = Object.keys(valueObj).map((key) => { + return { + key, + value: valueObj[key], + }; + }); + } + return { + name: name, + value: value, + }; + } + /** + * Adds a value, given the attribute name and the host object. If the + * attribute already exists, but is not an array, it will convert it to an + * array of values. + * + * @param obj The host object that holds the attribute. + * @param name The attribute name (key). + * @param value The attribute value. + * @param pathAtt A path that identifies the attribute. Used to check if + * an attribute is an array or not. + */ + function addAttribute( + obj: { [name: string]: any }, + name: string, + value: { [name: string]: any } | string | number | boolean, + pathAtt: string[], + ): void { + // We treat 'node' specially since it is done so often. + let existingValue = obj[name]; + if (existingValue == null) { + obj[name] = pathAtt.join('.') in repeatedFields ? [value] : value; + } else if (Array.isArray(existingValue)) { + existingValue.push(value); + } else { + obj[name] = [existingValue, value]; + } + } + // Run through the file a line at a time. + return streamParse(input, (line: string) => { + let lineNew = line.trim(); + if (!lineNew) { + return; + } + switch (lineNew[lineNew.length - 1]) { + case '{': { + // create new object + let name = lineNew.substring(0, lineNew.length - 2).trim(); + let newValue: { + [name: string]: any; + } = {}; + stack.push(current); + path.push(name); + addAttribute(current, name, newValue, path); + current = newValue; + break; + } + case '}': + current = stack.pop() ?? {}; + path.pop(); + break; + default: + let x = splitNameAndValueInAttribute(lineNew); + addAttribute(current, x.name, x.value, path.concat(x.name)); + break; + } + }).then(() => { + return output; + }); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/proto.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/proto.ts new file mode 100644 index 000000000..3e34fe429 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/proto.ts @@ -0,0 +1,221 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +/** + * @fileoverview Interfaces that parallel proto definitions in + * third_party/tensorflow/core/framework/... + * graph.proto + * step_stats.proto + * These should stay in sync. + * + * When adding a repeated field to this file, make sure to update the + * GRAPH_REPEATED_FIELDS and METADATA_REPEATED_FIELDS lists within parser.ts. + * Otherwise, the parser has no way of differentiating between a field with a + * certain value and a repeated field that has only 1 occurence, resulting in + * subtle bugs. + */ + +export enum NodeOpType { + MODULE = 0, + DEFAULT = 1, + MULTI_COLLECTION = 8, + API_LIST = 9, +} +/** Name of the node */ +export interface NodeDef { + name: string; + /** List of nodes that are inputs for this node. */ + input: string[]; + /** The name of the operation associated with this node. */ + op: string; + /** The op type of the node. */ + node_type: NodeOpType; + /** The array of inputs data in JSON string format. */ + input_data: { + [key: string]: any; + }; + /** The array of outputs data in JSON string format. */ + output_data: { + [key: string]: any; + }; + stack_info: []; + matched_node_link: []; + suggestions: { + [key: string]: string; + }; + /** The array consist of the path of linked node in graph comparison. */ + subnodes?: string[]; + isLeaf: boolean; + /** List of attributes that describe/modify the operation. */ + attr: { + key: string; + value: Record; + }[]; +} +export interface EdgeInfo { + input: string; + output: string; + shape: string; + attr: { + key: string; + value: Record; + }[]; +} +/** + * Specifies an argument. An argument is either an input or an output of a + * function. There are thus 2 types of arguments: input_args and output_args. + * Nodes outside a function call connect to arguments. The graph explorer + * creates nodes for all arguments within a function. + */ +export interface ArgDef { + name: string; + type: string; +} +/** + * Describes the signature of a function - its name, inputs, and outputs. + */ +export interface OpDef { + name: string; + input_arg: ArgDef[]; + output_arg: ArgDef[]; +} +/** + * Describes a single function within the library. + */ +export interface FunctionDef { + // The definition of the function's name, arguments, return values, + // attrs etc. + signature: OpDef; + // A list of nodes in the function. + node_def: NodeDef[]; +} +/** + * TensorFlow graph definition as defined in the graph.proto file. + */ +export interface GraphDef { + // A list of nodes in the graph. + node: NodeDef[]; + // The information of the list of edges. + edge?: EdgeInfo[]; +} +/** + * Generic graph as defined in the graph_explorer.proto file. + */ +export interface GenericGraph { + /** List of nodes in the graph */ + node: GenericNode[]; + /** List of nodes in the graph */ + edge: GenericEdge[]; + /** List of attributes that describe/modify the operation. */ + attr: Array<{ + [key: string]: any; + }>; +} +/** + * GenericEdge corresponds to the Edge message in graph_explorer.proto. + */ +export interface GenericEdge { + /** Name of the source node. */ + source: string; + /** Name of the target node. */ + target: string; + /** Attributes of the edge. */ + edge_attr: Array<{ + [key: string]: any; + }>; +} +/** + * GenericNode corresponds to the Node message in graph_explorer.proto. + */ +export interface GenericNode { + /** Name of the node */ + name: string; + /** Attributes of a leaf node or leaf nodes within a metanode. */ + node_attr: Array<{ + [key: string]: any; + }>; + /** Attributes of a metanode. */ + metanode_attr: Array<{ + [key: string]: any; + }>; +} +export interface DevStat { + device: string; + node_stats: NodeExecStats[]; +} +/** + * TensorFlow stats file definition as defined in the stats proto file. + */ +export interface StepStats { + dev_stats: DevStat[]; +} +/** + * TensorFlow stats for a node as defined in the step_stats proto file. + */ +export interface NodeExecStats { + node_name: string; + // The next 4 properties are currently stored as string in json + // and must be parsed. + all_start_micros: number; + op_start_rel_micros: number; + op_end_rel_micros: number; + all_end_rel_micros: number; + memory: { + allocator_name: string; + total_bytes: number; // Stored as string in json and should be parsed. + peak_bytes: number; // Stored as string in json and should be parsed. + }[]; + /** Output sizes recorded for a single execution of a graph node */ + output: NodeOutput[]; + timeline_label: string; + scheduled_micros: string; + thread_id: string; +} +/** + * Description for the output tensor(s) of an operation in the graph as + * defined in the step_stats.proto file. + */ +export interface NodeOutput { + slot: number; // Stored as string in json and should be parsed. + tensor_description: { + /** Data type of tensor elements */ + dtype: string; + /** Shape of the tensor */ + shape: { + /** + * Dimensions of the tensor, such as [{name: 'input', size: 30}, + * {name: 'output', size: 40}] for a 30 x 40 2D tensor. The names + * are optional. The order of entries in 'dim' matters: It indicates + * the layout of the values in the tensor in-memory representation. + */ + dim: { + /** Size of the tensor in that dimension */ + size: number; // Stored as string in json and should be parsed. + /** Optional name of the tensor dimension */ + name?: string; + }[]; + }; + /** Information about the size and allocator used for the data */ + allocation_description: { + // The next 2 properties are stored as string in json and + // should be parsed. + /** Total number of bytes requested */ + requested_bytes: number; + /** Total number of bytes allocated, if known */ + allocated_bytes?: number; + /** Name of the allocator used */ + allocator_name: string; + }; + }; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/render.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/render.ts new file mode 100644 index 000000000..026a08339 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/render.ts @@ -0,0 +1,1348 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +/** + * Package for the Render Hierarchy for TensorFlow graph. + */ +import * as d3 from 'd3'; +import { graphlib } from 'dagre'; +import * as _ from 'lodash'; +import { NPU_PREFIX, BENCH_PREFIX, EDGE_WIDTH_SIZE_BASED_SCALE } from './common'; +import * as tf_graph from './graph'; +import { + BridgeNode, + createGraph, + EllipsisNode, + getHierarchicalPath, + GraphType, + GroupNode, + InclusionType, + Metaedge, + MetaedgeImpl, + Metanode, + Node, + NodeType, + OpNode, + OpNodeImpl, +} from './graph'; +import { Hierarchy } from './hierarchy'; +import { NodeOpType } from './proto'; + +const NODE_LINE_FEED_NUMBER = 5; +export interface EdgeData { + v: string; + w: string; + id: number; + label: RenderMetaedgeInfo; +} + +export interface Point { + x: number; + y: number; +} +/** + * Color parameters for op nodes. + */ +export const OpNodeColors = { + DEFAULT_FILL: '#ffffff', + DEFAULT_STROKE: '#b2b2b2', +}; +/** + * Color parameters for node encoding. + * @type {Object} + */ +export let MetanodeColors = { + /** + * Default fill and stroke to use when no other information is available. + */ + DEFAULT_FILL: '#d9d9d9', + DEFAULT_STROKE: '#a6a6a6', + SATURATION: 0.6, + LIGHTNESS: 0.85, + /** + * Neutral color to use when the node is expanded (used when coloring by + * compute time, memory and device). + */ + EXPANDED_COLOR: '#f0f0f0', + /** + * Standard hue values for node color palette. + */ + HUES: [220, 100, 180, 40, 20, 340, 260, 300, 140, 60], + STRUCTURE_PALETTE(id: number, lightened?: boolean): string { + // The code below is a flexible way to computationally create a set + // of colors that go well together. + let hues = MetanodeColors.HUES; + let n = hues.length; + let hue = hues[id % n]; + let m = Math.sin((hue * Math.PI) / 360); + let sat = lightened ? 30 : 90 - 60 * m; + let light = lightened ? 95 : 80; + return d3.hsl(hue, 0.01 * sat, 0.01 * light).toString(); + }, + DEVICE_PALETTE(index: number): string { + return MetanodeColors.STRUCTURE_PALETTE(index); + }, + XLA_CLUSTER_PALETTE(index: number): string { + return MetanodeColors.STRUCTURE_PALETTE(index); + }, + UNKNOWN: '#eee', + GRADIENT_OUTLINE: '#888', +}; +/** + * Color parameters for op nodes. + */ +export const SeriesNodeColors = { + DEFAULT_FILL: 'white', + DEFAULT_STROKE: '#b2b2b2', +}; +/** + * Function that computes edge thickness in pixels. + */ +export interface EdgeThicknessFunction { + (edgeData: EdgeData, edgeClass: string): number; +} +/** + * Function that computes edge label strings. This function accepts a Metaedge, + * which could actually encapsulate several base edges. For instance, several + * base edges may merge into a single metaedge. + * + * To determine whether a metaedge represents several edges, check the length of + * its baseEdgeList property. + */ +export interface EdgeLabelFunction { + (metaedge: Metaedge, renderInfo: RenderGraphInfo): string; +} +/** + * Parameters that affect how the graph is rendered on the screen. + */ +const PARAMS = { + /** + * The minimum number of nodes for a graph to have in order for high in and + * out degree nodes to be extracted in auxiliary. The aim here is to prevent + * nodes from being extracted from small graphs. + */ + minNodeCountForExtraction: 15, + /** + * The minimum in or out degree a node must have in order to be possibly + * extracted. + */ + minDegreeForExtraction: 5, + /** + * Maximum number of control edges a node can have before they aren't + * displayed. + */ + maxControlDegree: 4, + /** + * Maximum in (for outbound bridge paths) or out (for inbound bridge paths) + * degree of a node allowed for a bridge path to be rendered to it from a + * subhierarchy of nodes. Having a max prevents having too many nodes emanate + * from a subhierarchy and crowding up. + */ + maxBridgePathDegree: 4, + /** + * Types patterns for predefined out-extract nodes, which are + * sink-like nodes that will be extracted from the main graph. + */ + outExtractTypes: ['NoOp'], + /** + * Types patterns for predefined in-extract nodes, which are + * source-like nodes that will be extracted from the main graph. + */ + inExtractTypes: [], + /** + * When removing edges from a high degree node, remove all of its edges if + * detachAllEdgesForHighDegree is true. Otherwise remove all in-edges if + * the node has high in-degree, or all out-edges if the node has high + * out-degree. + */ + detachAllEdgesForHighDegree: true, + /** + * After extracting high in/out degree nodes and predefined + * source-like/sink-like, extract isolated nodes to the side + * if this extractIsolatedNodesWithAnnotationsOnOneSide is true. + */ + extractIsolatedNodesWithAnnotationsOnOneSide: true, + /** + * Whether to add bridge nodes and edges to the core when building the + * subhierarchy of an expanded metanode. See buildSubhierarchy(). + */ + enableBridgegraph: true, + /** + * 2 colors, for the minimum and maximum value respectively, whenever we + * have a gradient scale. + */ + minMaxColors: ['#fff5f0', '#fb6a4a'], + /** + * Maximum number of annotations to be displayed on a node before an + * ellipsis is used. + */ + maxAnnotations: 5, +}; +/** + * The regular expression to use when parsing for the string that is + * used to label a function node in the graph. We strip away a prefix + * indicating that the node represents a function definition. We also + * remove an arbitrary hexadecimal suffix and the number following it + * if it is present. To be clear, we extract foo from + * __function_library__foo_deadb00f_42. + */ +const nodeDisplayNameRegex = new RegExp( + `^(?:'${tf_graph.FUNCTION_LIBRARY_NODE_PREFIX}')?(\\w+)_[a-z0-9]{8}(?:_\\d+)?$`, +); +// 同时包含npu侧和标杆侧的图渲染信息 +export interface MergedRenderGraphInfo { + npu: RenderGraphInfo; + bench?: RenderGraphInfo; +} +/** + * Stores the rendering information, such as x and y coordinates, + * for each node in the graph. + */ +export class RenderGraphInfo { + hierarchy: Hierarchy; + renderedOpNames: string[]; + /** Scale for the thickness of edges when there is no shape information. */ + edgeWidthSizedBasedScale: d3.ScaleLinear | d3.ScalePower; + root: RenderGroupNodeInfo; + traceInputs: boolean; + private index: { + [nodeName: string]: RenderNodeInfo; + }; + private toRenderEdgeObjs: { + v: string; + w: string; + id: number; + edge: tf_graph.Metaedge; + }[]; + // Since the rendering information for each node is constructed lazily, + // upon node's expansion by the user, we keep a map between the node's name + // and whether the rendering information was already constructed for that + // node. + private hasSubhierarchy: { + [nodeName: string]: boolean; + }; + constructor(hierarchy: Hierarchy) { + this.hierarchy = hierarchy; + this.index = {}; + this.toRenderEdgeObjs = []; + this.renderedOpNames = []; + // Maps node name to whether the rendering hierarchy was already + // constructed. + this.hasSubhierarchy = {}; + this.root = new RenderGroupNodeInfo(hierarchy.root, hierarchy.graphOptions); + this.index[hierarchy.root.name] = this.root; + this.renderedOpNames.push(hierarchy.root.name); + this.buildSubhierarchy(hierarchy.root.name); + this.root.expanded = true; + this.traceInputs = false; + this.edgeWidthSizedBasedScale = EDGE_WIDTH_SIZE_BASED_SCALE; + } + + /** + * Get index. + */ + getIndex(): { [nodeName: string]: RenderNodeInfo } { + return this.index; + } + + /** + * Get a previously created RenderNodeInfo by its node name. + */ + getRenderNodeByName(nodeName: string): RenderNodeInfo { + return this.index[nodeName]; + } + + /** + * Get the underlying node in the hierarchical graph by its name. + */ + getNodeByName(nodeName: string): Node { + return this.hierarchy.node(nodeName); + } + + /** + * Get a previously created RenderNodeInfo for the specified node name, + * or create one if it hasn't been created yet. + */ + getOrCreateRenderNodeByName(nodeName: string): RenderNodeInfo | null { + // Polymer may invoke this with null. + if (!nodeName) { + return null; + } + if (nodeName in this.index) { + return this.index[nodeName]; + } + let node = this.hierarchy.node(nodeName); + // Exit early if the node does not exist in the hierarchy. This can happen + // when a graph is reloaded while the infocard points to a node not visible + // at the top-level. + if (!node) { + return null; + } + let renderInfo = node.isGroupNode + ? new RenderGroupNodeInfo(node, this.hierarchy.graphOptions) + : new RenderNodeInfo(node); + this.index[nodeName] = renderInfo; + this.renderedOpNames.push(nodeName); + return this.index[nodeName]; + } + + /** + * Return the nearest ancestor node, including itself, that is visible + * in the visualization. This method is used so that we can select + * (highlight) a node that isn't drawn yet, by selecting (highlighting) + * its nearest ancestor that has been drawn. + */ + getNearestVisibleAncestor(name: string): string { + let path = getHierarchicalPath(name); + let i = 0; + let renderNode: RenderNodeInfo | null = null; + // Fallthrough. If everything was expanded return the node. + let nodeName = name; + for (; i < path.length; i++) { + nodeName = path[i]; + renderNode = this.getRenderNodeByName(nodeName); + // Op nodes have expanded set to false by default. + if (renderNode && !renderNode.expanded) { + break; + } + } + if (!renderNode) { + return ''; + } + // Check case where highlighted node is an embedded node whose parent node + // is also its hierarchical parent. In this case, we want to return the + // embedded node name, as it is also displayed if its parent has been + // displayed. + if (i === path.length - 2) { + let nextName = path[i + 1]; + if (renderNode?.inAnnotations.nodeNames[nextName]) { + return nextName; + } + if (renderNode?.outAnnotations.nodeNames[nextName]) { + return nextName; + } + } + return nodeName; + } + + setDepth(depth: number): void { + setGroupNodeDepth(this.root, Number(depth)); + } + + /** + * Returns true if the renderNode is an isolated node within its parent node. + */ + isNodeAuxiliary(renderNode: RenderNodeInfo): boolean { + let parentNode = this.getRenderNodeByName(renderNode.node.parentNode.name); + let found = _.find(parentNode.isolatedInExtract, (node) => { + return node.node.name === renderNode.node.name; + }); + if (found) { + return true; + } + found = _.find(parentNode.isolatedOutExtract, (node) => { + return node.node.name === renderNode.node.name; + }); + return !!found; + } + + /** + * Returns a list of ops that have been rendered so far for this graph. More + * ops may later be rendered if the user expands nodes for instance. The list + * returned here can only stay the same size or grow on successive calls. + */ + getNamesOfRenderedOps(): string[] { + return this.renderedOpNames; + } + + buildSubhierarchy(nodeName: string, subGraph: tf_graph.SlimGraph | undefined = undefined): void { + // Terminate if the rendering hierarchy was already constructed + // for this node. + if (nodeName in this.hasSubhierarchy) { + return; + } + // Record that we constructed the rendering hierarchy for this node, so we + // don't construct it another time. + this.hasSubhierarchy[nodeName] = true; + let renderNodeInfo = this.index[nodeName]; + // If it is not a meta node or a series node, don't do anything. + const excludedTypes = [NodeType.META, NodeType.MULTI_COLLECTION, NodeType.API_LIST, NodeType.SERIES]; + if (!excludedTypes.includes(renderNodeInfo.node.type)) { + return; + } + // At this point we know the rendering information is about a group node. + let renderGroupNodeInfo = renderNodeInfo; + let metagraph = renderGroupNodeInfo.node.metagraph; + let coreGraph = renderGroupNodeInfo.coreGraph; + // Create render nodes to represent each child from the metagraph. Although + // these will initially be added to the coreGraph, they may later be + // extracted. Also, due to extraction, the coreGraph may contain disjoint + // groups between which there is no visible path (other than annotations). + _.each(metagraph.nodes(), (childName, index: number) => { + let childRenderInfo = this.getOrCreateRenderNodeByName(childName); + if (!childRenderInfo) { + return; + } + let childNode = childRenderInfo.node; + coreGraph.setNode(childName, childRenderInfo); + // 可展开节点自成一行，模块间游离节点每NODE_LINE_FEED_NUMBER个换行 + if (index >= 1 && subGraph && Object.keys(subGraph.metaNodes).length > 0) { + coreGraph.setEdge(metagraph.nodes()[index - 1], childName, {}); + } else if (index >= NODE_LINE_FEED_NUMBER && subGraph && Object.keys(subGraph.metaNodes).length === 0) { + coreGraph.setEdge(metagraph.nodes()[index - NODE_LINE_FEED_NUMBER], childName, {}); + } + if (!childNode.isGroupNode) { + _.each((childNode).inEmbeddings, (embedding) => { + let renderMetaedgeInfo = new RenderMetaedgeInfo(null); + let renderNodeData = new RenderNodeInfo(embedding); + addInAnnotation( + childRenderInfo as RenderNodeInfo, + embedding, + renderNodeData, + renderMetaedgeInfo, + AnnotationType.CONSTANT, + ); + this.index[embedding.name] = renderNodeData; + }); + _.each((childNode).outEmbeddings, (embedding) => { + let renderMetaedgeInfo = new RenderMetaedgeInfo(null); + let renderNodeData = new RenderNodeInfo(embedding); + addOutAnnotation( + childRenderInfo as RenderNodeInfo, + embedding, + renderNodeData, + renderMetaedgeInfo, + AnnotationType.SUMMARY, + ); + this.index[embedding.name] = renderNodeData; + }); + } + }); + // Add render metaedge info for edges in the metagraph. + _.each(metagraph.edges(), (edgeObj) => { + if (edgeObj.v.includes(tf_graph.NAMESPACE_DELIM) || edgeObj.w.includes(tf_graph.NAMESPACE_DELIM)) { + let inbound = edgeObj.w.includes(tf_graph.NAMESPACE_DELIM); + if (inbound) { + let pathNames = edgeObj.w.split(tf_graph.NAMESPACE_DELIM); + this.toRenderEdgeObjs.push({ + v: edgeObj.v, + w: pathNames[pathNames.length - 1], + id: edgeObj.name, + edge: metagraph.edge(edgeObj), + }); + } else { + let pathNames = edgeObj.v.split(tf_graph.NAMESPACE_DELIM); + this.toRenderEdgeObjs.push({ + v: pathNames[pathNames.length - 1], + w: edgeObj.w, + id: edgeObj.name, + edge: metagraph.edge(edgeObj), + }); + } + return; + } + let metaedge = metagraph.edge(edgeObj); + let renderMetaedgeInfo = new RenderMetaedgeInfo(metaedge as any); + renderMetaedgeInfo.isFadedOut = this.index[edgeObj.v].isFadedOut || this.index[edgeObj.w].isFadedOut; + coreGraph.setEdge(edgeObj.v, edgeObj.w, renderMetaedgeInfo, edgeObj.name); + }); + // Look up the parent node's render information and short circuit if none. + let parentNode = renderGroupNodeInfo.node.parentNode; + if (!parentNode) { + return; + } + let parentNodeInfo = this.index[parentNode.name]; + // Utility function for computing the name of a bridge node. + let getBridgeNodeName = (inbound, ...rest): string => rest.concat([inbound ? 'IN' : 'OUT']).join('~~'); + if (subGraph) { + const subNodes = Object.keys(subGraph.metaNodes).concat(Object.keys(subGraph.nodes)); + renderNodeInfo.node.cardinality += subNodes.length; + const parentMetagraph = (parentNode as GroupNode).metagraph; + const parentBridgegraph = (parentNode as GroupNode).bridgegraph; + _.each(subNodes, (subName) => { + this.toRenderEdgeObjs + .filter((e) => e.v === subName || e.w === subName) + .forEach((item) => { + const edgeObj = item.edge; + const inbound = item.w === subName; + const edgeIO = inbound + ? [edgeObj.v?.split(tf_graph.NAMESPACE_DELIM)[0], nodeName] + : [nodeName, edgeObj.w?.split(tf_graph.NAMESPACE_DELIM)[0]]; + let bridgeMetaedge = parentMetagraph.edge(...edgeIO, item.id); + if (!bridgeMetaedge) { + bridgeMetaedge = parentBridgegraph.edge(...edgeIO, item.id); + if (!bridgeMetaedge) { + return; + } + } + _.each(edgeObj.baseEdgeList, (baseEdge) => { + let name = inbound ? baseEdge.v : baseEdge.w; + if (baseEdge.attr) { + baseEdge.attr._path = name; + } else { + baseEdge.attr = { _path: name }; + } + if (inbound) { + baseEdge.v = name?.split(tf_graph.NAMESPACE_DELIM).pop(); + baseEdge.w = subName; + } else { + baseEdge.v = subName; + baseEdge.w = name?.split(tf_graph.NAMESPACE_DELIM).pop(); + } + bridgeMetaedge.addBaseEdge(baseEdge, this.hierarchy, true); + }); + }); + }); + } + // Remove rendered edges to save memory. + this.toRenderEdgeObjs = this.toRenderEdgeObjs.filter((e) => !this.index[e.v] || !this.index[e.w]); + // Build out the bridgegraph. + let bridgegraph = this.hierarchy.getBridgegraph(nodeName); + // Look for popular nodes so we can make annotations instead of paths. + let otherCounts = { + // Counts of edges coming INTO other nodes by name (outgoing from self). + in: < + { + [nodeName: string]: number; + } + >{}, + // Counts of edges going OUT from other nodes by name (coming into self). + out: < + { + [nodeName: string]: number; + } + >{}, + // Counts of all control edges involving other nodes by name. + control: < + { + [nodeName: string]: number; + } + >{}, + }; + _.each(bridgegraph.edges(), (e) => { + // An edge is inbound if its destination node is in the metagraph. + let inbound = !!metagraph.node(e.w); + let otherName = inbound ? e.v : e.w; + let metaedge = bridgegraph.edge(e); + if (!metaedge.numRegularEdges) { + otherCounts.control[otherName] = (otherCounts.control[otherName] || 0) + 1; + } else if (inbound) { + otherCounts.out[otherName] = (otherCounts.out[otherName] || 0) + 1; + } else { + otherCounts.in[otherName] = (otherCounts.in[otherName] || 0) + 1; + } + }); + // For each bridge container (IN and/or OUT), add structural edges between + // terminal nodes and that container. A terminal node is one which has no + // non-bridge edges in the direction of the container. + // + // For example, consider a Metanode A which contains two child nodes A/B + // and A/C. Let's say it has one edge in the metagraph from A/B->A/C, and + // one edge in the bridgegraph from Z->A/C. + // + // At this point, we've added a container bridge node IN to house all + // incoming bridge nodes. We've also added a bridge node Z' (with parent IN) + // to A, and a bridge edge from Z'->C. + // + // +----------------------+ + // | A +---+ | + // | +------>| C | | + // | | +---+ | + // | | ^ | + // | | | | + // | | +----|----+ | + // | | | IN | | | + // | +---+ | +---+ | | + // | | B | | | Z'| | | + // | +---+ | +---+ | | + // | +---------+ | + // +----------------------+ + // + // With no other help, dagre would lay out B and Z' on the same level, + // because both of them have no incoming edges. In other words, B is a + // terminal node in the INCOMING direction. + // + // But we want to force dagre to lay out Z' (and everything in IN) lower + // than all non-bridge nodes, so that there's enough room for the bridge + // edges after they've been adjusted to meet up with paths coming in from + // outside. + // + // To force Z' (and all other bridge nodes) to be lowest in the graph, we + // identify terminal nodes like B and give them structural edges to + // a new structural bridge node S which we add to IN. + // + // +----------------------+ + // | A +---+ | + // | +--->| C | | + // | | +---+ | + // | +---+ ^ | + // | | B | | | + // | +---+ | | + // | ^ | | + // | | | | + // | +----|------|----+ | + // | |IN | | | | + // | | +---+ +---+ | | + // | | | S | | Z'| | | + // | | +---+ +---+ | | + // | +----------------+ | + // +----------------------+ + // + // This ensures that dagre will lay out the bridge containers strictly at + // the ends of the graph. The structural edges will never be seen in the + // visualization except as a debugging aid. + _.each([true, false], (inbound) => { + let bridgeContainerName = getBridgeNodeName(inbound, nodeName); + let bridgeContainerInfo = coreGraph.node(bridgeContainerName); + if (!bridgeContainerInfo) { + return; + } + _.each(coreGraph.nodes(), (childName) => { + // Short-circuit if this child is a bridge node or it's not a terminal + // node in the direction we're interested in. + let childNodeInfo = coreGraph.node(childName); + if (childNodeInfo.node.type === NodeType.BRIDGE) { + return; + } + let isTerminal = inbound + ? !coreGraph.predecessors(childName)?.length + : !coreGraph.successors(childName)?.length; + if (!isTerminal) { + return; + } + // Find or create a bridge node in the container for all structural + // metaedges. It would have been nice to skip this step and simply + // set a metaedge between the terminal node and the container node, but + // in that case, something about the graph upsets dagre.layout()'s + // longestPath algorithm (was getting errors due to an undefined). + let structuralNodeName = getBridgeNodeName(inbound, nodeName, 'STRUCTURAL_TARGET'); + let structuralRenderInfo = coreGraph.node(structuralNodeName); + if (!structuralRenderInfo) { + let bridgeNode: BridgeNode = { + // Important Node properties. + name: structuralNodeName, + type: NodeType.BRIDGE, + // Unimportant Node properties. + isGroupNode: false, + cardinality: 1, + parentNode: null, + include: InclusionType.UNSPECIFIED, + // BridgeNode properties. + inbound: inbound, + inputData: {}, + outputData: {}, + suggestions: {}, + nodeAttributes: {}, + }; + structuralRenderInfo = new RenderNodeInfo(bridgeNode); + structuralRenderInfo.structural = true; + this.index[structuralNodeName] = structuralRenderInfo as any; + coreGraph.setNode(structuralNodeName, structuralRenderInfo); + bridgeContainerInfo.node.cardinality++; + coreGraph.setParent(structuralNodeName, bridgeContainerName); + } + // Create the structural Metaedge and insert it. + let structuralMetaedgeInfo = new RenderMetaedgeInfo(null); + structuralMetaedgeInfo.structural = true; + structuralMetaedgeInfo.weight--; // Reduce weight for dagre layout. + inbound + ? coreGraph.setEdge(structuralNodeName, childName, structuralMetaedgeInfo) + : coreGraph.setEdge(childName, structuralNodeName, structuralMetaedgeInfo); + }); + }); + } + + checkSubhierarchy(nodeName: string): boolean { + return nodeName in this.hasSubhierarchy; + } + + /** + * Clones an op node and adds it to a metagraph. Does nothing if an op node + * with the same new name has already been created within the metagraph. This + * method is used when duplicating a library function to be injected within a + * metanode representing a function call. + * @param parentMetanode The parent metanode on which to add the new node. + * @param node The op node to clone. + * @param newPrefix The prefix string to use in lieu of the one that merely + * indicates that the metanode represents a function defined in the + * library. This prefix should reflect graph hierarchy. + * @return The newly created op node (the clone of the original). + */ + private cloneAndAddFunctionOpNode( + parentMetanode: Metanode, + libraryFunctionNodeName: string, + node: OpNode, + newPrefix: string, + ): OpNode { + const newName = node.name.replace(libraryFunctionNodeName, newPrefix); + let newOpNode = parentMetanode.metagraph.node(newName) as any; + if (newOpNode) { + // This node had already been created and added to the graph. + return newOpNode; + } + // Create a new op node. + newOpNode = new OpNodeImpl({ + name: newName, + input: [], + op: node.op, + input_data: _.cloneDeep(node.inputData), + output_data: _.cloneDeep(node.outputData), + stack_info: _.cloneDeep(node.stackData), + suggestions: _.cloneDeep(node.suggestions), + isLeaf: false, + attr: _.cloneDeep(node.attr), + node_type: NodeOpType.DEFAULT, + matched_node_link: _.cloneDeep(node.matchedNodeLink), + }); + // Update various properties. + newOpNode.cardinality = node.cardinality; + newOpNode.include = node.include; + newOpNode.outputShapes = _.cloneDeep(node.outputShapes); + // Update the inputs of the new node to reflect the new path. + newOpNode.inputs = node.inputs.map((normalizedInput) => { + const newNormalizedInput = _.clone(normalizedInput); + newNormalizedInput.name = normalizedInput.name.replace(libraryFunctionNodeName, newPrefix); + return newNormalizedInput; + }); + // Add the new op node to the hierarchy and metagraph. Also add it to its + // parent metanode. + newOpNode.parentNode = parentMetanode; + parentMetanode.metagraph.setNode(newOpNode.name, newOpNode); + this.hierarchy.setNode(newOpNode.name, newOpNode); + // Update embeddings. + const updateEmbeddingOpNode = (embeddingNode): OpNode => { + return this.cloneAndAddFunctionOpNode(parentMetanode, libraryFunctionNodeName, embeddingNode, newPrefix); + }; + newOpNode.inEmbeddings = node.inEmbeddings.map(updateEmbeddingOpNode); + newOpNode.outEmbeddings = node.outEmbeddings.map(updateEmbeddingOpNode); + return newOpNode; + } +} +/** + * A class for rendering annotation object which contains label + * about the node embedded as annotation, type of annotation and the location + * of both the annotation's node and edge. + * + * Annotation objects include embedded constants, embedded summary, and + * edge shortcuts. + */ +export class Annotation { + node: Node; + renderNodeInfo: RenderNodeInfo; + renderMetaedgeInfo: RenderMetaedgeInfo | null; + annotationType: AnnotationType; + /** + * Center position of annotation relative to the host + * node's center x. + */ + dx: number; + /** + * Center position of annotation relative to the host + * node's center y. + */ + dy: number; + width: number; + height: number; + /** + * The names of nodes on either side of this edge. + */ + v: string; + w: string; + /** + * A flag whether it is an in-annotation (if true) or + * out-annotation (if false). + */ + isIn: boolean; + /** Label horizontal offset from the end of the node shape */ + labelOffset: number; + /** + * Array of points for edges from the annotation to its host + * node. Each point contains the point location, relative to + * the host node's center. + */ + points: { + dx: number; + dy: number; + }[]; + /** + * Creates a new Annotation. + * + * @param node The underlying node this annotation points to. + * @param renderNodeInfo The render information for the underlying node + * this annotation points to. This can be null if the annotation + * denotes an embedding (constant, summary), in which case we + * use the node property. + * @param renderMetaedgeInfo The render information for the edge associated + * with the annotation. + * @param type The type of the annotation. + * @param isIn True if it is an in-annotation. False if it is an + * out-annotation. + */ + constructor( + node: Node, + renderNodeInfo: RenderNodeInfo, + renderMetaedgeInfo: RenderMetaedgeInfo | null, + type: AnnotationType, + isIn: boolean, + ) { + this.node = node; + this.renderNodeInfo = renderNodeInfo; + this.renderMetaedgeInfo = renderMetaedgeInfo; + this.annotationType = type; + // Properties specified by layout + this.dx = 0; + this.dy = 0; + this.width = 0; + this.height = 0; + // Properties needed for generating an ID for the edge's path element if + // this annotation is associated with a metaedge. + if (renderMetaedgeInfo?.metaedge) { + this.v = renderMetaedgeInfo.metaedge.v ?? ''; + this.w = renderMetaedgeInfo.metaedge.w ?? ''; + } + this.isIn = isIn; + this.points = []; + } +} +export enum AnnotationType { + SHORTCUT = 0, + CONSTANT = 1, + SUMMARY = 2, + ELLIPSIS = 3, +} +/** + * Manages a list of annotations. Two will be used for each + * RenderNodeInfo, one for in annotations and one for out annotations. + */ +export class AnnotationList { + /** + * List of visually drawable annotations, may include an ellipses annotation + * if the number added exceeds the number specified by maxAnnotations. + */ + list: Annotation[]; + /** + * Set of nodes which have been added as annotations to this list, so we can + * prevent duplicates. + */ + nodeNames: { + [nodeName: string]: boolean; + }; + constructor() { + this.list = []; + this.nodeNames = {}; + } + + /** + * Append an annotation to the list, or a stand-in ellipsis annotation instead + * if this would make it too many. + */ + push(annotation: Annotation): void { + if (annotation.node.name in this.nodeNames) { + return; // Skip duplicate annotation. + } + this.nodeNames[annotation.node.name] = true; + if (this.list.length < PARAMS.maxAnnotations) { + this.list.push(annotation); + return; + } + let lastAnnotation = this.list[this.list.length - 1]; + if (lastAnnotation.annotationType === AnnotationType.ELLIPSIS) { + let ellipsisNode = lastAnnotation.node; + ellipsisNode.setNumMoreNodes(++ellipsisNode.numMoreNodes); + return; + } + let ellipsisNode = new tf_graph.EllipsisNodeImpl(1); + this.list.push( + new Annotation(ellipsisNode, new RenderNodeInfo(ellipsisNode), null, AnnotationType.ELLIPSIS, annotation.isIn), + ); + } +} +/** + * Contains rendering information about a node in the hierarchical graph. + */ +export class RenderNodeInfo { + /** Reference to the original underlying Node from the hierarchical graph. */ + node: Node; + /** Whether the node is expanded or not. */ + expanded: boolean; + /** + * List of rendering information about in-annotations like constants and + * shortcuts to high-degree nodes. + */ + inAnnotations: AnnotationList; + /** + * List of rendering information about out-annotations (e.g. summary nodes) + */ + outAnnotations: AnnotationList; + // --- Params specified by layout --- // + /** Center x position */ + x: number; + /** Center y position */ + y: number; + /** + * Total width of the node's shape, including in- and out-annotations. This + * property is used by dagre to layout the graph. + */ + width: number; + /** + * Total height of the node's shape, including in- and out-annotations. This + * property is used by dagre to layout the graph. + */ + height: number; + /** + * Size of the main box of the node, excluding in- and out-annotations. This + * property is used to draw the rectangle/ellipse shape denoting the node. + */ + coreBox: { + width: number; + height: number; + }; + /** Width of the bounding box for all in-annotations. */ + inboxWidth: number; + /** Width of the bounding box for all out-annotations. */ + outboxWidth: number; + /** + * Whether the node should be excluded from the scene. + * This is only used when there are too many items in a series so we only + * want to include top N ones. + */ + excluded: boolean; + // --- Params used in drawing the bridge paths --- // + /** + * All bridge nodes are meant to be invisible, but whereas most represent a + * relationship from the underlying graph hierarchy, some exist solely for + * layout reasons. Specifically, those bridge nodes which have only structural + * rendering metaedges. + */ + structural: boolean; + // --- Params for the size of the node box --- // + /** Label vertical offset from the center of node shape */ + labelOffset: number; + /** Rectangle radius (for making rounded rectangle) */ + radius: number; + // --- Params for expanded node --- // + /** Label height for expanded node. */ + labelHeight: number; + // Paddings between inner subscene and the border of the expanded node. + paddingTop: number; + paddingLeft: number; + paddingRight: number; + paddingBottom: number; + /** + * Whether a node is extracted as source-like (having high out-degree or + * matching predefined in-extract pattern.) + */ + isInExtract: boolean; + /** + * Whether a node is extracted as sink-like (having high in-degree or matching + * predefined out-extract pattern.) + */ + isOutExtract: boolean; + /** + * Whether a node represents a function template within the library, in which + * case it should be rendered in a special scene group. + */ + isLibraryFunction: boolean; + /** + * Whether this node is faded out. Used when displaying stats. + */ + isFadedOut: boolean; + /** + * The name string used to label the node in the graph. + */ + displayName: string; + constructor(node: Node) { + this.node = node; + this.expanded = false; + this.inAnnotations = new AnnotationList(); + this.outAnnotations = new AnnotationList(); + // Params specified by layout + this.x = 0; + this.y = 0; + this.width = 0; + this.height = 0; + this.inboxWidth = 0; + this.outboxWidth = 0; + this.excluded = false; + // Params for bridge paths. + this.structural = false; + // Params for node box. + this.labelOffset = 0; + this.radius = 0; + // Params for expanded node + this.labelHeight = 0; + this.paddingTop = 0; + this.paddingLeft = 0; + this.paddingRight = 0; + this.paddingBottom = 0; + this.isInExtract = false; + this.isOutExtract = false; + this.coreBox = { width: 0, height: 0 }; + // By default, we don't fade nodes out. Default to false for safety. + this.isFadedOut = false; + // Only use the portion beyond the prefix as the display name. + if (node.name.startsWith(BENCH_PREFIX) && node.parentNode.name === tf_graph.ROOT_NAME) { + this.displayName = '标杆'; + } else { + const nameList = node.name.split('.'); + if (nameList.length > 3) { + const secondLastItem = nameList[nameList.length - 2]; + nameList.splice(nameList.length - 2, 1); + nameList.splice(2, 0, secondLastItem); + this.displayName = nameList.slice(1, nameList.length - 1).join('.'); + } else if (node.name.startsWith(BENCH_PREFIX) || node.name.startsWith(NPU_PREFIX)) { + this.displayName = node.name.slice(4); + } else { + this.displayName = node.name; + } + } + + if ( + node.type === (NodeType.META || NodeType.MULTI_COLLECTION || NodeType.API_LIST) && + (node as Metanode).associatedFunction + ) { + // Function names are suffixed with a length-8 hexadecimal string + // followed by an optional number. We remove that suffix because + // the user did not generate that suffix. That suffix merely + // serves to differentiate between functions with different + // signatures but the same name otherwise. + // Furthermore, we remove the prefix that merely ascertains this + // node as a function definition. There is no reason for the user + // to see that in the graph, as the node would already be within + // the functions scene group. + const match = this.displayName.match(nodeDisplayNameRegex); + if (match) { + // The display name had been successfully extracted. This is the most + // common scenario. + this.displayName = match[1]; + } else if (_.startsWith(this.displayName, tf_graph.FUNCTION_LIBRARY_NODE_PREFIX)) { + // The string does not match the usual pattern for how functions are + // named. Just use the entire second portion of the string as the name + // if we can successfully remove the prefix. + this.displayName = this.displayName.substring(tf_graph.FUNCTION_LIBRARY_NODE_PREFIX.length); + } + } + } + + isInCore(): boolean { + return !this.isInExtract && !this.isOutExtract && !this.isLibraryFunction; + } +} +/** + * Contains rendering information about a Metaedge from the underlying + * hierarchical graph. It may be from either a metagraph or a bridgegraph. + */ +export class RenderMetaedgeInfo { + /** + * Reference to the original underlying Metaedge from the hierarchical graph, + * if any. This will be null for the edges which connect OpNodes to their + * embeddings, for example. + */ + metaedge: Metaedge | null; + /** + * Reference to the adjoining RenderMetaedgeInfo from the parent's + * coreGraph. This is used during layout to determine the point at which this + * edge should touch the node's bounding box. This property will be null for + * edges which terminate at a node on both ends (all non-bridge edges). + */ + adjoiningMetaedge: RenderMetaedgeInfo | null; + /** + * Most of the time, a RenderMetaedgeInfo object represents a real + * edge between nodes in the underlying graph structure. But sometimes, an + * edge only exists for layout purposes. These structural edges are added + * during buildSubhierarchy() to force dagre.layout() to put bridge nodes + * at the ends of the flow. + * @see buildSubhierarchy() + */ + structural: boolean; + /** + * Weight of the edge, used by dagre when deciding how important an edge is. + * Edges with higher weight are made shorter and straighter. The default + * dagre uses is 1. + */ + weight: number; + /** + * X and Y coordinate pairs of the points in the path of the edge. + * @see tf_graph.node.subsceneAdjustPaths + */ + points: Point[]; + /** + * D3 selection of the group containing the path that displays this edge. + */ + edgeGroup: d3.Selection; + /** Id of the used as a start-marker for the edge path. */ + startMarkerId: string; + /** Id of the used as an end-marker for the edge path. */ + endMarkerId: string; + /** + * Whether this edge is faded out. Used for fading out unused edges when + * displaying run statistics. + */ + isFadedOut: boolean; + constructor(metaedge: Metaedge | null) { + this.metaedge = metaedge; + this.adjoiningMetaedge = null; + this.structural = false; + this.weight = 1; + this.isFadedOut = false; + } +} +function addInAnnotation( + node: RenderNodeInfo, + predecessor: Node, + predecessorRenderInfo: RenderNodeInfo, + edge: RenderMetaedgeInfo, + type: AnnotationType, +): void { + let annotation = new Annotation(predecessor, predecessorRenderInfo, edge, type, true); + node.inAnnotations.push(annotation); +} +function addOutAnnotation( + node: RenderNodeInfo, + successor: Node, + successorRenderInfo: RenderNodeInfo, + edge: RenderMetaedgeInfo, + type: AnnotationType, +): void { + let annotation = new Annotation(successor, successorRenderInfo, edge, type, false); + node.outAnnotations.push(annotation); +} +function setGraphDepth(graph: graphlib.Graph, depth: number): void { + _.each(graph.nodes(), (nodeName) => { + let child = graph.node(nodeName); + child.expanded = depth > 1; // set all child of depth 1 to collapsed + if (depth > 0) { + switch (child.node.type) { + case NodeType.META: + case NodeType.MULTI_COLLECTION: + case NodeType.API_LIST: + case NodeType.SERIES: + setGroupNodeDepth(child, depth - 1); + break; + default: + // Do nothing for leaf + } + } + }); +} +export class RenderGroupNodeInfo extends RenderNodeInfo { + override node: GroupNode; + /** + * The core graph is derived from the underlying node's metagraph, minus + * the extracted source-like and sink-like nodes. + */ + coreGraph: graphlib.Graph; + /** Size of the bounding box for a metanode's isolated in-extract children. */ + inExtractBox: { + width: number; + height: number; + }; + /** + * Size of the bounding box for a metanode's isolated out-extract children. + */ + outExtractBox: { + width: number; + height: number; + }; + /** Size of the bounding box for the function library. */ + libraryFunctionsBox: { + width: number; + height: number; + }; + /** Array of isolated in-extract nodes. */ + isolatedInExtract: RenderNodeInfo[]; + /** Array of isolated out-extract nodes. */ + isolatedOutExtract: RenderNodeInfo[]; + /** Array of nodes to show in the function library scene group. */ + libraryFunctionsExtract: RenderNodeInfo[]; + constructor(groupNode: GroupNode, graphOptions: tf_graph.LabeledGraphOptions) { + super(groupNode); + let metagraph = groupNode.metagraph; + let gl = metagraph.graph() as any; + this.coreGraph = createGraph(gl.name, GraphType.CORE, graphOptions); + this.inExtractBox = { width: 0, height: 0 }; + this.outExtractBox = { width: 0, height: 0 }; + this.libraryFunctionsBox = { width: 0, height: 0 }; + this.isolatedInExtract = []; + this.isolatedOutExtract = []; + this.libraryFunctionsExtract = []; + } +} +function setGroupNodeDepth(renderInfo: RenderGroupNodeInfo, depth: number): void { + if (renderInfo.coreGraph) { + setGraphDepth(renderInfo.coreGraph, depth); + } +} +/** + * Remove an edge from the graph and add annotations to both ends of the edge. + * + * @param The core graph. + * @param v Source name. + * @param w Sink name. + */ +function createShortcut(graph: graphlib.Graph, v: string, w: string): void { + let src = graph.node(v) as any; + let sink = graph.node(w) as any; + let edge = graph.edge(v, w) as any; + // If either of the nodes is explicitly included in the main graph and + // both nodes are in the main graph then do not create the shortcut + // and instead keep the real edge. + const isInclude = src.node.include === InclusionType.INCLUDE || sink.node.include === InclusionType.INCLUDE; + const isExclude = src.node.include === InclusionType.EXCLUDE || sink.node.include === InclusionType.EXCLUDE; + if (isInclude && !isExclude) { + return; + } + + // Add each annotation. + addOutAnnotation(src, sink.node, sink, edge, AnnotationType.SHORTCUT); + addInAnnotation(sink, src.node, src, edge, AnnotationType.SHORTCUT); + // Remove the edge from the core graph. + graph.removeEdge(v, w); +} +/** + * Remove edges from a node, and set its isOutExtract property to true, + * and remove the node and move it to isolatedOutExtract. + * + * If detachAllEdgesForHighDegree or forceDetach is true, extract all of its + * edges. Otherwise, only extract all in-edges. + */ +function makeOutExtract(renderNode: RenderGroupNodeInfo, n: string, forceDetach?: boolean): void { + let graph = renderNode.coreGraph; + let child = graph.node(n) as any; + child.isOutExtract = true; + _.each(graph.predecessors(n), (p, index) => { + createShortcut(graph, p, n); + }); + if (PARAMS.detachAllEdgesForHighDegree || forceDetach) { + _.each(graph.successors(n), (s, index) => { + createShortcut(graph, n, s); + }); + } + // Remove the node from the core graph if it no longer has neighbors. + if (graph.neighbors(n)?.length === 0) { + child.node.include = InclusionType.EXCLUDE; + renderNode.isolatedOutExtract.push(child); + graph.removeNode(n); + } +} +/** + * Remove edges from a node, set its isInExtract property to true, + * and remove the node and move it to isolatedInExtract. + * + * If detachAllEdgesForHighDegree or forceDetach is true, extract all of its + * edges. Otherwise, only remove all out-edges. + */ +export function makeInExtract(renderNode: RenderGroupNodeInfo, n: string, forceDetach?: boolean): void { + let graph = renderNode.coreGraph; + let child = graph.node(n) as any; + child.isInExtract = true; + _.each(graph.successors(n), (s, index) => { + createShortcut(graph, n, s); + }); + if (PARAMS.detachAllEdgesForHighDegree || forceDetach) { + _.each(graph.predecessors(n), (p, index) => { + createShortcut(graph, p, n); + }); + } + // Remove the node from the core graph if it no longer has neighbors. + if (graph.neighbors(n)?.length === 0) { + child.node.include = InclusionType.EXCLUDE; + renderNode.isolatedInExtract.push(child); + graph.removeNode(n); + } +} +/** + * Check whether the node's type is a member of the given list of types. + * + * @param node Node. + * @param types List of type to match. + */ +function hasTypeIn(node: Node, types: string[]): boolean { + if (node.type === NodeType.OP) { + for (let i = 0; i < types.length; i++) { + if ((node).op === types[i]) { + return true; + } + } + } else if (node.type === NodeType.META) { + let rootOpNode = (node).getRootOp(); + if (rootOpNode) { + for (let i = 0; i < types.length; i++) { + if (rootOpNode.op === types[i]) { + return true; + } + } + } + } + return false; +} +/** + * Given an integer, picks a hue that is far apart from other colors. + * The formula for picking color that avoid collision is: + * hue = (color range * golden ratio * index) % color range + */ +export function mapIndexToHue(id: number): number { + let GOLDEN_RATIO = 1.61803398875; + // Hue of 0 is reserved for the gray nodes. + let MIN_HUE = 1; + let MAX_HUE = 359; + let COLOR_RANGE = MAX_HUE - MIN_HUE; + return MIN_HUE + ((COLOR_RANGE * GOLDEN_RATIO * id) % COLOR_RANGE); +} +/** + * Remove edges and add to annotation instead. + * + * For root node, consider predefined types for source and sink. + * We do not extract predefined type from non-root so that Variables and the + * sgd node (op type = 'NoOp') do not get extract from inside own group. + * + * The order of extraction is important here as swapping the order can totally + * screw up the graph layout. + * + * @param {Render.Node} renderNode Node to manipulate. + * nodes from the main graph. If false, only exclude predefined nodes. + */ +/** + * Expands nodes in the graph until the desired node is visible. + * + * @param scene The scene polymer component. + * @param renderHierarchy The render hierarchy. + * @param tensorName The name of a tensor. + * @return A string that is the name of the node representing the given tensor. + * Note that the original tensor name might differ from this returned node + * name. Specifically, for instance, the tensor name usually ends with an + * output slot index (such as :0), while the node name lacks that suffix. + */ +export function expandUntilNodeIsShown(scene, renderHierarchy: RenderGraphInfo, tensorName: string): string { + const splitTensorName = tensorName.split('/'); + // Graph names do not take into account the output slot. Strip it. + const lastNodeNameMatch = splitTensorName[splitTensorName.length - 1].match(/(?.*)\w+/); + if (lastNodeNameMatch?.length === 2) { + splitTensorName[splitTensorName.length - 1] = lastNodeNameMatch?.[1]; + } + let nodeName = splitTensorName[0]; + let renderNode = renderHierarchy.getRenderNodeByName(nodeName); + for (let i = 1; i < splitTensorName.length; i++) { + // Op nodes are not expandable. + if (renderNode.node.type === tf_graph.NodeType.OP) { + break; + } + renderHierarchy.buildSubhierarchy(nodeName); + renderNode.expanded = true; + scene.setNodeExpanded(renderNode); + nodeName += `/${splitTensorName[i]}`; + renderNode = renderHierarchy.getRenderNodeByName(nodeName); + } + return renderNode.node.name; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts new file mode 100644 index 000000000..4645cfb75 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts @@ -0,0 +1,602 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as d3 from 'd3'; +import * as PolymerDom from '../polymer/dom'; +import { Class as _Class, selectChild as _selectChild, SVG_NAMESPACE } from './common'; +import { NodeType, OpNode } from './graph'; +import * as layout from './layout'; +import * as render from './render'; + +export const selectChild = _selectChild; +export const Class = _Class; + +/** + * The dimensions of the minimap including padding and margin. + */ +const MINIMAP_BOX_WIDTH = 320; +const MINIMAP_BOX_HEIGHT = 150; +/** + * A health pill encapsulates an overview of tensor element values. The value + * field is a list of 12 numbers that shed light on the status of the tensor. + * Visualized in health pills are the 3rd through 8th (inclusive) numbers of + * health pill values. Those 6 numbers are counts of tensor elements that fall + * under -Inf, negative, 0, positive, +Inf, NaN (in that order). + * + * Please keep this interface consistent with HealthPillDatum within + * backend.ts. + */ +export interface HealthPill { + device_name: string; + node_name: string; + output_slot: number; + dtype: string; + shape: number[]; + value: number[]; + wall_time: number; + step: number; +} +interface HealthPillNumericStats { + min: number; + max: number; + mean: number; + stddev: number; +} +/** + * Encapsulates how to render a single entry in a health pill. Each entry + * corresponds to a category of tensor element values. + */ +export interface HealthPillEntry { + background_color: string; + label: string; +} +export const healthPillEntries: HealthPillEntry[] = [ + { + background_color: '#CC2F2C', + label: 'NaN', + }, + { + background_color: '#FF8D00', + label: '-∞', + }, + { + background_color: '#EAEAEA', + label: '-', + }, + { + background_color: '#A5A5A5', + label: '0', + }, + { + background_color: '#262626', + label: '+', + }, + { + background_color: '#003ED4', + label: '+∞', + }, +]; +/** + * Helper method for fitting the graph in the svg view. + * + * @param svg The main svg. + * @param zoomG The svg group used for panning and zooming. + * @param d3zoom The zoom behavior. + * @param callback Called when the fitting is done. + */ +export function fit(svg, zoomG, d3zoom, callback): void { + let svgRect = svg.getBoundingClientRect(); + let sceneSize: DOMRect | null = null; + try { + sceneSize = zoomG.getBBox(); + if (sceneSize?.width === 0) { + // There is no scene anymore. We have been detached from the dom. + return; + } + } catch (e) { + // Firefox produced NS_ERROR_FAILURE if we have been + // detached from the dom. + return; + } + let scale = 0.9 * Math.min(svgRect.width / (sceneSize?.width ?? 1), svgRect.height / (sceneSize?.height ?? 1), 2); + let params = layout.PARAMS.graph; + const transform = d3.zoomIdentity.scale(scale).translate(params.padding.paddingLeft, params.padding.paddingTop); + d3.select(svg) + .transition() + .duration(500) + .call(d3zoom.transform, transform) + .on('end.fitted', () => { + // Remove the listener for the zoomend event, + // so we don't get called at the end of regular zoom events, + // just those that fit the graph to screen. + d3zoom.on('end.fitted', null); + callback(); + }); +} +/** + * Helper method for panning the graph to center on the provided node, + * if the node is currently off-screen. + * + * @param nodeName The node to center the graph on + * @param svg The root SVG element for the graph + * @param zoomG The svg group used for panning and zooming. + * @param d3zoom The zoom behavior. + * @return True if the graph had to be panned to display the + * provided node. + */ +export function panToNode(nodeName: string, svg, zoomG, d3zoom): boolean { + const node = d3.select(svg).select(`[data-name="${nodeName}"]`).node(); + if (!node) { + console.warn(`panToNode() failed for node name "${nodeName}"`); + return false; + } + // Check if the selected node is off-screen in either + // X or Y dimension in either direction. + let nodeBox = node.getBBox(); + let nodeCtm = node.getScreenCTM(); + let pointTL = svg.createSVGPoint(); + let pointBR = svg.createSVGPoint(); + pointTL.x = nodeBox.x; + pointTL.y = nodeBox.y; + pointBR.x = nodeBox.x + nodeBox.width; + pointBR.y = nodeBox.y + nodeBox.height; + pointTL = pointTL.matrixTransform(nodeCtm); + pointBR = pointBR.matrixTransform(nodeCtm); + let isOutsideOfBounds = (start, end, lowerBound, upperBound): boolean => { + // Return if even a part of the interval is out of bounds. + return !(start > lowerBound && end < upperBound); + }; + let svgRect = svg.getBoundingClientRect(); + // Subtract to make sure that the node is not hidden behind the minimap. + const horizontalBound = svgRect.left + svgRect.width - MINIMAP_BOX_WIDTH; + const verticalBound = svgRect.top + svgRect.height - MINIMAP_BOX_HEIGHT; + if ( + isOutsideOfBounds(pointTL.x, pointBR.x, svgRect.left, horizontalBound) || + isOutsideOfBounds(pointTL.y, pointBR.y, svgRect.top, verticalBound) + ) { + // Determine the amount to translate the graph in both X and Y dimensions in + // order to center the selected node. This takes into account the position + // of the node, the size of the svg scene, the amount the scene has been + // scaled by through zooming, and any previous transforms already performed + // by this logic. + let centerX = (pointTL.x + pointBR.x) / 2; + let centerY = (pointTL.y + pointBR.y) / 2; + let dx = svgRect.left + svgRect.width / 2 - centerX; + let dy = svgRect.top + svgRect.height / 2 - centerY; + + // We translate by this amount. We divide the X and Y translations by the + // scale to undo how translateBy scales the translations (in d3 v4). + const svgTransform = d3.zoomTransform(svg); + d3.select(svg) + .transition() + .duration(500) + .call(d3zoom.translateBy, dx / svgTransform.k, dy / svgTransform.k); + return true; + } + return false; +} +/** + * Given a scene's svg group, set g.in-extract, g.coreGraph, g.out-extract svg + * groups' position relative to the scene. + * + * @param sceneGroup + * @param renderNode render node of a metanode or series node. + */ +export function position(sceneGroup, renderNode: render.RenderGroupNodeInfo): void { + // Translate scenes down by the label height so that when showing graphs in + // expanded metanodes, the graphs are below the labels. Do not shift them + // down for series nodes as series nodes don't have labels inside of their + // bounding boxes. + let yTranslate = renderNode.node.type === NodeType.SERIES ? 0 : layout.PARAMS.subscene.meta.labelHeight; + // core + translate(selectChild(sceneGroup, 'g', Class.Scene.CORE), 0, yTranslate); + // in-extract + let hasInExtract = renderNode.isolatedInExtract.length > 0; + let hasOutExtract = renderNode.isolatedOutExtract.length > 0; + let hasLibraryFunctions = renderNode.libraryFunctionsExtract.length > 0; + let offset = layout.PARAMS.subscene.meta.extractXOffset; + let auxWidth = 0; + if (hasInExtract) { + auxWidth += renderNode.outExtractBox.width; + } + if (hasOutExtract) { + auxWidth += renderNode.outExtractBox.width; + } + if (hasInExtract) { + let inExtractX = renderNode.coreBox.width; + if (auxWidth < layout.MIN_AUX_WIDTH) { + inExtractX = inExtractX - layout.MIN_AUX_WIDTH + renderNode.inExtractBox.width / 2; + } else { + inExtractX = + inExtractX - renderNode.inExtractBox.width / 2 - renderNode.outExtractBox.width - (hasOutExtract ? offset : 0); + } + inExtractX = inExtractX - renderNode.libraryFunctionsBox.width - (hasLibraryFunctions ? offset : 0); + translate(selectChild(sceneGroup, 'g', Class.Scene.INEXTRACT), inExtractX, yTranslate); + } + // out-extract + if (hasOutExtract) { + let outExtractX = renderNode.coreBox.width; + if (auxWidth < layout.MIN_AUX_WIDTH) { + outExtractX = outExtractX - layout.MIN_AUX_WIDTH + renderNode.outExtractBox.width / 2; + } else { + outExtractX -= renderNode.outExtractBox.width / 2; + } + outExtractX = outExtractX - renderNode.libraryFunctionsBox.width - (hasLibraryFunctions ? offset : 0); + translate(selectChild(sceneGroup, 'g', Class.Scene.OUTEXTRACT), outExtractX, yTranslate); + } + if (hasLibraryFunctions) { + let libraryFunctionsExtractX = renderNode.coreBox.width - renderNode.libraryFunctionsBox.width / 2; + translate(selectChild(sceneGroup, 'g', Class.Scene.FUNCTION_LIBRARY), libraryFunctionsExtractX, yTranslate); + } +} +/** Adds a click listener to a group that fires a graph-select event */ +export function addGraphClickListener(graphGroup, sceneElement): void { + d3.select(graphGroup).on('click', () => { + sceneElement.fire('graph-select'); + }); +} +/** Helper for adding transform: translate(x0, y0) */ +export function translate(selection, x0: number, y0: number): void { + // If it is already placed on the screen, make it a transition. + let selectionTemp = selection; + if (selection.attr('transform') != null) { + selectionTemp = selection.transition('position'); + } + selectionTemp.attr('transform', `translate(${x0},${y0})`); +} +/** + * Helper for setting position of a svg rect + * @param rect A d3 selection of rect(s) to set position of. + * @param cx Center x. + * @param cy Center x. + * @param width Width to set. + * @param height Height to set. + */ +export function positionRect(rect, cx: number, cy: number, width: number, height: number): void { + rect + .transition() + .attr('x', cx - width / 2) + .attr('y', cy - height / 2) + .attr('width', width) + .attr('height', height); +} +/** + * Positions a triangle and sizes it. + * @param polygon polygon to set position of. + * @param cx Center x. + * @param cy Center y. + * @param width Width of bounding box for triangle. + * @param height Height of bounding box for triangle. + */ +export function positionTriangle(polygon, cx, cy, width, height): void { + const halfHeight = height / 2; + const halfWidth = width / 2; + const points = [ + [cx, cy - halfHeight], + [cx + halfWidth, cy + halfHeight], + [cx - halfWidth, cy + halfHeight], + ]; + polygon.transition().attr('points', points.map((point) => point.join(',')).join(' ')); +} +/** + * Helper for setting position of a svg expand/collapse button + * @param button container group + * @param renderNode the render node of the group node to position + * the button on. + */ +export function positionButton(button, renderNode: render.RenderNodeInfo): void { + let cx = layout.computeCXPositionOfNodeShape(renderNode); + // Position the button in the top-right corner of the group node, + // with space given the draw the button inside of the corner. + let width = renderNode.expanded ? renderNode.width : renderNode.coreBox.width; + let height = renderNode.expanded ? renderNode.height : renderNode.coreBox.height; + let x = cx + width / 2 - 6; + let y = renderNode.y - height / 2 + 6; + + // For unexpanded series nodes, the button has special placement due + // to the unique visuals of this group node. + if (renderNode.node.type === NodeType.SERIES && !renderNode.expanded) { + x += 10; + y -= 2; + } + let translateStr = `translate(${x},${y})`; + button.selectAll('path').transition().attr('transform', translateStr); + button.select('circle').transition().attr({ cx: x, cy: y, r: layout.PARAMS.nodeSize.meta.expandButtonRadius }); +} +/** + * Helper for setting position of a svg ellipse + * @param ellipse ellipse to set position of. + * @param cx Center x. + * @param cy Center x. + * @param width Width to set. + * @param height Height to set. + */ +export function positionEllipse(ellipse, cx: number, cy: number, width: number, height: number): void { + ellipse + .transition() + .attr('cx', cx) + .attr('cy', cy) + .attr('rx', width / 2) + .attr('ry', height / 2); +} +/** + * @param {number} stat A stat for a health pill (such as mean or variance). + * @param {boolean} shouldRoundOnesDigit Whether to round this number to the + * ones digit. Useful for say int, uint, and bool output types. + * @return {string} A human-friendly string representation of that stat. + */ +export function humanizeHealthPillStat(stat: number, shouldRoundOnesDigit: boolean): string { + if (shouldRoundOnesDigit) { + return stat.toFixed(0); + } + if (Math.abs(stat) >= 1) { + return stat.toFixed(1); + } + return stat.toExponential(1); +} +/** + * Get text content describing a health pill. + */ +function _getHealthPillTextContent( + healthPill: HealthPill, + totalCount: number, + elementsBreakdown: number[], + numericStats: HealthPillNumericStats, +): string { + let text = `Device: ${healthPill.device_name}\n`; + text += `dtype: ${healthPill.dtype}\n`; + let shapeStr = '(scalar)'; + if (healthPill.shape.length > 0) { + shapeStr = `(${healthPill.shape.join(',')})`; + } + text += `\nshape: ${shapeStr}\n\n`; + text += `#(elements): ${totalCount}\n`; + + const breakdownItems: string[] = []; + for (let i = 0; i < elementsBreakdown.length; i++) { + if (elementsBreakdown[i] > 0) { + breakdownItems.push(`#(${healthPillEntries[i].label}): ${elementsBreakdown[i]}`); + } + } + text += `${breakdownItems.join(', ')}\n\n`; + // In some cases (e.g., size-0 tensors; all elements are nan or inf) the + // min/max and mean/stddev stats are meaningless. + if (numericStats.max >= numericStats.min) { + text += `min: ${numericStats.min}, max: ${numericStats.max}\n`; + text += `mean: ${numericStats.mean}, stddev: ${numericStats.stddev}`; + } + return text; +} +/** + * Renders a health pill for an op atop a node. + * nodeGroupElement: The SVG element in which to render. + * healthPill: A list of backend.HealthPill objects. + * nodeInfo: Info on the associated node. + * healthPillId: A unique numeric ID assigned to this health pill. + * healthPillWidth: Optional width of the health pill. + * healthPillHeight: Optional height of the health pill. + * healthPillYOffset: Optional y-offset of the health pill (that is, the + * color-coded region). + * textOffset: Optional value for the x-offset of the top text label + * relative to the left edge of the health pill. If not provided, will + * default to `healthPillWidth / 2`. + */ +export function addHealthPill( + nodeGroupElement: SVGElement, + healthPill: HealthPill | null, + nodeInfo: render.RenderNodeInfo, + healthPillId: number, + healthPillWidth = 60, + healthPillHeight = 10, + healthPillYOffset = 0, + textXOffset?: number, +): void { + let healthPillWidthTemp = healthPillWidth; + let healthPillHeightTemp = healthPillHeight; + // Check if text already exists at location. + d3.select(nodeGroupElement.parentNode as any) + .selectAll('.health-pill') + .remove(); + if (!healthPill) { + return; + } + const lastHealthPillData = healthPill.value; + // For now, we only visualize the 6 values that summarize counts of tensor + // elements of various categories: -Inf, negative, 0, positive, Inf, and NaN. + const lastHealthPillElementsBreakdown = lastHealthPillData.slice(2, 8); + const nanCount = lastHealthPillElementsBreakdown[0]; + const negInfCount = lastHealthPillElementsBreakdown[1]; + const posInfCount = lastHealthPillElementsBreakdown[5]; + let totalCount = lastHealthPillData[1]; + const numericStats: HealthPillNumericStats = { + min: lastHealthPillData[8], + max: lastHealthPillData[9], + mean: lastHealthPillData[10], + stddev: Math.sqrt(lastHealthPillData[11]), + }; + + if (healthPillWidthTemp == null) { + healthPillWidthTemp = 60; + } + if (healthPillHeightTemp == null) { + healthPillHeightTemp = 10; + } + if (healthPillYOffset == null) { + healthPillYOffset = 0; + } + if (nodeInfo != null && nodeInfo.node.type === NodeType.OP) { + // Use a smaller health pill for op nodes (rendered as smaller ellipses). + healthPillWidthTemp /= 2; + healthPillHeightTemp /= 2; + } + let healthPillGroup = document.createElementNS(SVG_NAMESPACE, 'g'); + healthPillGroup.classList.add('health-pill'); + // Define the gradient for the health pill. + let healthPillDefs = document.createElementNS(SVG_NAMESPACE, 'defs'); + healthPillGroup.appendChild(healthPillDefs); + let healthPillGradient = document.createElementNS(SVG_NAMESPACE, 'linearGradient'); + // Every element in a web page must have a unique ID. + const healthPillGradientId = `health-pill-gradient-${healthPillId}`; + healthPillGradient.setAttribute('id', healthPillGradientId); + let cumulativeCount = 0; + let previousOffset = '0%'; + for (let i = 0; i < lastHealthPillElementsBreakdown.length; i++) { + if (!lastHealthPillElementsBreakdown[i]) { + // Exclude empty categories. + continue; + } + cumulativeCount += lastHealthPillElementsBreakdown[i]; + // Create a color interval using 2 stop elements. + let stopElement0 = document.createElementNS(SVG_NAMESPACE, 'stop'); + stopElement0.setAttribute('offset', previousOffset); + stopElement0.setAttribute('stop-color', healthPillEntries[i].background_color); + healthPillGradient.appendChild(stopElement0); + let stopElement1 = document.createElementNS(SVG_NAMESPACE, 'stop'); + let percent = `${(cumulativeCount * 100) / totalCount}%`; + stopElement1.setAttribute('offset', percent); + stopElement1.setAttribute('stop-color', healthPillEntries[i].background_color); + healthPillGradient.appendChild(stopElement1); + previousOffset = percent; + } + healthPillDefs.appendChild(healthPillGradient); + // Create the rectangle for the health pill. + let rect = document.createElementNS(SVG_NAMESPACE, 'rect'); + rect.setAttribute('fill', `url(#${healthPillGradientId})`); + rect.setAttribute('width', String(healthPillWidthTemp)); + rect.setAttribute('height', String(healthPillHeightTemp)); + rect.setAttribute('y', String(healthPillYOffset)); + healthPillGroup.appendChild(rect); + // Show a title with specific counts on hover. + let titleSvg = document.createElementNS(SVG_NAMESPACE, 'title'); + titleSvg.textContent = _getHealthPillTextContent( + healthPill, + totalCount, + lastHealthPillElementsBreakdown, + numericStats, + ); + healthPillGroup.appendChild(titleSvg); + // Center this health pill just right above the node for the op. + let shouldRoundOnesDigit = false; + + function calculateHealthPillPosition( + nodeInfo, + healthPillWidth, + healthPillHeight, + ): { healthPillX: number; healthPillY: number } { + let healthPillX = nodeInfo.x - healthPillWidth / 2; + let healthPillY = nodeInfo.y - healthPillHeight - nodeInfo.height / 2 - 2; + + if (nodeInfo.labelOffset < 0) { + healthPillY += nodeInfo.labelOffset; + } + + return { healthPillX, healthPillY }; + } + + function hasNonInfOrNaNValue(lastHealthPillElementsBreakdown): any { + return ( + lastHealthPillElementsBreakdown[2] || lastHealthPillElementsBreakdown[3] || lastHealthPillElementsBreakdown[4] + ); + } + + function isIntegerOutputType(attributes): boolean { + if (!attributes?.length) { + return false; + } + + for (let i = 0; i < attributes.length; i++) { + if (attributes[i].key === 'T') { + let outputType = attributes[i].value.type; + return outputType && /^DT_(?BOOL|INT|UINT)/.test(outputType); + } + } + + return false; + } + + // 主逻辑 + if (nodeInfo != null) { + let { healthPillX, healthPillY } = calculateHealthPillPosition(nodeInfo, healthPillWidthTemp, healthPillHeightTemp); + healthPillGroup.setAttribute('transform', `translate(${healthPillX}, ${healthPillY})`); + + if (hasNonInfOrNaNValue(lastHealthPillElementsBreakdown)) { + let node = nodeInfo.node as OpNode; + shouldRoundOnesDigit = isIntegerOutputType(node.attr); + } + } + let statsSvg = document.createElementNS(SVG_NAMESPACE, 'text'); + if (Number.isFinite(numericStats.min) && Number.isFinite(numericStats.max)) { + const minString = humanizeHealthPillStat(numericStats.min, shouldRoundOnesDigit); + const maxString = humanizeHealthPillStat(numericStats.max, shouldRoundOnesDigit); + if (totalCount > 1) { + statsSvg.textContent = `${minString} ~ ${maxString}`; + } else { + statsSvg.textContent = minString; + } + if (nanCount > 0 || negInfCount > 0 || posInfCount > 0) { + statsSvg.textContent += ' ('; + const badValueStrings: string[] = []; + if (nanCount > 0) { + badValueStrings.push(`NaN×${nanCount}`); + } + if (negInfCount > 0) { + badValueStrings.push(`-∞×${negInfCount}`); + } + if (posInfCount > 0) { + badValueStrings.push(`+∞×${posInfCount}`); + } + statsSvg.textContent += `${badValueStrings.join('; ')} )`; + } + } else { + statsSvg.textContent = '(No finite elements)'; + } + statsSvg.classList.add('health-pill-stats'); + if (textXOffset == null) { + textXOffset = healthPillWidthTemp / 2; + } + statsSvg.setAttribute('x', String(textXOffset)); + statsSvg.setAttribute('y', String(healthPillYOffset - 2)); + healthPillGroup.appendChild(statsSvg); + (PolymerDom.dom(nodeGroupElement.parentNode) as any).appendChild(healthPillGroup); +} + +/** + * Adds health pills (which visualize tensor summaries) to a graph group. + * @param svgRoot The root SVG element of the graph to add heath pills to. + * @param nodeNamesToHealthPills An object mapping node name to health pill. + * @param colors A list of colors to use. + */ +export function addHealthPills( + svgRoot: SVGElement, + nodeNamesToHealthPills: { + [key: string]: HealthPill[]; + }, + healthPillStepIndex: number, +): void { + if (!nodeNamesToHealthPills) { + // No health pill information available. + return; + } + // We generate a unique ID for each health pill because the ID of each element + // in a web page must be unique, and each health pill generates a gradient + // that its code later refers to. + let healthPillId = 1; + let svgRootSelection = d3.select(svgRoot); + svgRootSelection.selectAll('g.nodeshape').each(function (nodeInfo: render.RenderNodeInfo) { + // Only show health pill data for this node if it is available. + const healthPills = nodeNamesToHealthPills[nodeInfo.node.name]; + const healthPill = healthPills ? healthPills[healthPillStepIndex] : null; + addHealthPill(this as SVGElement, healthPill, nodeInfo, healthPillId++); + }); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts new file mode 100644 index 000000000..de28c4c47 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts @@ -0,0 +1,262 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { computed, customElement, property } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import { DarkModeMixin } from '../polymer/dark_mode_mixin'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import '../tf_dashboard_common/tensorboard-color'; +import { MetanodeColors, OpNodeColors, SeriesNodeColors } from './render'; + +export enum GraphIconType { + CONST = 'CONST', + META = 'META', + OP = 'OP', + SERIES = 'SERIES', + SUMMARY = 'SUMMARY', + MULTI_COLLECTION = 'MULTI_COLLECTION', + API_LIST = 'API_LIST', +} +@customElement('tf-graph-icon') +class TfGraphIcon extends LegacyElementMixin(DarkModeMixin(PolymerElement)) { + static readonly template = html` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + `; + + @property({ type: String }) + type: string; + + @property({ type: Boolean }) + vertical: boolean = false; + + @property({ type: String }) + fillOverride: string | null = null; + + @property({ type: String }) + strokeOverride: string | null = null; + + @property({ type: Number }) + height: number = 20; + + @property({ type: Boolean }) + faded: boolean = false; + + getSvgDefinableElement(): HTMLElement { + return this.$.svgDefs as HTMLElement; + } + + @computed('type', 'fillOverride') + get _fill(): string { + let type = this.type; + let fillOverride = this.fillOverride; + if (fillOverride != null) return fillOverride; + switch (type) { + case GraphIconType.META: + return MetanodeColors.DEFAULT_FILL; + case GraphIconType.SERIES: + return SeriesNodeColors.DEFAULT_FILL; + default: + return OpNodeColors.DEFAULT_FILL; + } + } + + @computed('type', 'strokeOverride') + get _stroke(): string { + let type = this.type; + let strokeOverride = this.strokeOverride; + if (strokeOverride != null) return strokeOverride; + switch (type) { + case GraphIconType.META: + return MetanodeColors.DEFAULT_STROKE; + case GraphIconType.SERIES: + return SeriesNodeColors.DEFAULT_STROKE; + default: + return OpNodeColors.DEFAULT_STROKE; + } + } + /** + * Test whether the specified node's type, or the literal type string, + * match a particular other type. + */ + _isType(type: GraphIconType, targetType: GraphIconType): boolean { + return type === targetType; + } + _fadedClass(faded: boolean, shape: string): string { + return `${faded ? 'faded-' + shape : ''}`; + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-scene.ts new file mode 100644 index 000000000..190cc9ed9 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-scene.ts @@ -0,0 +1,36 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as d3 from 'd3'; +import { Annotation, RenderNodeInfo } from './render'; + +type Selection = d3.Selection; +// This technically extends Polymer.Component whose constructor is not +// accessible. +export abstract class TfGraphScene extends HTMLElement { + maxMetanodeLabelLength: number; + maxMetanodeLabelLengthLargeFont: number; + maxMetanodeLabelLengthFontSize: number; + abstract fire(eventName: string, daat: any): void; + abstract addNodeGroup(name: string, selection: Selection): void; + abstract removeNodeGroup(name: string): void; + abstract removeAnnotationGroup(annotation: Annotation, renderNode: RenderNodeInfo): void; + abstract isNodeExpanded(node: RenderNodeInfo): boolean; + abstract isNodeHighlighted(nodeName: string): boolean; + abstract isNodeSelected(nodeName: string): boolean; + abstract isNodeLinked(nodeName: string): boolean; + abstract getAnnotationGroupsIndex(name: string): Selection; + abstract getGraphSvgRoot(): SVGElement; + abstract getContextMenu(): HTMLElement; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-node-icon.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-node-icon.ts new file mode 100644 index 000000000..d62dc4303 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-node-icon.ts @@ -0,0 +1,180 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { customElement, property } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import * as tf_graph from '../tf_graph_common/graph'; +import * as tf_graph_scene_node from '../tf_graph_common/node'; +import './tf-graph-icon'; +import * as tf_graph_icon from './tf-graph-icon'; + +@customElement('tf-node-icon') +class TfNodeIcon extends LegacyElementMixin(PolymerElement) { + static readonly template = html` + + + `; + + /** + * Node to represent with an icon. Optional, but if specified, its + * properties override those defined in the type, vertical, const and + * summary properties. + * This property is a tf.graph.Node. + */ + @property({ + type: Object, + }) + node: object | null = null; + + /** + * Render node information associated with this node. Optional. If + * specified, this is only used when computing the fill of the icon + * element. + * This property is a tf.graph.render.RenderNodeInfo. + */ + @property({ + type: Object, + }) + renderInfo: object | null = null; + + /** Type of node to draw (ignored if node is set). */ + @property({ + type: String, + }) + type: string | null = null; + + /** Direction for series (ignored for other types). */ + @property({ + type: Boolean, + }) + vertical: boolean = false; + + /** Whether the op is Const (ignored for non-ops). */ + @property({ + type: Boolean, + }) + const: boolean = false; + + /** Whether the op is a Summary (ignored for non-ops). */ + @property({ + type: Boolean, + }) + summary: boolean = false; + + /** + * Fill for the icon, optional. If fill is specified and node is not + * specified, then this value will override the default for the + * element. However, if node is specified, this value will be ignored. + */ + @property({ + type: String, + }) + fill: string | null = null; + + /** Height of the SVG element in pixels, used for scaling. */ + @property({ + type: Number, + }) + height: number = 20; + + @property({ + type: String, + computed: '_computeFillOverride(node, renderInfo, fill)', + observer: '_onFillOverrideChanged', + }) + _fillOverride: string; + + /** + * Returns fill value based on node and configuration. If any of those + * configurations or node value missing, it returns `fill` property. + * Note that if this evaluates to null, it will be chosen based on + * the type of the node. + */ + _computeFillOverride(inputNode, inputRenderInfo, inputFill): string | null { + if (inputNode && inputRenderInfo) { + return tf_graph_scene_node.getFillForNode(inputRenderInfo); + } + return inputFill; + } + + _getStrokeOverride(fillOverride): string | null { + return fillOverride ? tf_graph_scene_node.getStrokeForFill(fillOverride) : null; + } + + /** + * Returns graph-icon type from input, type, and summary. + */ + _getType(inputNode, isSummary, isConst, inputType): string { + const { GraphIconType } = tf_graph_icon; + if (inputNode) { + switch (inputNode.type) { + case tf_graph.NodeType.OP: { + const opName = inputNode.op; + if (typeof opName !== 'string') return GraphIconType.OP; + if (opName === 'Const' || isConst) return GraphIconType.CONST; + if (opName.endsWith('Summary') || isSummary) { + return GraphIconType.SUMMARY; + } + return GraphIconType.OP; + } + case tf_graph.NodeType.META: + return GraphIconType.META; + case tf_graph.NodeType.SERIES: + return GraphIconType.SERIES; + default: + } + } + return inputType; + } + + /** + * Test whether the specified node should be represented as a vertical + * series. Defaults to the value of the vertical property if node is + * not specified. + */ + _isVertical(inputNode, inputVertical): boolean { + if (inputNode) { + return inputNode.hasNonControlEdges; + } + return !!inputVertical; + } + + _getFaded(itemRenderInfo): any { + return itemRenderInfo?.isFadedOut; + } + + _onFillOverrideChanged(newFill, oldFill): void { + const { node, renderInfo } = this; + if (newFill !== oldFill) { + tf_graph_scene_node.removeGradientDefinitions((this.$.icon as any).getSvgDefinableElement()); + } + if (node && renderInfo) { + tf_graph_scene_node.getFillForNode(renderInfo as any); + } + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/util.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/util.ts new file mode 100644 index 000000000..50789af26 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/util.ts @@ -0,0 +1,370 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the 'License'); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an 'AS IS' BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +/** + * @fileoverview Utility functions for the tensorflow graph visualizer. + */ +import * as _ from 'lodash'; +import { + GraphDebugActionEventId, + GraphDebugTimingEventId, + GRAPH_DEBUG_ACTION_EVENT_CATEGORY, + GRAPH_DEBUG_TIMING_EVENT_CATEGORY, +} from '../tb_debug/types'; +import { ProgressTracker } from './common'; + +const ASYNC_TASK_DELAY = 20; + +interface DebugTimingEvent { + timingId: GraphDebugTimingEventId; + // An associated duration in milliseconds for a timing event. + eventValue: number; +} + +interface DebugActionEvent { + actionId: GraphDebugActionEventId; + eventLabel?: string; +} + +export type DebugEvent = DebugTimingEvent | DebugActionEvent; + +/** + * Measure and log a synchronous task. + */ +export function time(msg: string, task: () => T, debugEventId?: GraphDebugTimingEventId): T { + let start = Date.now(); + let result = task(); + const durationInMs = Date.now() - start; + /* tslint:disable */ + console.log(msg, ':', durationInMs, 'ms'); + return result; +} +/** + * Creates a tracker that sets the progress property of the + * provided polymer component. The provided component must have + * a property called 'progress' that is not read-only. The progress + * property is an object with a numerical 'value' property and a + * string 'msg' property. + */ +export function getTracker(polymerComponent: any): ProgressTracker { + return { + setMessage: function (msg): void { + polymerComponent.set('progress', { + value: polymerComponent.progress.value, + msg: msg, + }); + }, + updateProgress: function (value): void { + polymerComponent.set('progress', { + value: polymerComponent.progress.value + value, + msg: polymerComponent.progress.msg, + }); + }, + reportError: function (msg: string, err): void { + // Log the stack trace in the console. + console.error(err.stack); + // And send a user-friendly message to the UI. + polymerComponent.set('progress', { + value: polymerComponent.progress.value, + msg: msg, + error: true, + }); + }, + }; +} +/** + * Creates a tracker for a subtask given the parent tracker, the total + * progress + * of the subtask and the subtask message. The parent task should pass a + * subtracker to its subtasks. The subtask reports its own progress which + * becomes relative to the main task. + */ +export function getSubtaskTracker( + parentTracker: ProgressTracker, + impactOnTotalProgress: number, + subtaskMsg: string, +): ProgressTracker { + return { + setMessage: function (progressMsg): void { + // The parent should show a concatenation of its message along with + // its subtask tracker message. + parentTracker.setMessage(`${subtaskMsg}: ${progressMsg}`); + }, + updateProgress: function (incrementValue): void { + // Update the parent progress relative to the child progress. + // For example, if the sub-task progresses by 30%, and the impact on the + // total progress is 50%, then the task progresses by 30% * 50% = 15%. + parentTracker.updateProgress((incrementValue * impactOnTotalProgress) / 100); + }, + reportError: function (msg: string, err: Error): void { + // The parent should show a concatenation of its message along with + // its subtask error message. + parentTracker.reportError(`${subtaskMsg}: ${msg}`, err); + }, + }; +} +/** + * Runs a synchronous expensive task and return the result. + * Please use runAsyncPromiseTask in case a task returns a Promise. + */ +export function runTask( + msg: string, + incProgressValue: number, + task: () => T, + tracker: ProgressTracker, + debugEventId?: GraphDebugTimingEventId, +): any { + // Update the progress message to say the current running task. + tracker.setMessage(msg); + // Run the expensive task with a delay that gives enough time for the + // UI to update. + try { + let result = time(msg, task, debugEventId); + // Update the progress value. + tracker.updateProgress(incProgressValue); + // Return the result to be used by other tasks. + return result; + } catch (e: any) { + // Errors that happen inside asynchronous tasks are + // reported to the tracker using a user-friendly message. + tracker.reportError(`Failed${msg}`, e); + return null; + } +} +/** + * Runs an expensive task asynchronously and returns a promise of the result. + */ +export function runAsyncTask( + msg: string, + incProgressValue: number, + task: () => T, + tracker?: ProgressTracker, + debugEventId?: GraphDebugTimingEventId, +): Promise { + return new Promise((resolve, reject) => { + // Update the progress message to say the current running task. + if (tracker) { + tracker.setMessage(msg); + } + // Run the expensive task with a delay that gives enough time for the + // UI to update. + setTimeout(function () { + try { + let result = time(msg, task, debugEventId); + // Update the progress value. + if (tracker) { + tracker.updateProgress(incProgressValue); + } + // Return the result to be used by other tasks. + resolve(result); + } catch (e: any) { + // Errors that happen inside asynchronous tasks are + // reported to the tracker using a user-friendly message. + if (tracker) { + tracker.reportError(`Failed${msg}`, e); + } + } + }, ASYNC_TASK_DELAY); + }); +} +/** + * Asynchronously runs an expensive task that returns a promise. Updates the + * tracker's progress after the promise resolves. Returns a new promise that + * resolves after the progress is updated. + */ +export function runAsyncPromiseTask( + msg: string, + incProgressValue: number, + task: () => Promise, + tracker: ProgressTracker, + debugEventId?: GraphDebugTimingEventId, +): Promise { + return new Promise((resolve, reject) => { + let handleError = function (e): void { + // Errors that happen inside asynchronous tasks are + // reported to the tracker using a user-friendly message. + tracker.reportError(`Failed${msg}`, e); + reject(e); + }; + // Update the progress message to say the current running task. + tracker.setMessage(msg); + // Run the expensive task with a delay that gives enough time for the + // UI to update. + setTimeout(function () { + try { + let start = Date.now(); + task() + .then(function (value) { + const durationInMs = Date.now() - start; + // Update the progress value. + tracker.updateProgress(incProgressValue); + // Return the result to be used by other tasks. + resolve(value); + }) + .catch(handleError); + } catch (e) { + handleError(e); + } + }, ASYNC_TASK_DELAY); + }); +} +/** + * Returns a query selector with escaped special characters that are not + * allowed in a query selector. + */ +export function escapeQuerySelector(querySelector: string): string { + return querySelector.replace(/(?[:.\[\],/\\\(\)])/g, '\\$'); +} +/** + * Given a list of strings, it returns a new list of strings with the longest + * common prefix removed. If the common prefix is one of the strings in the + * list, it returns the original strings. + */ +export function removeCommonPrefix(strings: string[]): string[] { + if (strings.length < 2) { + return strings; + } + let index = 0; + let largestIndex = 0; + // Find the shortest name across all strings. + let minLength = _.min(_.map(strings, (str) => str.length)) as number; + while (true) { + index++; + let prefixes = _.map(strings, (str) => str.substring(0, index)); + let allTheSame = prefixes.every((prefix, i) => { + return i === 0 ? true : prefix === prefixes[i - 1]; + }); + if (allTheSame) { + if (index >= minLength) { + // There is a string whose whole name is a prefix to other string. + // In this case, we return the original list of string. + return strings; + } + largestIndex = index; + } else { + break; + } + } + return _.map(strings, (str) => str.substring(largestIndex)); +} +/** + * Given a timestamp in microseconds, return a human-friendly string denoting + * how long ago the timestamp was. + */ +export function computeHumanFriendlyTime(timeInMicroseconds: number): string { + let timeDifferenceInMs = Number(new Date()) - Number(new Date(timeInMicroseconds / 1000)); + if (timeDifferenceInMs < 30000) { + return 'just now'; + } else if (timeDifferenceInMs < 60000) { + return `${Math.floor(timeDifferenceInMs / 1000)} seconds ago`; + } else if (timeDifferenceInMs < 120000) { + return 'a minute ago'; + } else if (timeDifferenceInMs < 3600000) { + return `${Math.floor(timeDifferenceInMs / 60000)} minutes ago`; + } else if (Math.floor(timeDifferenceInMs / 3600000) === 1) { + return 'an hour ago'; + } else if (timeDifferenceInMs < 86400000) { + return `${Math.floor(timeDifferenceInMs / 3600000)} hours ago`; + } else if (timeDifferenceInMs < 172800000) { + return 'yesterday'; + } else { + return `${Math.floor(timeDifferenceInMs / 86400000)} days ago`; + } +} + +const canvas = document.createElement('canvas'); +const measurerContext = canvas.getContext('2d'); + +/** + * Returns width of `text` rendered with Roboto at provided fontSize. + */ +export function measureTextWidth(text: string, fontSize: number): number { + if (measurerContext) measurerContext.font = `${fontSize}px Roboto, sans-serif`; + return measurerContext?.measureText(text).width as number; +} + +/** + * Returns, if rendered `text` does not fit into maxWidth, truncated string with trailing + * ellipsis. + */ +export function maybeTruncateString(text: string, fontSize: number, maxWidth: number): string { + if (!text) return ''; + if (measureTextWidth(text, fontSize) <= maxWidth) return text; + + let start = 0; + let end = text.length; + while (start < end) { + const middle = start + Math.round((end - start) / 2); + const substring = `${text.slice(0, middle)}…`; + if (measureTextWidth(substring, fontSize) <= maxWidth) { + start = middle; + } else { + end = middle - 1; + } + } + return start === 0 ? text[0] : `${text.slice(0, start)}…`; +} + +/** + * Extend this subclass to receive event dispatching traits. + * Useful for when various locations need to observe changes on + * a common instance, who has a limited lifetime. + * + * This is not intended for use with framework-supported elements. + * For example, prefer using `@Output myEmitter` on Angular + * Components, or Polymer's `on-myprop-changed` for Polymer + * elements, instead. + * + * Example usage: + * + * ``` + * export enum ReactorEvent {EXPLODED} + * export class Reactor extends Dispatcher { + * _update() { + * this.dispatchEvent(ReactorEvent.EXPLODED); + * } + * } + * + * // Elsewhere + * const r = new Reactor(); + * r.addEventListener(ReactorEvent.EXPLODED, this._cleanup); + * ``` + */ +export class Dispatcher { + private eventTypeToListeners = new Map void>>(); + + addListener(eventType: EventType, listener: () => void): void { + this.getListeners(eventType)?.push(listener); + } + + removeListener(eventType: EventType, listener: () => void): void { + const newListeners = this.getListeners(eventType)?.filter((x) => { + return x !== listener; + }); + this.eventTypeToListeners.set(eventType, newListeners); + } + + dispatchEvent(eventType: EventType, payload?: any): void { + for (const listener of this.getListeners(eventType)) { + listener(payload); + } + } + + private getListeners(eventType): any { + if (!this.eventTypeToListeners.has(eventType)) { + this.eventTypeToListeners.set(eventType, []); + } + return this.eventTypeToListeners.get(eventType); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_color_select/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_color_select/index.ts new file mode 100644 index 000000000..7df201d0e --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_color_select/index.ts @@ -0,0 +1,945 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import '@vaadin/combo-box'; +import * as _ from 'lodash'; +import * as d3 from 'd3'; +import { PolymerElement, html } from '@polymer/polymer'; +import { customElement, property, observe } from '@polymer/decorators'; +import * as tf_graph_parser from '../../../tf_graph_common/parser'; +import { BENCH_PREFIX, NPU_PREFIX, UNMATCHED_COLOR } from '../../../tf_graph_common/common'; +import * as tf_graph_node from '../../../tf_graph_common/node'; +import { getElementBySelectors } from './../../utils'; +import * as tf_graph_render from '../../../tf_graph_common/render'; +import { DarkModeMixin } from '../../../polymer/dark_mode_mixin'; +import { LegacyElementMixin } from '../../../polymer/legacy_element_mixin'; + +@customElement('tf-color-select') +class Legend extends LegacyElementMixin(DarkModeMixin(PolymerElement)) { + // 定义模板 + static get template(): HTMLTemplateElement { + return html` + + + `; + } + + // 核心part + @property({ type: Array }) + datasets; + + @property({ type: Boolean }) + _colorSetting: boolean = true; // 颜色设置按钮 + + @property({ type: Boolean }) + _filterSetting: boolean = false; + + @property({ type: Boolean }) + _overFlowLevel: boolean = true; // 溢出筛选图例 + + @property({ type: Array }) + selectColor: any = []; + + @property({ type: String }) + selectedPrecisionNode: string = ''; + + @property({ type: Object }) + precisionmenu: any = []; + + // 颜色图例 + @property({ type: Object }) + colorset; + + @property({ type: Object }) + colorSetChanged; + + // 溢出图例默认数据 + @property({ type: Object }) + overFlowSet: any = [ + ['#B6C7FC', 'medium'], + ['#7E96F0', 'high'], + ['#4668B8', 'critical'], + ]; + + // 自定义颜色设置 + @property({ type: Array }) + standardColorList = ['#FFFCF3', '#FFEDBE', '#FFDC7F', '#FFC62E', '#FF9B3D', '#FF704D', '#FF4118']; + + @property({ type: Array }) + colorList = _.cloneDeep(this.standardColorList); + + @property({ type: Array }) + hiddenSelects = [{ key: 'NaN', values: [NaN, NaN] }]; + + @property({ type: Number, notify: true }) + dropdownIndex; + + @property({ type: Object }) + renderHierarchy: tf_graph_render.MergedRenderGraphInfo = {} as any; + + @property({ type: Object }) + colors: any; + + @property({ type: String, notify: true }) + selectedNode: string | null = null; + + // 目录，全量节点数据，支撑各种节点的搜索 + @property({ type: Object }) + menu: any; + + @property({ type: Object }) + unmatched: any = []; + + @property({ type: Object }) + NPU_unmatched: any = []; + + @property({ type: Object }) + Bench_unmatched: any = []; + + // 溢出筛选 + @property({ type: Array }) + overflowLevel: any = []; + + @property({ type: Object }) + overflowmenu: any = []; + + @property({ type: Boolean }) + overflowcheck; + + @property({ type: Boolean }) + hiddenAll = true; + + @property({ type: Boolean }) + hiddenTabChanged = true; + + @property({ type: Object }) + selection: object = {}; + + @observe('unmatched') + _observeUnmatchedNode(): void { + this.set('NPU_unmatched', this.unmatched[0]); + this.set('Bench_unmatched', this.unmatched[1]); + } + + @observe('colorset') + _observeColorSet(): void { + if (this.colorset.length !== 0) { + const colorsets = this.colorset; + for (const item of colorsets) { + if (item[1].value.length === 0) { + item[1].value.push('无匹配节点'); + } + } + this.colorSetChanged = colorsets; + } else { + return; + } + } + + @observe('renderHierarchy') + observeColorSetting(): void { + if (_.isEmpty(this.renderHierarchy)) { + return; + } + + if (this.renderHierarchy.bench) { + this.set('hiddenAll', true); + if (!this.overflowcheck) { + this.set('hiddenTabChanged', false); + } + } else { + if (this.overflowcheck) { + this._selectedTabChanged(); + this.set('hiddenAll', true); + this.set('hiddenTabChanged', false); + } else { + this.set('hiddenAll', false); + } + } + } + + // 写一个如果切换数据清除所有checkbox和所有this.selectColor + @observe('selection') + _clearAllToggleCheckbox(): void { + this.set('selectedSide', '0'); + const allCheckboxes = this.shadowRoot?.querySelectorAll('paper-checkbox'); + if (allCheckboxes) { + allCheckboxes.forEach((checkbox) => { + checkbox.checked = false; // 清空每个 checkbox 的选中状态 + }); + } + this.selectColor = []; + this.precisionmenu = []; + this.overflowLevel = []; + this.set('selectedNode', ''); + } + + toggleVisibility(): void { + this.set('_colorSetting', !this._colorSetting); + } + + _clickSetting(event): void { + event.stopPropagation(); + this.set('_colors', true); + this.toggleVisibility(); + } + + _cancelAction(): void { + this.toggleVisibility(); + } + + _confirmAction(): void { + const newColorsList = {}; + const len = this.hiddenSelects.length; + if (len === 0) { + this.showDynamicDialog('配置失败，请添加配置项。'); + return; + } + + // 遍历每一项，动态生成 newColorsList 对象 + for (let i = 0; i < len; i++) { + const color = this.hiddenSelects[i].key; + const leftValue = this.hiddenSelects[i].values[0]; + const rightValue = this.hiddenSelects[i].values[1]; + // 检查每个组中的所有输入框是否都有值 + if (isNaN(leftValue) || isNaN(rightValue) || color === 'NaN') { + this.showDynamicDialog('配置失败，存在未配置项。'); + return; + } + // 将每个 color 和其对应的 leftValue 和 rightValue 作为 value 数组，设置到 colors 对象中 + newColorsList[color] = { + value: [leftValue, rightValue], + description: + '此节点所有输入输出的统计量相对误差，值越大代表测量值与标杆值的偏差越大，相对误差计算方式：|(测量值-标杆值)/标杆值|', + }; + } + // 无匹配节点图例一定存在 + newColorsList[UNMATCHED_COLOR] = { + value: '无匹配节点', + description: '对比过程中节点未匹配上', + }; + // 更新颜色列表 + this.set('colors', newColorsList); + let newColorSetChanged: any[] = []; + Object.entries(newColorsList).forEach(([color, details]) => { + let detailsTyped = details as { value: string }; + const colorset: any[] = [color, detailsTyped]; + newColorSetChanged.push(colorset); + }); + this.set('colorSetChanged', newColorSetChanged); + const params = new URLSearchParams(); + params.set('colors', JSON.stringify(newColorsList)); + const colorsPath = `setNewColors?${String(params)}`; + tf_graph_parser.fetchPbTxt(colorsPath); + // 根据颜色列表重绘 + let nodeDataSet = Object.entries(this.renderHierarchy.npu.getIndex()); + tf_graph_node.getColors(this.colors); + for (let [_key, value] of Object.entries(nodeDataSet)) { + const renderInfo = value[1]; + const svgRoot = getElementBySelectors(['tf-graph-board', 'tf-graph', 'tf-graph-scene', 'svg']); + const sceneElement = getElementBySelectors(['tf-graph-board', 'tf-graph', 'tf-graph-scene']) as any; + const nodeGroup = d3.select(svgRoot).select(`.node[data-name="${renderInfo.node.name}"]`); + tf_graph_node.stylize(nodeGroup, renderInfo, sceneElement); + } + this.toggleVisibility(); + } + + _toggleDropdown(event): void { + const selectBox = event.target.closest('.select-box'); // 获取最近的父元素 .select-box + const dropdown = selectBox.nextElementSibling; // 获取下一个兄弟元素，即 .dropdown + dropdown.hidden = !dropdown.hidden; + this.dropdownIndex = event.model.index; + function maybeCloseMenu(eventCloseMenu?: any): void { + if (eventCloseMenu?.composedPath().includes(selectBox)) { + return; + } + dropdown.hidden = true; + document.body.removeEventListener('click', maybeCloseMenu, { + capture: true, + }); + } + if (!dropdown.hidden) { + document.body.addEventListener('click', maybeCloseMenu, { + capture: true, + }); + } + } + + _onOptionHover(event): void { + event.target.style.border = 'solid 1px black'; + } + + _outOptionHover(event): void { + event.target.style.border = ''; + } + + _changeColor(event): void { + const dropdown = event.target.closest('.dropdown'); + const select = dropdown.previousElementSibling; + dropdown.hidden = true; + const selectedColor = event.target.value; + select.style.backgroundColor = selectedColor; + this.set(`hiddenSelects.${this.dropdownIndex}.key`, selectedColor); + this.notifyPath('hiddenSelects'); + this._setColorList(); + } + + // 不显示NaN 而显示空 + _formatValue(value): string { + return isNaN(value) ? '' : value; + } + + _validateInputs(event: any): void { + const index = event.model.index; + const { values } = this.hiddenSelects[index]; + + // 显式定义 leftInputSet 和 rightInputSet 的类型为 number[] + const [leftInputSet, rightInputSet] = this.hiddenSelects.reduce<[number[], number[]]>( + (acc, item) => { + acc[0].push(item.values[0]); + acc[1].push(item.values[1]); + return acc; + }, + [[], []], // 初始值为两个空数组 + ); + + let value = parseFloat(event.target.value); + // 输入值验证 NaN值防护 限制输入范围 + if (isNaN(value) || value < 0 || value > 1) { + this._clearInput(event, index); + return; + } + + const valueStr = value.toString(); + + // 检查是否存在小数点 + const parts = valueStr.split('.'); + const hasDecimal = parts.indexOf('.') !== -1; + + // 如果存在小数点且小数部分长度超过最大限制 + if (hasDecimal && parts[1].length > 5) { + // 使用 toFixed 保留最多5位小数 + value = parseFloat(value.toFixed(5)); + } + + const isLeftInput = event.target.id === 'input-left'; + const otherSide = isLeftInput ? values[1] : values[0]; + const [left, right] = isLeftInput ? [value, otherSide] : [otherSide, value]; + + // 检查输入值是否有效 + const isLeftInputGreater = isLeftInput && left > right; + const isRightInputGreater = !isLeftInput && right < left; + + if (isLeftInputGreater || isRightInputGreater) { + this._clearInput(event, index); + return; + } + + // 检查输入值是否与其他区间冲突 + const isConflict = this.hiddenSelects.some((item, i) => { + // 排除当前输入框 + if (i === index) return false; + + const [leftInput, rightInput] = item.values; + return ( + (isLeftInput && left !== leftInput && left >= leftInput && left < rightInput) || + (!isLeftInput && right !== rightInput && right > leftInput && right <= rightInput) || + (isLeftInput && leftInputSet.includes(left)) || + (!isLeftInput && rightInputSet.includes(right)) + ); + }); + + if (isConflict) { + this._clearInput(event, index); + return; + } + + // 0！@#￥ 也可以被float转换为0，阻止这种情况发生 + event.target.value = value; + // 更新值 + this.set(`hiddenSelects.${index}.values.${isLeftInput ? 0 : 1}`, value); + } + + _clearInput(event: any, index: number): void { + event.target.value = ''; // 清空输入框 + this.set(`hiddenSelects.${index}.values.${event.target.id === 'input-left' ? 0 : 1}`, NaN); // 更新 hiddenSelects + } + + _addOption(): void { + if (this.hiddenSelects.length < 5) { + const obj = { + key: 'NaN', + values: [NaN, NaN], + }; + this.push('hiddenSelects', obj); + } + // 确保它在当前同步操作this.push()之后才执行. + this.async(() => { + this._setColorList(); + }, 0); + } + + _removeOption(event): void { + const index = event.model.index; + + // 删除项 + this.splice('hiddenSelects', index, 1); + + // 恢复其他输入框的值 + this.hiddenSelects.forEach((item, i) => { + if (i >= index) { + this.set(`hiddenSelects.${i}.values`, item.values); + } + }); + this._setColorList(); + } + + _setColorList(): void { + let colorSelectElements = this.shadowRoot?.querySelectorAll('[id^="color-select"]'); + let backgroundColors: string[] = []; + this.hiddenSelects.forEach((item) => { + // 获取计算后的背景色 + const backgroundColor = item.key; + backgroundColors.push(backgroundColor); + }); + let newColorList = this.standardColorList.filter((color) => !backgroundColors.includes(color)); + this.set('colorList', newColorList); + // 清除选中，否则再次选中不同列表的同一顺位的值的时候不会触发on-change + this.async(() => { + colorSelectElements?.forEach((element) => { + if (element instanceof HTMLSelectElement) { + element.selectedIndex = -1; + } + }); + }, 0); + } + + _toggleOverflowLevelOpen(): void { + this.set('_overFlowLevel', !this._overFlowLevel); + } + + showDynamicDialog(message): void { + // 检查是否已经有显示的对话框，避免重复添加 + let existingDialog = this.shadowRoot?.querySelector('#dynamicDialog'); + if (existingDialog) { + existingDialog.remove(); // 删除旧的对话框 + } + // 创建新的对话框 + const dialog = document.createElement('paper-dialog'); + dialog.id = 'dynamicDialog'; + // 添加标题 + const title = document.createElement('h2'); + title.textContent = '提示'; + dialog.appendChild(title); + // 添加提示内容 + const content = document.createElement('div'); + content.textContent = message; + dialog.appendChild(content); + // 添加按钮 + const buttonContainer = document.createElement('div'); + buttonContainer.classList.add('buttons'); + const closeButton = document.createElement('paper-button'); + closeButton.setAttribute('dialog-dismiss', ''); + closeButton.textContent = '关闭'; + buttonContainer.appendChild(closeButton); + dialog.appendChild(buttonContainer); + // 添加到 shadow DOM + this.shadowRoot?.appendChild(dialog); + // 打开对话框 + dialog.open(); + } + + async _toggleCheckbox(this, event): Promise { + const { batch, step, run, tag } = this.selection; + const item = event.model.item; + let checkbox; + let overflowCheckbox; + if (item[1].value) { + checkbox = this.shadowRoot?.getElementById(`checkbox-${event.model.index}`) as HTMLInputElement; + } else { + overflowCheckbox = this.shadowRoot?.getElementById(`overflowCheckbox-${event.model.index}`) as HTMLInputElement; + } + const params = new URLSearchParams(); + if (run) params.set('run', run); + if (tag) params.set('tag', tag); + params.set('batch', String(batch === -1 ? -1 : batch - 1)); + params.set('step', String(step === -1 ? -1 : step - 1)); + // 更新 selectColor 数组 + if (checkbox) { + if (checkbox.checked) { + this.selectColor.push(item[1].value); // 添加选中的颜色 + } else { + const index = this.selectColor.findIndex( + (color) => color[0] === item[1].value[0] && color[1] === item[1].value[1], + ); + if (index !== -1) { + this.selectColor.splice(index, 1); // 取消选中的颜色 + } + } + if (this.selectColor.length === 0) { + this.precisionmenu = []; + return; + } + params.set('precision_index', this.selectColor.join(',')); + const screenPath = `screen?${String(params)}`; + try { + const screenStr = tf_graph_parser.fetchPbTxt(screenPath); + const precisionmenu = JSON.parse(new TextDecoder().decode(await screenStr).replace(/'/g, '"')) as object; + this.set('precisionmenu', precisionmenu); + } catch (e) { + console.error('Parse tooltips failed, please check the format of tooltips in the input vis file'); + } + // 更新数据绑定 + this.notifyPath(`menu.${event.model.index}.checked`, checkbox.checked); + } else { + if (overflowCheckbox.checked) { + this.overflowLevel.push(item[1]); // 添加选中的颜色 + } else { + const index = this.overflowLevel.findIndex((overflow) => overflow === item[1]); + if (index !== -1) { + this.overflowLevel.splice(index, 1); // 取消选中的颜色 + } + } + if (this.overflowLevel.length === 0) { + this.overflowmenu = []; + return; + } + params.set('overflow_level', this.overflowLevel.join(',')); + const screenPath = `screen?${String(params)}`; + + try { + const screenStr = tf_graph_parser.fetchPbTxt(screenPath); + this.overflowmenu = JSON.parse(new TextDecoder().decode(await screenStr).replace(/'/g, '"')) as object; + } catch (e) { + console.error('Parse tooltips failed, please check the format of tooltips in the input vis file'); + } + // 更新数据绑定 + this.notifyPath(`menu.${event.model.index}.checked`, overflowCheckbox.checked); + } + } + + _selectedTabChanged(): void { + this.set('_filterSetting', !this._filterSetting); + } + + _observePrecsionNode(): void { + let prefix = ''; + const hasBNode = this.renderHierarchy.bench?.renderedOpNames.some((name: string) => name.startsWith(BENCH_PREFIX)); + if (hasBNode) { + prefix = NPU_PREFIX; + } + const node = prefix + this.selectedPrecisionNode; + this.set('selectedNode', node); + } + + _handlePrecisonSearch(event): void { + this._handleNodeSearch(event, 'precision'); + } + + _handleOverflowSearch(event): void { + this._handleNodeSearch(event, 'overflow'); + } + + _handleNodeSearch(event, type: 'precision' | 'overflow'): void { + const action = event.target.getAttribute('data-action'); + const menuFirstRow = this.menu[0]; + const selectedNode = this.selectedNode; + let nodeList; + let colorSet; + if (type === 'overflow') { + nodeList = this.overflowmenu; + colorSet = this.overflowLevel; + } else { + nodeList = this.precisionmenu; + if (type === 'precision') { + colorSet = this.selectColor; + } else { + colorSet = null; + } + } + const prefix = NPU_PREFIX; + const hasBNode = this.renderHierarchy.bench?.renderedOpNames.some((name: string) => name.startsWith(BENCH_PREFIX)); + const showDialog = (message: string): void => { + this.showDynamicDialog(message); + }; + + const setDefaultNode = (): void => { + const defaultNode = hasBNode ? `${prefix}${nodeList[0]}` : `${prefix}${nodeList[0]}`; + this.set('selectedNode', defaultNode); + }; + + if (colorSet.length === 0) { + showDialog('请选择颜色'); + return; + } + if (nodeList.length === 0) { + showDialog('选择的颜色没有节点存在'); + return; + } + + // 如果用户未选中节点，设置默认节点 + if (!selectedNode) { + setDefaultNode(); + return; + } + + // 获取 selectedNode 在 menuFirstRow 中的索引 + const slicedNode = hasBNode ? selectedNode.slice(4) : selectedNode; + const startIndex = menuFirstRow.indexOf(slicedNode); + if (startIndex === -1) { + setDefaultNode(); + return; + } + + // 查找下一个节点 + const findNextNode = (): string | null => { + if (nodeList.includes(selectedNode)) { + const currentIndex = nodeList.indexOf(selectedNode); + if (currentIndex + 1 >= nodeList.length) { + showDialog('没有下一个问题节点'); + return null; + } + return nodeList[currentIndex + 1]; + } + for (let i = startIndex + 1; i < menuFirstRow.length; i++) { + if (nodeList.includes(menuFirstRow[i])) { + return menuFirstRow[i]; + } + } + showDialog('没有下一个问题节点'); + return null; + }; + + // 查找上一个节点 + const findPreviousNode = (): string | null => { + if (nodeList.includes(selectedNode)) { + const currentIndex = nodeList.indexOf(selectedNode); + if (currentIndex === 0) { + showDialog('没有上一个问题节点'); + return null; + } + return nodeList[currentIndex - 1]; + } + for (let i = startIndex - 1; i >= 0; i--) { + if (nodeList.includes(menuFirstRow[i])) { + return menuFirstRow[i]; + } + } + showDialog('没有上一个问题节点'); + return null; + }; + + // 执行查找 + const nextNode = action === 'next' ? findNextNode() : findPreviousNode(); + + if (nextNode) { + const nextSelectedNode = hasBNode ? `${prefix}${nextNode}` : nextNode; + this.set('selectedNode', nextSelectedNode); + } + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts new file mode 100644 index 000000000..b517a858b --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts @@ -0,0 +1,410 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import '@vaadin/button'; +import '@vaadin/details'; +import '@vaadin/combo-box'; + +import { isEmpty } from 'lodash'; +import { Notification } from '@vaadin/notification'; +import { PolymerElement, html } from '@polymer/polymer'; +import * as tf_graph_render from '../../../tf_graph_common/render'; +import { customElement, property, observe } from '@polymer/decorators'; +import { NPU_PREFIX, BENCH_PREFIX } from '../../../tf_graph_common/common'; +import useMatched from './useMatched'; +import type { UseMatchedType } from './useMatched'; +import '@vaadin/progress-bar'; +import '../tf_search_combox/index'; +@customElement('tf-manual-match') +class Legend extends PolymerElement { + // 定义模板 + static get template(): HTMLTemplateElement { + return html` + + +
    +

    注意：匹配结束后需要点击保存按钮，将操作后数据更新到文件中，否则操作无效

    + 保存 + +
    +
    +

    未匹配节点

    + + +
    + 点击匹配 +
    +
    +
    +

    已匹配节点

    + + +
    + 取消匹配 +
    +
    +     + `; + } + + @property({ type: Object }) + unmatched: any = []; + + @property({ type: Object }) + selection: any; + + @property({ type: Object }) + renderHierarchy: tf_graph_render.MergedRenderGraphInfo = {} as any; + + @property({ type: Boolean }) + isCompareGraph: boolean = true; + + @property({ type: String, notify: true }) + selectedNode: string = ''; + + @property({ type: Array }) + npuMatchedNodes: Array = []; + + @property({ type: Array }) + benchMatchedNodes: Array = []; + + @property({ type: Array }) + npuUnMatchedNodes: Array = []; + + @property({ type: Array }) + benchUnMatchedNodes: Array = []; + + @property({ type: String }) + selectedNpuMatchedNode: string = ''; + + @property({ type: String }) + selectedBenchMatchedNode: string = ''; + + @property({ type: String }) + selectedNpuUnMatchedNode: string = ''; + + @property({ type: String }) + selectedBenchUnMatchedNode: string = ''; + + @property({ type: Boolean }) + saveLoading: boolean = false; + + useMatched: UseMatchedType = useMatched(); + + npuMatchedNodeList = {}; + benchMatchedNodeList = {}; + + @observe('unmatched') + _observeUnmatchedNode(): void { + this.set('npuUnMatchedNodes', this.unmatched[0]); + this.set('benchUnMatchedNodes', this.unmatched[1]); + } + + @observe('renderHierarchy') + _observeRenderHierarchy(): void { + const isCompareGraphTemp = this.renderHierarchy.bench?.renderedOpNames.some((name: string) => + name.startsWith(BENCH_PREFIX), + ); + this.set('isCompareGraph', isCompareGraphTemp); + } + + @observe('selection') + async _observeSelection(): Promise { + if (isEmpty(this.selection)) return; + const result = await this.useMatched.queryMatchedStateList(this.selection); + if (result.success) { + // 初始化已匹配节点列表 + const { npu_match_nodes, bench_match_nodes } = result.data; + this.npuMatchedNodeList = npu_match_nodes; + this.benchMatchedNodeList = bench_match_nodes; + this.set('npuMatchedNodes', Object.keys(npu_match_nodes)); + this.set('benchMatchedNodes', Object.keys(bench_match_nodes)); + } else { + Notification.show(`错误：${result.error}`, { + position: 'middle', + duration: 3000, + theme: 'error', + }); + } + } + + @observe('selectedNode') + _observeSelectedNode(): void { + if (isEmpty(this.selectedNode)) return; + if (this.selectedNode.startsWith(NPU_PREFIX)) { + this.set('selectedNpuUnMatchedNode', this.selectedNode.replace(NPU_PREFIX, '')); + } else if (this.selectedNode.startsWith(BENCH_PREFIX)) { + this.set('selectedBenchUnMatchedNode', this.selectedNode.replace(BENCH_PREFIX, '')); + } + } + + // 一定要写箭头函数，不然父子组件传值this指向有问题 + _changeNpuUnMatchedNode = (): void => { + if (this.isCompareGraph) { + const node = NPU_PREFIX + this.selectedNpuUnMatchedNode; + this.set('selectedNode', node); + } else { + Notification.show('提示：单图节点不支持匹配', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + } + }; + + _changeBenchUnMatchedNode = (): void => { + if (this.isCompareGraph) { + const node = BENCH_PREFIX + this.selectedBenchUnMatchedNode; + this.set('selectedNode', node); + } else { + Notification.show('提示：单图节点不支持匹配', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + } + }; + + _changeNpuMatchedNode = (): void => { + if (this.isCompareGraph) { + const node = NPU_PREFIX + this.selectedNpuMatchedNode; + this.set('selectedBenchMatchedNode', this.npuMatchedNodeList[this.selectedNpuMatchedNode]); + this.set('selectedNode', node); + this.set('selectedNode', BENCH_PREFIX + this.selectedBenchMatchedNode); + } else { + Notification.show('提示：单图节点不支持匹配', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + } + }; + + _changeBenchMatchedNode = (): void => { + if (this.isCompareGraph) { + const node = BENCH_PREFIX + this.selectedBenchMatchedNode; + this.set('selectedNpuMatchedNode', this.benchMatchedNodeList[this.selectedBenchMatchedNode]); + this.set('selectedNode', node); + this.set('selectedNode', NPU_PREFIX + this.selectedNpuMatchedNode); + } else { + Notification.show('提示：单图节点不支持匹配', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + } + }; + + // 取消匹配 + async _deletelMatchedNodesLink(): Promise { + const result = await this.useMatched.deleteMatchedNodesLink( + this.selectedNpuMatchedNode, + this.selectedBenchMatchedNode, + this.selection, + this.renderHierarchy, + ); + if (result.success) { + // 更新匹配关系 + delete this.npuMatchedNodeList[this.selectedNpuMatchedNode]; + delete this.benchMatchedNodeList[this.selectedBenchMatchedNode]; + // 未匹配列表添加取消匹配的节点 + this.set('npuUnMatchedNodes', [...this.npuUnMatchedNodes, this.selectedNpuMatchedNode]); + this.set('benchUnMatchedNodes', [...this.benchUnMatchedNodes, this.selectedBenchMatchedNode]); + // 已匹配列表删除匹配成功的节点 + this.set('npuMatchedNodes', Object.keys(this.npuMatchedNodeList)); + this.set('benchMatchedNodes', Object.keys(this.benchMatchedNodeList)); + // 未匹配列表选择取消匹配的节点 + this.set('selectedNpuUnMatchedNode', this.selectedNpuMatchedNode); + this.set('selectedBenchUnMatchedNode', this.selectedBenchMatchedNode); + // 选中节点 + this.set('selectedNode', ''); + this.set('selectedNode', NPU_PREFIX + this.selectedNpuMatchedNode); + // 已匹配列表清空选中的节点 + this.set('selectedNpuMatchedNode', ''); + this.set('selectedBenchMatchedNode', ''); + Notification.show('取消成功：对应节点状态已更新', { + position: 'middle', + duration: 3000, + theme: 'success', + }); + } else { + Notification.show(`匹配失败：${result.error}`, { + position: 'middle', + duration: 3000, + theme: 'error', + }); + } + } + + // 匹配节点 + async _addMatchedNodesLink(): Promise { + const result = await this.useMatched.addMatchedNodesLink( + this.selectedNpuUnMatchedNode, + this.selectedBenchUnMatchedNode, + this.selection, + this.renderHierarchy, + ); + if (result.success) { + // 更新匹配关系 + this.npuMatchedNodeList[this.selectedNpuUnMatchedNode] = this.selectedBenchUnMatchedNode; + this.benchMatchedNodeList[this.selectedBenchUnMatchedNode] = this.selectedNpuUnMatchedNode; + // 未匹配列表删除匹配成功的节点 + this.set( + 'npuUnMatchedNodes', + this.npuUnMatchedNodes.filter((node) => node !== this.selectedNpuUnMatchedNode), + ); + this.set( + 'benchUnMatchedNodes', + this.benchUnMatchedNodes.filter((node) => node !== this.selectedBenchUnMatchedNode), + ); + // 已匹配列表添加匹配成功的节点 + this.set('npuMatchedNodes', Object.keys(this.npuMatchedNodeList)); + this.set('benchMatchedNodes', Object.keys(this.benchMatchedNodeList)); + // 已匹配列表选择匹配成功的节点 + this.set('selectedNpuMatchedNode', this.selectedNpuUnMatchedNode); + this.set('selectedBenchMatchedNode', this.selectedBenchUnMatchedNode); + // 选中节点 + this.set('selectedNode', ''); + this.set('selectedNode', NPU_PREFIX + this.selectedNpuUnMatchedNode); + // 未匹配列表清空选中的节点 + this.set('selectedNpuUnMatchedNode', ''); + this.set('selectedBenchUnMatchedNode', ''); + + Notification.show('匹配成功：对应节点状态已更新', { + position: 'middle', + duration: 3000, + theme: 'success', + }); + } else { + Notification.show(`匹配失败：${result.error}`, { + position: 'middle', + duration: 3000, + theme: 'error', + }); + } + } + + // 保存 + async _saveMatchedNodesLink(): Promise { + this.set('saveLoading', true); + const result = await this.useMatched.saveMatchedNodesLink(this.selection); + this.set('saveLoading', false); + if (result.success) { + Notification.show('保存成功：文件已变更', { + position: 'middle', + duration: 3000, + theme: 'success', + }); + } else { + Notification.show(`保存失败：${result.error}`, { + position: 'middle', + duration: 3000, + theme: 'error', + }); + } + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/useMatched.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/useMatched.ts new file mode 100644 index 000000000..1ec6d3bcd --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/useMatched.ts @@ -0,0 +1,242 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import { isEmpty, zip } from 'lodash'; +import { fetchPbTxt } from '../../../tf_graph_common/parser'; +import { Notification } from '@vaadin/notification'; +import { NPU_PREFIX, BENCH_PREFIX } from '../../../tf_graph_common/common'; + +export interface UseMatchedType { + saveMatchedNodesLink: (selection: any) => Promise; + addMatchedNodesLink: ( + npuNodeName: string, + beachNodeName: string, + selection: any, + renderHierarchy: any, + ) => Promise; + queryMatchedStateList: (selection: any) => Promise; + deleteMatchedNodesLink: ( + npuNodeName: string, + beachNodeName: string, + selection: any, + renderHierarchy: any, + ) => Promise; +} + +const useMatched = (): UseMatchedType => { + const requestAddMatchNodes = async (npuNodeName: string, beachNodeName: string, metaData: any): Promise => { + const params = new URLSearchParams(); + params.set('npuNodeName', JSON.stringify(npuNodeName)); + params.set('beachNodeName', JSON.stringify(beachNodeName)); + params.set('metaData', JSON.stringify(metaData)); + // 接口请求 + const precisionPath = `addMatchNodes?${String(params)}`; + const precisionStr = await fetchPbTxt(precisionPath); // 获取异步的 ArrayBuffer + const decoder = new TextDecoder(); + const decodedStr = decoder.decode(precisionStr); // 解码 ArrayBuffer 到字符串 + // 接口返回 + const mactchResult = JSON.parse(decodedStr.replace(/"None"/g, '{}')); + return mactchResult; + }; + + const requestDeleteMatchNodes = async (npuNodeName: string, beachNodeName: string, metaData: any): Promise => { + const params = new URLSearchParams(); + params.set('npuNodeName', JSON.stringify(npuNodeName)); + params.set('beachNodeName', JSON.stringify(beachNodeName)); + params.set('metaData', JSON.stringify(metaData)); + // 接口请求 + const precisionPath = `deleteMatchNodes?${String(params)}`; + const precisionStr = await fetchPbTxt(precisionPath); // 获取异步的 ArrayBuffer + const decoder = new TextDecoder(); + const decodedStr = decoder.decode(precisionStr); // 解码 ArrayBuffer 到字符串 + // 接口返回 + const mactchResult = JSON.parse(decodedStr.replace(/"None"/g, '{}')); + return mactchResult; + }; + + const requestMatchStateList = async (metaData: any): Promise => { + const params = new URLSearchParams(); + params.set('metaData', JSON.stringify(metaData)); + // 接口请求 + const precisionPath = `getMatchedStateList?${String(params)}`; + const precisionStr = await fetchPbTxt(precisionPath); // 获取异步的 ArrayBuffer + const decoder = new TextDecoder(); + const decodedStr = decoder.decode(precisionStr); // 解码 ArrayBuffer 到字符串 + // 接口返回 + const mactchResult = JSON.parse(decodedStr.replace(/"None"/g, '{}')); + return mactchResult; + }; + + const queryMatchedStateList = async (selection: any): Promise => { + const metaData = { + run: selection.run, + tag: selection.tag, + }; + const matchStateList = await requestMatchStateList(metaData); + return matchStateList; + }; + + const saveMatchedNodesLink = async (selection: any): Promise => { + const metaData = { + run: selection.run, + tag: selection.tag, + }; + const params = new URLSearchParams(); + params.set('metaData', JSON.stringify(metaData)); + // 接口请求 + const precisionPath = `saveData?${String(params)}`; + const precisionStr = await fetchPbTxt(precisionPath); // 获取异步的 ArrayBuffer + const decoder = new TextDecoder(); + const decodedStr = decoder.decode(precisionStr); // 解码 ArrayBuffer 到字符串 + // 接口返回 + const saveResult = JSON.parse(decodedStr.replace(/"None"/g, '{}')); + return saveResult; + }; + + const addMatchedNodesLink = async ( + npuNodeName: string, + beachNodeName: string, + selection: any, + renderHierarchy: any, + ): Promise => { + if (isEmpty(npuNodeName) || isEmpty(beachNodeName)) { + Notification.show('错误：调试侧节点或标杆节点为空', { + position: 'middle', + duration: 2000, + theme: 'error', + }); + return; + } + const metaData = { + run: selection.run, + tag: selection.tag, + }; + const matchResult = await requestAddMatchNodes(npuNodeName, beachNodeName, metaData); + if (matchResult.success) { + const graphNpuNodeName = NPU_PREFIX + npuNodeName; + const graphBeachNodeName = BENCH_PREFIX + beachNodeName; + const graphNpuNodeInputData = renderHierarchy.npu?.index?.[graphNpuNodeName]?.node?.inputData; + const graphNpuNodeOutputData = renderHierarchy.npu?.index?.[graphNpuNodeName]?.node?.outputData; + const intputStatisticalDiff = matchResult.data.intput_statistical_diff; + const outputStatisticalDiff = matchResult.data.output_statistical_diff; + // 更新节点之间的匹配关系 + updateGraphNodeData(graphNpuNodeInputData, intputStatisticalDiff); + updateGraphNodeData(graphNpuNodeOutputData, outputStatisticalDiff); + renderHierarchy.npu.index[graphNpuNodeName].node.matchedNodeLink = [graphBeachNodeName]; + renderHierarchy.bench.index[graphBeachNodeName].node.matchedNodeLink = [graphNpuNodeName]; + renderHierarchy.npu.index[graphNpuNodeName].node.nodeAttributes._linked_node = [graphBeachNodeName]; + renderHierarchy.bench.index[graphBeachNodeName].node.nodeAttributes._linked_node = [graphNpuNodeName]; + // 更新匹配精度,节点重新上色 + const precisionIndex = matchResult.data.precision_error; + const nodeAtts = renderHierarchy.npu.index[graphNpuNodeName].node.attr; + const precisionIndexObj = nodeAtts?.find((item) => item.key === 'precision_index'); + if (precisionIndexObj) { + precisionIndexObj.value = precisionIndex; + } else { + nodeAtts.push({ + key: 'precision_index', + value: precisionIndex, + }); + } + } + return matchResult; + }; + + const deleteMatchedNodesLink = async ( + npuNodeName: string, + beachNodeName: string, + selection: any, + renderHierarchy: any, + ): Promise => { + if (isEmpty(npuNodeName) || isEmpty(beachNodeName)) { + Notification.show('错误：调试侧节点或标杆节点为空', { + position: 'middle', + duration: 2000, + theme: 'error', + }); + return null; + } + const metaData = { + run: selection.run, + tag: selection.tag, + }; + const matchResult = await requestDeleteMatchNodes(npuNodeName, beachNodeName, metaData); + matchResult.success = true; + if (matchResult.success) { + const graphNpuNodeName = NPU_PREFIX + npuNodeName; + const graphBeachNodeName = BENCH_PREFIX + beachNodeName; + const graphNpuNodeInputData = renderHierarchy.npu?.index?.[graphNpuNodeName]?.node?.inputData; + const graphNpuNodeOutputData = renderHierarchy.npu?.index?.[graphNpuNodeName]?.node?.outputData; + // 清空节点之间的匹配关系 + deleteMatchedNodeData(graphNpuNodeInputData); + deleteMatchedNodeData(graphNpuNodeOutputData); + renderHierarchy.npu.index[graphNpuNodeName].node.matchedNodeLink = []; + renderHierarchy.bench.index[graphBeachNodeName].node.matchedNodeLink = []; + renderHierarchy.npu.index[graphNpuNodeName].node.nodeAttributes._linked_node = []; + renderHierarchy.bench.index[graphBeachNodeName].node.nodeAttributes._linked_node = []; + // 更新匹配精度,节点重新上色 + const nodeAtts = renderHierarchy.npu.index[graphNpuNodeName].node.attr; + const precisionIndexObj = nodeAtts?.filter((item) => item.key === 'precision_index'); + renderHierarchy.npu.index[graphNpuNodeName].node.attr = precisionIndexObj; + } + return matchResult; + }; + + const updateGraphNodeData = (graphNpuNodeData, statisticalDiff): void => { + if (isEmpty(statisticalDiff) || isEmpty(graphNpuNodeData)) { + return; + } + for (const key in statisticalDiff) { + if (Object.prototype.hasOwnProperty.call(statisticalDiff, key)) { + const value = statisticalDiff[key]; + graphNpuNodeData[key] = { + ...graphNpuNodeData[key], // 如果 graphNpuNodeData[key] 可能为 undefined，则需要额外处理以避免错误 + ...value, + }; + } + } + }; + const deleteMatchedNodeData = (graphNpuNodeData): void => { + const keysToRemove = [ + 'MaxAbsErr', + 'MinAbsErr', + 'NormAbsErr', + 'MeanAbsErr', + 'MaxRelativeErr', + 'MinRelativeErr', + 'NormRelativeErr', + 'MeanRelativeErr', + ]; + for (const key in graphNpuNodeData) { + if (Object.prototype.hasOwnProperty.call(graphNpuNodeData, key)) { + const fildObj = graphNpuNodeData[key]; + keysToRemove.forEach((keyToRemove) => { + // 确保要删除的键存在于当前对象中 + delete fildObj[keyToRemove]; + }); + } + } + }; + + return { + saveMatchedNodesLink, + addMatchedNodesLink, + queryMatchedStateList, + deleteMatchedNodesLink, + }; +}; + +export default useMatched; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_search_combox/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_search_combox/index.ts new file mode 100644 index 000000000..7b384da73 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_search_combox/index.ts @@ -0,0 +1,166 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import '@vaadin/button'; +import '@vaadin/details'; +import '@vaadin/combo-box'; + +import { isEmpty } from 'lodash'; +import { Notification } from '@vaadin/notification'; +import { PolymerElement, html } from '@polymer/polymer'; +import { customElement, property } from '@polymer/decorators'; +import '@vaadin/progress-bar'; +@customElement('tf-search-combox') +class Legend extends PolymerElement { + static get shadowRootOptions(): { mode: string } { + return { mode: 'open' }; // 确保启用了 Shadow DOM + } + // 定义模板 + static get template(): HTMLTemplateElement { + return html` + +
    + + + +
    + `; + } + + @property({ type: Object }) + onSelectChange!: () => void; + + @property({ type: String, notify: true }) + selectedValue: string = ''; + + @property({ type: Array }) + items: string[] = []; + + _onChange(): void { + this.onSelectChange(); + } + + // 选择列表中的下一个节点 + _selectNext(): void { + if (isEmpty(this.items)) { + Notification.show('提示：列表为空', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + return; + } + if (isEmpty(this.selectedValue)) { + this.set('selectedValue', this.items[0]); + this.onSelectChange(); + return; + } + const index = this.items.indexOf(this.selectedValue); + if (index + 1 >= this.items.length) { + Notification.show('提示：已到达列表底部', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + return; + } else { + this.set('selectedValue', this.items[index + 1]); + } + this.onSelectChange(); + } + + // 选择列表中的上一个节点 + _selectPrevious(): void { + if (isEmpty(this.items)) { + Notification.show('提示：列表为空', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + return; + } + if (isEmpty(this.selectedValue)) { + this.set('selectedValue', this.items[0]); + this.onSelectChange(); + return; + } + const index = this.items.indexOf(this.selectedValue); + if (index - 1 < 0) { + Notification.show('提示：已到达列表顶部', { + position: 'middle', + duration: 2000, + theme: 'contrast', + }); + return; + } else { + this.set('selectedValue', this.items[index - 1]); + } + this.onSelectChange(); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/ts_linkage_search_combox/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/ts_linkage_search_combox/index.ts new file mode 100644 index 000000000..6b1f1eeac --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/ts_linkage_search_combox/index.ts @@ -0,0 +1,193 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import '@vaadin/button'; +import '@vaadin/details'; +import '@vaadin/combo-box'; +import '@vaadin/vaadin-select'; +import '@vaadin/text-field'; +import { NPU_PREFIX, BENCH_PREFIX } from '../../../tf_graph_common/common'; +import { PolymerElement, html } from '@polymer/polymer'; +import { customElement, property, observe } from '@polymer/decorators'; +import '@vaadin/progress-bar'; +import * as tf_graph_render from '../../../tf_graph_common/render'; +import '../tf_search_combox/index'; +@customElement('tf-linkage-search-combox') +class legend extends PolymerElement { + static get shadowRootOptions(): { mode: string } { + return { mode: 'open' }; // 确保启用了 Shadow DOM + } + // 定义模板 + static get template(): HTMLTemplateElement { + return html` + +
    +
    + + +
    +
    + +
    +
    + `; + } + + @property({ type: Object }) + renderHierarchy: tf_graph_render.MergedRenderGraphInfo = {} as any; + + @property({ type: String, notify: true }) + selectedNode = ''; + + @property({ type: Boolean }) + isCompareGraph: boolean = true; + + @property({ type: Array }) + menu = []; + + @property({ type: String }) + selectedMenuNode = ''; + + @property({ type: Array }) + menuItem = []; + + @property({ type: String }) + searchText = ''; + + @property({ type: String }) + selectedSide = '0'; + menuSideItem = [ + { label: '调试侧', value: '0' }, + { label: '标杆侧', value: '1' }, + ]; + + @observe('selectedSide') + _observeSelectSide(): void { + if (this.menu) { + this.set('menuItem', this.menu[Number(this.selectedSide)]); + this.set('searchText', ''); + this.set('selectedMenuNode', ''); + } + } + + @observe('menu') + _observeMenu(): void { + this.set('selectedMenuNode', ''); + this.set('selectedSide', '0'); + this.set('searchText', ''); + this.set('menuItem', this.menu[Number(this.selectedSide)]); + } + + @observe('renderHierarchy') + _observeRenderHierarchy(): void { + const isCompareGraphTemp = this.renderHierarchy.bench?.renderedOpNames.some((name: string) => + name.startsWith(BENCH_PREFIX), + ); + this.updateStyles({ '--select-border-color': isCompareGraphTemp ? '#0d0d0d' : 'white' }); + this.set('isCompareGraph', isCompareGraphTemp); + } + + _onSelectedMenuNode = (): void => { + const prefix = this.isCompareGraph ? (this.selectedSide === '0' ? NPU_PREFIX : BENCH_PREFIX) : ''; + const node = prefix + this.selectedMenuNode; + this.set('selectedNode', node); + }; + + _onChangeSearchText(): void { + const allNodeItems = this.menu[Number(this.selectedSide)] as Array; + if (!this.searchText) { + this.set('menuItem', allNodeItems); + return; + } + const searchTextLower = this.searchText.trim().toLowerCase(); // 将搜索文本转换为小写 + const filterItem = allNodeItems?.filter((item: string) => { + return item.toLowerCase().indexOf(searchTextLower) !== -1; // 将目标文本转换为小写 + }); + this.set('selectedMenuNode', ''); + this.set('menuItem', filterItem); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/tf-graph-controls.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/tf-graph-controls.ts new file mode 100644 index 000000000..1b9ea63c3 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/tf-graph-controls.ts @@ -0,0 +1,855 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import '@vaadin/icon'; +import '@vaadin/icons'; +import '@vaadin/details'; +import '@vaadin/vaadin-combo-box'; +import '@vaadin/vaadin-select'; +import './components/ts_linkage_search_combox/index'; +import { customElement, property, observe } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import * as _ from 'lodash'; +import { DarkModeMixin } from '../polymer/dark_mode_mixin'; +import '../polymer/irons_and_papers'; +import './components/tf_manual_match/index'; +import './components/tf_color_select/index'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import '../tf_dashboard_common/tensorboard-color'; +import { SelectionType, NPU_PREFIX, BENCH_PREFIX } from '../tf_graph_common/common'; +import * as tf_graph_proto from '../tf_graph_common/proto'; +import * as tf_graph_render from '../tf_graph_common/render'; +import '../tf_graph_common/tf-graph-icon'; +import '../tf_graph_loader/tf-graph-dashboard-loader'; + +export interface Selection { + run: string; + tag: string | null; + type: SelectionType; + batch: number; + step: number; +} +export interface TagItem { + tag: string | null; + displayName: string; + conceptualGraph: boolean; + opGraph: boolean; + profile: boolean; +} +export interface RunItem { + name: string; + tags: TagItem[]; +} +export type Dataset = Array; +@customElement('tf-graph-controls') +class TfGraphControls extends LegacyElementMixin(DarkModeMixin(PolymerElement)) { + static readonly template = html` + + +
    + + +
    +
    +
    +
    + + + Fit to screen + +
    +
    + + + Download PNG + +
    + +
    +
    Run ([[datasets.length]])
    + + + + + +
    + +
    + + +
    +
    +
    + + +
    + +
    + + + `; + + // 核心part + @property({ type: Array, observer: '_datasetsChanged' }) + datasets: any = []; + + /** + * @type {tf_graph_render.MergedRenderGraphInfo} + */ + @property({ type: Object }) + renderHierarchy: tf_graph_render.MergedRenderGraphInfo; + + /** + * @type {!Selection} + */ + @property({ + type: Object, + notify: true, + readOnly: true, + computed: + '_computeSelection(datasets, _selectedRunIndex, _selectedTagIndex, _selectedGraphType, _selectedMicroStep, _selectedStep)', + }) + selection: object; + + /** + * @type {SelectionType} + */ + @property({ type: String }) + _selectedGraphType: string = SelectionType.OP_GRAPH; + + @property({ type: Object }) + graphDef: any; + + // 下载文件 + @property({ type: Object }) + _downloadFilename = 'graph.png'; + + // Run 路径选择 + @property({ type: Number, observer: '_selectedRunIndexChanged' }) + _selectedRunIndex: number = 0; + + // Tag选择 + @property({ type: Number, observer: '_selectedTagIndexChanged' }) + _selectedTagIndex: number = 0; + + @property({ type: Boolean }) + showSessionRunsDropdown: boolean = true; + + // MicroStep 选择 和 Step选择 + @property({ type: Number }) + _selectedMicroStep: number = -1; + _selectedStep: number = -1; + + @property({ type: Object }) + microsteps: any; + steplist: any; + + // 目录，全量节点数据，支撑各种节点的搜索 + @property({ type: Object }) + menu: any; + + // 颜色数据 + @property({ type: Object }) + colors: any; + + // 颜色图例 + @property({ type: Object }) + colorset; + + // 溢出检测标志 + @property({ type: Boolean }) + overflowcheck; + + // 节点匹配，未匹配部分节点 + @property({ type: Object }) + unmatched: any = []; + + // 上传文件 + @property({ type: Object, notify: true }) + selectedFile: object; + + @property({ type: Boolean }) + showUploadButton: boolean = false; + + // trace input to off-state + @property({ type: Boolean, notify: true }) + traceInputs: boolean = false; + + @property({ type: String, notify: true }) + selectedNode: string | null = null; + + override ready(): void { + super.ready(); + this._showTabContent('设置', 'nodes-content'); + document.addEventListener('contextMenuTag-changed', this._getTagChanged.bind(this)); + } + + _getTagChanged(contextMenuTag): void { + this.set('_selectedTagIndex', contextMenuTag.detail); + } + + _showTabContent(buttonText, contentId): void { + // Remove 'active' class from all buttons + this.shadowRoot?.querySelectorAll('.tab-button').forEach((button) => { + button.classList.remove('active'); + }); + + // Add 'active' class to the clicked button + const buttons = this.shadowRoot?.querySelectorAll('.tab-button'); + buttons?.forEach((button) => { + if ((button as HTMLElement).innerHTML === buttonText) { + button?.classList.add('active'); + } + }); + + // Hide all content + this.shadowRoot?.querySelectorAll('.tab-content').forEach((content) => { + content.classList.add('hidden'); + }); + + // Show the selected content + const selectedContent = this.shadowRoot?.getElementById(contentId); + if (selectedContent) { + selectedContent.classList.remove('hidden'); + } + } + + // 使用示例 + _showNodeControls(): void { + this._showTabContent('设置', 'nodes-content'); + } + + _showMatch(): void { + this._showTabContent('匹配', 'match-content'); + } + + _numTags(datasets: Dataset, _selectedRunIndex: number): number { + return this._getTags(datasets, _selectedRunIndex).length; + } + + _getTags(datasets: Dataset, _selectedRunIndex: number): TagItem[] { + if (!datasets || !datasets[_selectedRunIndex]) { + return []; + } + return datasets[_selectedRunIndex].tags; + } + + _fit(): void { + this.fire('fit-tap'); + } + + download(): void { + this.fire('download-image-requested', this._downloadFilename); + } + + _clearMicroStep(): void { + // 也清除一下MicroStep和Step + this.set('_selectedMicroStep', -1); + this.set('_selectedStep', -1); + this.set('selectedNode', null); + } + + computedLength(microsteps): number { + return microsteps.length > 0 ? microsteps.length - 1 : 0; + } + + _updateFileInput(e: Event): void { + const file = (e.target as HTMLInputElement).files?.[0]; + if (!file) return; + // Strip off everything before the last "/" and strip off the file + // extension in order to get the name of the PNG for the graph. + let filePath = file.name; + const dotIndex = filePath.lastIndexOf('.'); + if (dotIndex >= 0) { + filePath = filePath.substring(0, dotIndex); + } + const lastSlashIndex = filePath.lastIndexOf('/'); + if (lastSlashIndex >= 0) { + filePath = filePath.substring(lastSlashIndex + 1); + } + this._setDownloadFilename(filePath); + this.set('selectedFile', e); + } + + _datasetsChanged(newDatasets: Dataset, oldDatasets: Dataset): void { + if (oldDatasets !== null) { + // Select the first dataset by default. + this._selectedRunIndex = 0; + } + this._setDownloadFilename(this.datasets[this._selectedRunIndex]?.name); + } + + _computeSelection( + datasets: Dataset, + _selectedRunIndex: number, + _selectedTagIndex: number, + _selectedGraphType: SelectionType, + _selectedMicroStep: number, + _selectedStep: number, + ): { run: string; tag: string | null; type: SelectionType; batch: number; step: number } | null { + if (!datasets[_selectedRunIndex] || !datasets[_selectedRunIndex].tags[_selectedTagIndex]) { + return null; + } + return { + run: datasets[_selectedRunIndex].name, + tag: datasets[_selectedRunIndex].tags[_selectedTagIndex].tag, + type: _selectedGraphType, + batch: _selectedMicroStep, + step: _selectedStep, + }; + } + + _selectedRunIndexChanged(runIndex: number): void { + if (!this.datasets) return; + this._selectedTagIndex = 0; + this._selectedGraphType = this._getDefaultSelectionType(); + this.traceInputs = false; // Set trace input to off-state. + this._setDownloadFilename(this.datasets[runIndex]?.name); + } + + _selectedTagIndexChanged(): void { + this._selectedGraphType = this._getDefaultSelectionType(); + } + + _getDefaultSelectionType(): SelectionType { + const { datasets, _selectedRunIndex: run, _selectedTagIndex: tag } = this; + function shouldSkip(datasets: any, run: any, tag: any): boolean { + return ( + !datasets || !datasets[run] || !(datasets[run] as any).tags[tag] || (datasets[run] as any).tags[tag].opGraph + ); + } + if (shouldSkip(datasets, run, tag)) { + return SelectionType.OP_GRAPH; + } + const datasetForRun = datasets[run] as any; + if (datasetForRun.tags[tag].profile) { + return SelectionType.PROFILE; + } + if (datasetForRun.tags[tag].conceptualGraph) { + return SelectionType.CONCEPTUAL_GRAPH; + } + return SelectionType.OP_GRAPH; + } + + _getFile(): void { + (this.$$('#file') as HTMLElement).click(); + } + + _setDownloadFilename(name?: string): void { + this._downloadFilename = `${name ?? 'graph'}.png`; + } + + _statsNotNull(stats: tf_graph_proto.StepStats): boolean { + return stats !== null; + } + + triggerMenuExpandEvent(newName): void { + const detailsElement = this.shadowRoot?.getElementById(newName) as HTMLDetailsElement; + if (detailsElement?.open) { + const event = new CustomEvent('menu-expand-node-changed', { + detail: { name: newName, open: 'unexpand' }, + }); + + document.dispatchEvent(event); + } else { + const event = new CustomEvent('menu-expand-node-changed', { + detail: { name: newName, open: 'expand' }, + }); + document.dispatchEvent(event); + } + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/utils.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/utils.ts new file mode 100644 index 000000000..62211ccec --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/utils.ts @@ -0,0 +1,24 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +export const getElementBySelectors = (selectors): Element | null => { + let currentElement = document.querySelector('graph-app'); + for (const selector of selectors) { + currentElement = currentElement?.shadowRoot?.querySelector(selector); + if (!currentElement) return null; + } + return currentElement; +}; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_dashboard/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_dashboard/index.ts new file mode 100644 index 000000000..b3f4d4586 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_dashboard/index.ts @@ -0,0 +1,358 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { customElement, observe, property } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import '../polymer/irons_and_papers'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import { Canceller } from '../tf_backend/canceller'; +import { RequestManager } from '../tf_backend/requestManager'; +import '../tf_dashboard_common/tf-dashboard-layout'; +import * as tf_storage from '../tf_storage'; +import * as vz_sorting from '../vz_sorting/sorting'; +import '../tf_graph_board/tf-graph-board'; +import * as tf_graph_render from '../tf_graph_common/render'; +import '../tf_graph_controls/tf-graph-controls'; +import '../tf_graph_loader/tf-graph-dashboard-loader'; + +/** + * The (string) name for the run of the selected dataset in the graph dashboard. + */ +const RUN_STORAGE_KEY = 'run'; +/** + * TODO(stephanwlee): Convert this to proper type when converting to TypeScript. + * @typedef {{ + * tag: ?string, + * displayName: string, + * conceptualGraph: boolean, + * opGraph: boolean, + * profile: boolean, + * }} + */ +const TagItem = {}; +/** + * TODO(stephanwlee): Convert this to proper type when converting to TypeScript. + * @typedef {{ + * name: string, + * tags: !Array, + * }} + */ +const RunItem = {}; + +/** + * tf-graph-dashboard displays a graph from a TensorFlow run. + * + * It has simple behavior: Creates a url-generator and run-generator + * to talk to the backend, and then passes the runsWithGraph (list of runs with + * associated graphs) along with the url generator into tf-graph-board for display. + * + * If there are multiple runs with graphs, the first run's graph is shown + * by default. The user can select a different run from a dropdown menu. + */ +@customElement('graph-app') +class TfGraphDashboard extends LegacyElementMixin(PolymerElement) { + static readonly template = html` + + + +
    + +
    +

    No graph definition files were found.

    +
    +
    + +
    +
    +     + + `; + /** + * @type {!Array} + */ + + @property({ type: Array }) + _datasets: any[] = []; + + @property({ type: Boolean }) + _datasetsFetched: boolean = false; + + @property({ type: Number }) + _selectedDataset: number = 0; + + @property({ type: Object }) + _renderHierarchy: tf_graph_render.RenderGraphInfo; + + @property({ type: Object }) + _requestManager: RequestManager = new RequestManager(); + + @property({ type: Object }) + _canceller: Canceller = new Canceller(); + + @property({ type: Boolean }) + _debuggerDataEnabled: boolean; + + @property({ type: Boolean }) + allStepsModeEnabled: boolean; + + @property({ type: String, notify: true }) + selectedNode: string; + + @property({ type: Boolean }) + _isAttached: boolean; + + // Whether this dashboard is initialized. This dashboard should only be initialized once. + @property({ type: Boolean }) + _initialized: boolean; + + // An array of alerts (in chronological order) provided by debugging libraries on when bad + // values (NaN, +/- Inf) appear. + @property({ type: Array, notify: true }) + _debuggerNumericAlerts: unknown[] = []; + + @property({ type: Array }) + runs: unknown[]; + + @property({ + type: String, + notify: true, + observer: '_runObserver', + }) + run: string = tf_storage + .getStringInitializer(RUN_STORAGE_KEY, { + defaultValue: '', + useLocalStorage: false, + }) + .call(this); + + @property({ type: Object }) + _selection: object; + + @property({ type: Boolean }) + _traceInputs: boolean; + + @property({ type: Boolean }) + _autoExtractNodes: boolean; + + @property({ type: Object }) + _selectedFile: any; + + _runObserver = tf_storage.getStringObserver(RUN_STORAGE_KEY, { + defaultValue: '', + polymerProperty: 'run', + useLocalStorage: false, + }); + + @observe('_isAttached') + _maybeInitializeDashboard(): void { + let isAttached = this._isAttached; + if (this._initialized || !isAttached) { + // Either this dashboard is already initialized ... or we are not yet ready to initialize. + return; + } + // Set this to true so we only initialize once. + this._initialized = true; + this._fetchDataset().then((dataset) => { + const runNames = Object.keys(dataset); + // Transform raw data into UI friendly data. + this._datasets = runNames.sort(vz_sorting.compareTagNames).map((runName) => { + const runData = dataset[runName]; + const tagNames = Object.keys(runData.tags).sort(vz_sorting.compareTagNames); + const tags = tagNames + .map((name) => runData.tags[name]) + .map(({ tag, conceptual_graph, op_graph, profile }) => ({ + tag, + displayName: tag, + conceptualGraph: conceptual_graph, + opGraph: op_graph, + profile, + })); + return { name: runName, tags }; + }); + this._datasetsFetched = true; + }); + } + + @observe('_datasetsFetched', '_datasets', 'run') + _determineSelectedDataset(): void { + let datasetsFetched = this._datasetsFetched; + let datasets = this._datasets; + let run = this.run; + // By default, load the first dataset. + if (!run) { + // By default, load the first dataset. + this.set('_selectedDataset', 0); + return; + } + // If the URL specifies a dataset, load it. + const dataset = datasets.findIndex((d) => d.name === run); + if (dataset === -1) { + if (datasetsFetched) { + // Tell the user if the dataset cannot be found to avoid misleading + // the user. + const dialog = this.$$('#error-dialog') as any; + dialog.textContent = `No dataset named "${run}" could be found.`; + dialog.open(); + } + return; + } + this.set('_selectedDataset', dataset); + } + + @observe('_datasetsFetched', '_datasets', '_selectedDataset') + _updateSelectedDatasetName(): void { + let datasetsFetched = this._datasetsFetched; + let datasets = this._datasets; + let selectedDataset = this._selectedDataset; + if (!datasetsFetched) return; + // Cannot update `run` to update the hash in case datasets for graph is empty. + if (datasets.length <= selectedDataset) return; + this.set('run', datasets[selectedDataset].name); + } + + override attached(): void { + this.set('_isAttached', true); + } + + override detached(): void { + this.set('_isAttached', false); + } + + ready(): void { + super.ready(); + } + + _fit(): void { + (this.$$('#graphboard') as any).fit(); + } + + _onDownloadImageRequested(event: CustomEvent): void { + (this.$$('#graphboard') as any).downloadAsImage(event.detail as string); + } + + _getGraphDisplayClassName(_selectedFile: any, _datasets: any[]): string { + const isDataValid = _selectedFile || _datasets.length; + return isDataValid ? '' : 'no-graph'; + } + + _fetchDataset(): Promise { + return this._requestManager.request('info'); + } + + _datasetsState(datasetsFetched, datasets, state): boolean { + if (!datasetsFetched) return state === 'NOT_LOADED'; + if (!datasets || !datasets.length) return state === 'EMPTY'; + return state === 'PRESENT'; + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_debugger_data_card/tf-graph-debugger-data-card.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_debugger_data_card/tf-graph-debugger-data-card.ts new file mode 100644 index 000000000..f1004ad48 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_debugger_data_card/tf-graph-debugger-data-card.ts @@ -0,0 +1,537 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { computed, customElement, observe, property } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; +import * as PolymerDom from '../polymer/dom'; +import '../polymer/irons_and_papers'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import * as tf_graph_render from '../tf_graph_common/render'; +import * as tf_graph_scene from '../tf_graph_common/scene'; +import * as tf_graph_util from '../tf_graph_common/util'; + +@customElement('tf-graph-debugger-data-card') +class TfGraphDebuggerDataCard extends LegacyElementMixin(PolymerElement) { + static readonly template = html` + + +
    Enable all (not just sampled) steps. Requires slow disk read.
    + +

    + Step of Health Pills: + + + +

    + + +

    + Health Pill + + +

    + +
    +

    Numeric Alerts

    +

    Alerts are sorted from top to bottom by increasing timestamp.

    +
    + + + + + + + + + +
    First OffenseTensor (Device)Event Counts
    +
    +
    + +     + `; + + @property({ type: Object }) + renderHierarchy: tf_graph_render.RenderGraphInfo; + + @property({ type: Array, notify: true }) + debuggerNumericAlerts: any; + + @property({ type: Object }) + nodeNamesToHealthPills: any; + + @property({ type: Number, notify: true }) + healthPillStepIndex: any; + + // Only relevant if we are in all steps mode, in which case the user may want to view health + // pills for a specific step. + @property({ type: Number, notify: true }) + specificHealthPillStep: number = 0; + + // Two-ways + @property({ type: String, notify: true }) + selectedNode: any; + + @property({ type: String, notify: true }) + highlightedNode: any; + + // The enum value of the include property of the selected node. + @property({ type: Number, notify: true }) + selectedNodeInclude: any; + + // Whether health pills are currently being loaded, in which case we show a spinner (and the + // current health pills shown might be out of date). + @property({ type: Boolean }) + areHealthPillsLoading: any; + + @property({ type: Array }) + healthPillEntries: unknown[] = tf_graph_scene.healthPillEntries; + + // When all-steps mode is enabled, the user can request health pills for any step. In this + // mode, Tensorboard makes a request every time the user drags the slider to a different step. + @property({ type: Boolean, notify: true }) + allStepsModeEnabled: any; + + ready(): void { + super.ready(); + let mainContainer = document.getElementById('mainContainer'); + let scrollbarContainer = document.querySelector('tf-dashboard-layout .scrollbar') as HTMLElement | null; + if (mainContainer && scrollbarContainer) { + // If this component is being used inside of TensorBoard's dashboard layout, it may easily + // cause the dashboard layout element to overflow, giving the user 2 scroll bars. Prevent + // that by hiding whatever content overflows - the user will have to expand the viewport to + // use this debugging card. + mainContainer.style.overflow = 'hidden'; + scrollbarContainer.style.overflow = 'hidden'; + } + } + + _healthPillsAvailable(debuggerDataEnabled: any, nodeNamesToHealthPills: any): any { + // So long as there is a mapping (even if empty) from node name to health pills, show the + // legend and slider. We do that because, even if no health pills exist at the current step, + // the user may desire to change steps, and the slider must show for the user to do that. + return debuggerDataEnabled && nodeNamesToHealthPills; + } + + _computeTensorCountString(healthPillValuesForSelectedNode: any, valueIndex: any): any { + if (!healthPillValuesForSelectedNode) { + // No health pill data is available. + return ''; + } + return healthPillValuesForSelectedNode[valueIndex].toFixed(0); + } + + @computed( + 'nodeNamesToHealthPills', + 'healthPillStepIndex', + 'selectedNode', + 'allStepsModeEnabled', + 'areHealthPillsLoading', + ) + get healthPillValuesForSelectedNode(): unknown[] | null { + let nodeNamesToHealthPills = this.nodeNamesToHealthPills; + let healthPillStepIndex = this.healthPillStepIndex; + let selectedNode = this.selectedNode; + let allStepsModeEnabled = this.allStepsModeEnabled; + let areHealthPillsLoading = this.areHealthPillsLoading; + if (areHealthPillsLoading) { + // Health pills are loading. Do not render data that is out of date. + return null; + } + if (!selectedNode) { + // No node is selected. + return null; + } + const healthPills = nodeNamesToHealthPills[selectedNode]; + if (!healthPills) { + // This node lacks a health pill. + return null; + } + // If all steps mode is enabled, we use the first health pill in the list because the JSON + // response from the server is a mapping between node name and a list of 1 health pill. + const healthPill = healthPills[allStepsModeEnabled ? 0 : healthPillStepIndex]; + if (!healthPill) { + // This node lacks a health pill at the current step. + return null; + } + // The health pill count values start at 2. Each health pill contains 6 values. + return healthPill.value.slice(2, 8); + } + + @computed( + 'nodeNamesToHealthPills', + 'healthPillStepIndex', + 'allStepsModeEnabled', + 'specificHealthPillStep', + 'areHealthPillsLoading', + ) + get _currentStepDisplayValue(): any { + let nodeNamesToHealthPills = this.nodeNamesToHealthPills; + let healthPillStepIndex = this.healthPillStepIndex; + let allStepsModeEnabled = this.allStepsModeEnabled; + let specificHealthPillStep = this.specificHealthPillStep; + let areHealthPillsLoading = this.areHealthPillsLoading; + if (allStepsModeEnabled) { + // The user seeks health pills for specific step from the server. + return specificHealthPillStep.toFixed(0); + } + if (areHealthPillsLoading) { + // The current step is undefined. + return 0; + } + for (let nodeName in nodeNamesToHealthPills) { + if (Object.prototype.hasOwnProperty.call(nodeNamesToHealthPills, nodeName)) { + // All nodes have the same number of steps stored, so only examine 1 node. + // We do not directly index into the nodeNamesToHealthPills object because we do not have a key. + // If all steps mode is enabled, we only have 1 step to show. + return nodeNamesToHealthPills[nodeName][healthPillStepIndex].step.toFixed(0); + } + } + // The current step could not be computed. + return 0; + } + + // The biggest step value ever seen. Used to determine what steps of health pills to let the + // user fetch in all steps mode. + @computed('nodeNamesToHealthPills') + get _biggestStepEverSeen(): number { + let nodeNamesToHealthPills = this.nodeNamesToHealthPills; + for (let nodeName in nodeNamesToHealthPills) { + if (Object.prototype.hasOwnProperty.call(nodeNamesToHealthPills, nodeName)) { + // All nodes have the same number of steps stored, so only examine 1 node. + // The index is 1 less than the count. Tensorboard backend logic guarantees that the length + // of the array will be greater than 1. + let healthPills = nodeNamesToHealthPills[nodeName]; + return Math.max(this._biggestStepEverSeen, healthPills[healthPills.length - 1].step); + } + } + // No steps seen so far. Default to 0. + return this._biggestStepEverSeen || 0; + } + + @computed('nodeNamesToHealthPills') + get _maxStepIndex(): number { + let nodeNamesToHealthPills = this.nodeNamesToHealthPills; + for (let nodeName in nodeNamesToHealthPills) { + if (Object.prototype.hasOwnProperty.call(nodeNamesToHealthPills, nodeName)) { + // All nodes have the same number of steps stored, so only examine 1 node. + // The index is 1 less than the count. Tensorboard backend logic guarantees that the length + // of the array will be greater than 1. + return nodeNamesToHealthPills[nodeName].length - 1; + } + } + // Return a falsy value. The slider should be hidden. + return 0; + } + + _hasDebuggerNumericAlerts(debuggerNumericAlerts: any): any { + return debuggerNumericAlerts?.length; + } + + @observe('debuggerNumericAlerts') + _updateAlertsList(): void { + let debuggerNumericAlerts = this.debuggerNumericAlerts; + let alertBody = this.$$('#numeric-alerts-body'); + if (!alertBody) { + return; + } + (alertBody as HTMLElement).innerText = ''; + for (let i = 0; i < debuggerNumericAlerts.length; i++) { + let alert = debuggerNumericAlerts[i]; + let tableRow = document.createElement('tr'); + let timestampTd = document.createElement('td'); + timestampTd.innerText = tf_graph_util.computeHumanFriendlyTime(alert.first_timestamp); + timestampTd.classList.add('first-offense-td'); + tableRow.appendChild(timestampTd); + let tensorDeviceTd = document.createElement('td'); + tensorDeviceTd.classList.add('tensor-device-td'); + let tensorSection = document.createElement('div'); + tensorSection.classList.add('tensor-section-within-table'); + tensorSection.innerText = alert.tensor_name; + this._addOpExpansionListener(tensorSection, alert.tensor_name); + tensorDeviceTd.appendChild(tensorSection); + let deviceSection = document.createElement('div'); + deviceSection.classList.add('device-section-within-table'); + deviceSection.innerText = `(${alert.device_name})`; + tensorDeviceTd.appendChild(deviceSection); + tableRow.appendChild(tensorDeviceTd); + let miniHealthPill = document.createElement('div'); + miniHealthPill.classList.add('mini-health-pill'); + let miniHealthPillTd = document.createElement('td'); + miniHealthPillTd.classList.add('mini-health-pill-td'); + miniHealthPillTd.appendChild(miniHealthPill); + tableRow.appendChild(miniHealthPillTd); + if (alert.neg_inf_event_count) { + let negativeInfCountSection = document.createElement('div'); + negativeInfCountSection.classList.add('negative-inf-mini-health-pill-section'); + negativeInfCountSection.innerText = alert.neg_inf_event_count; + negativeInfCountSection.setAttribute('title', `${alert.neg_inf_event_count} events with -\u221E`); + miniHealthPill.appendChild(negativeInfCountSection); + } + if (alert.pos_inf_event_count) { + let positiveInfCountSection = document.createElement('div'); + positiveInfCountSection.classList.add('positive-inf-mini-health-pill-section'); + positiveInfCountSection.innerText = alert.pos_inf_event_count; + positiveInfCountSection.setAttribute('title', `${alert.pos_inf_event_count} events with +\u221E`); + miniHealthPill.appendChild(positiveInfCountSection); + } + if (alert.nan_event_count) { + let nanCountSection = document.createElement('div'); + nanCountSection.classList.add('nan-mini-health-pill-section'); + nanCountSection.innerText = alert.nan_event_count; + nanCountSection.setAttribute('title', `${alert.nan_event_count} events with NaN`); + miniHealthPill.appendChild(nanCountSection); + } + (PolymerDom.dom(alertBody) as any).appendChild(tableRow); + } + } + + // Adds a listener to an element, so that when that element is clicked, the tensor with + // tensorName expands. + _addOpExpansionListener(clickableElement: any, tensorName: any): void { + clickableElement.addEventListener('click', () => { + // When the user clicks on a tensor name, expand all nodes until the user can see the + // associated node. + let nameOfNodeToSelect = tf_graph_render.expandUntilNodeIsShown( + document.getElementById('scene'), + this.renderHierarchy, + tensorName, + ); + // Store the current scroll of the graph info card. Node selection alters that scroll, and + // we restore the scroll later. + let previousScrollFromBottom: any; + let graphInfoCard = document.querySelector('tf-graph-info#graph-info') as any; + if (graphInfoCard) { + previousScrollFromBottom = graphInfoCard.scrollHeight - graphInfoCard.scrollTop; + } + // Update the selected node within graph logic. + let previousSelectedNode = this.selectedNode; + this.set('selectedNode', nameOfNodeToSelect); + // Scroll the graph info card back down if necessary so that user can see the alerts section + // again. Selecting the node causes the info card to scroll to the top, which may mean the + // user no longer sees the list of alerts. + let scrollToOriginalLocation = (): void => { + graphInfoCard.scrollTop = graphInfoCard.scrollHeight - previousScrollFromBottom; + }; + if (graphInfoCard) { + // This component is used within an info card. Restore the original scroll. + if (previousSelectedNode) { + // The card for the selected node has already opened. Immediately restore the scroll. + scrollToOriginalLocation(); + } else { + // Give some time for the DOM of the info card to be created before scrolling down. + window.setTimeout(scrollToOriginalLocation, 20); + } + } + }); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_loader/tf-graph-dashboard-loader.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_loader/tf-graph-dashboard-loader.ts new file mode 100644 index 000000000..fe1c19520 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_loader/tf-graph-dashboard-loader.ts @@ -0,0 +1,368 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { customElement, observe, property } from '@polymer/decorators'; +import { PolymerElement } from '@polymer/polymer'; +import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; +import * as tf_graph_common from '../tf_graph_common/common'; +import * as tf_graph from '../tf_graph_common/graph'; +import * as tf_graph_hierarchy from '../tf_graph_common/hierarchy'; +import * as tf_graph_loader from '../tf_graph_common/loader'; +import * as tf_graph_parser from '../tf_graph_common/parser'; +import * as tf_graph_util from '../tf_graph_common/util'; +import * as tf_graph_node from '../tf_graph_common/node'; +import { DATA_LOAD_TIME, DATA_NOTICE_TIME } from '../tf_graph_common/common'; +import * as tf_graph_controls from '../tf_graph_controls/tf-graph-controls'; +import { error } from 'console'; + +interface GraphRunTag { + run: string; + tag: string | null; +} + +interface Components { + Menu: object; + ToolTip: ''; + Colors: object; + OverflowCheck: boolean; + MicroSteps: number; + StepList: []; + UnMatchedNode: []; + match: []; +} +/** + * Data loader for tf-graph-dashboard. + * + * The loader loads op graph, conceptual graphs, and RunMetadata associated with + * an op graph which is the major difference from the tf-graph-loader which is + * only capable of loading an op graph. Another difference is that the loader + * takes `selection` from the tf-graph-controls as an input as opposed to URL + * path of an data endpoint. + */ +@customElement('tf-graph-dashboard-loader') +class TfGraphDashboardLoader extends LegacyElementMixin(PolymerElement) { + @property({ type: Array }) + datasets: any[]; + + /** + * @type {{value: number, msg: string}} + * + * A number between 0 and 100 denoting the % of progress + * for the progress bar and the displayed message. + */ + @property({ type: Object, notify: true }) + progress: object; + + @property({ type: Object }) + selection: any; + + /** + * @type {?Event} + */ + @property({ type: Object }) + selectedFile: object; + + @property({ type: Object }) + hierarchyParams = tf_graph_hierarchy.DefaultHierarchyParams; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + outGraphHierarchy: tf_graph_hierarchy.Hierarchy; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + outGraph: tf_graph.SlimGraph; + + @property({ + type: Object, + readOnly: true, // This property produces data. + notify: true, + }) + outStats: object; + + @property({ type: Object }) + _graphRunTag: GraphRunTag; + override _template = null; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + menu: object; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + colorset: object; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + tooltips: object; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + colors: any; + + @property({ + type: Array, + notify: true, + }) + overflowcheck; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + microsteps: any; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + steplist: any; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + unmatched: object; + + @property({ + type: Object, + readOnly: true, // readonly so outsider can't change this via binding + notify: true, + }) + matchedlist: object; + + getColors(): any { + return this.colors; + } + + @observe('selection') + _selectionChanged(): void { + if (!this.selection) { + return; + } + // selection can change a lot within a microtask. + // Don't fetch too much too fast and introduce race condition. + this.debounce('selectionchange', () => { + this._load(this.selection); + }); + } + + _setCompoments(componentsPath): Promise { + return new Promise(async (resolve, reject) => { + this.set('progress', { + value: 0, + msg: '', + }); + + const tracker = tf_graph_util.getTracker(this); + const dataTracker = tf_graph_util.getSubtaskTracker(tracker, 100, 'Data'); + dataTracker.setMessage('Initialization in progress'); + + let timer = 0; + let shouldBreak = false; // 标志位，用于控制循环退出 + + // 启动定时器任务 + const timerTask = async function (): Promise { + let previousProgress = 0; // 记录上一次更新的进度 + + while (timer <= DATA_LOAD_TIME && !shouldBreak) { + if (timer < DATA_NOTICE_TIME) { + const progress = Math.log(timer + 1) / Math.log(DATA_NOTICE_TIME); + const progressIncrement = progress * 100 - previousProgress; + dataTracker.updateProgress(progressIncrement); + previousProgress = progress * 100; + } else { + dataTracker.setMessage('File data too large, still reading'); + } + await new Promise((resolveTimer) => setTimeout(resolveTimer, 100)); + timer++; + } + }.bind(this); + + const fetchTask = async function (): Promise { + let componentsStr; + try { + componentsStr = await tf_graph_parser.fetchPbTxt(componentsPath); + } catch (e) { + shouldBreak = true; // 捕获 fetchPbTxt 错误并停止定时器 + dataTracker.reportError('Fetch error, please check first file in file path', e as Error); + return; + } + + shouldBreak = true; // 正常流程也停止定时器 + + let components: Components = { + Menu: [], + ToolTip: '', + Colors: {}, + OverflowCheck: false, + MicroSteps: 0, + StepList: [], + UnMatchedNode: [], + match: [], + }; + + try { + if (componentsStr) { + components = { + ...components, + ...(JSON.parse(new TextDecoder().decode(componentsStr).replace(/'/g, '"')) as Components), + }; + } + } catch (e) { + shouldBreak = true; // 解析错误时停止定时器 + dataTracker.reportError( + 'Parse components failed, please check the format of config data in the input vis file', + e as Error, + ); + return; + } + + // 后续处理逻辑... + const entries = Object.entries(components.ToolTip); + const toolTipObject = Object.fromEntries(entries); + + this._setMenu(components.Menu); + this._setTooltips(toolTipObject); + this._setColors(components.Colors); + this.set('overflowcheck', components.OverflowCheck); + this._setColorset(Object.entries(components.Colors)); + this._setUnmatched(components.UnMatchedNode); + this._setMatchedlist(components.match); + + tf_graph_node.getColors(components.Colors); + + const microstepsCount = Number(components.MicroSteps); + if (microstepsCount) { + const microstepsArray = ['ALL', ...Array.from({ length: microstepsCount }, (_, index) => index)]; + this._setMicrosteps(microstepsArray); + } else { + this._setMicrosteps([]); + } + const steplistCount = Number(components.MicroSteps); + this._setSteplist(steplistCount ? components.StepList : []); + resolve(); + }.bind(this); + + // 同时启动定时器和 fetch 任务 + await Promise.all([timerTask(), fetchTask()]); + }); + } + + _load(selection: tf_graph_controls.Selection): void { + const { run, tag, type: selectionType, batch, step } = selection; + switch (selectionType) { + case tf_graph_common.SelectionType.OP_GRAPH: + case tf_graph_common.SelectionType.CONCEPTUAL_GRAPH: { + // Clear stats about the previous graph. + (function (): void { + this._setOutStats(null); + }).bind(this)(); + const params = new URLSearchParams(); + params.set('run', run); + params.set('conceptual', String(selectionType === tf_graph_common.SelectionType.CONCEPTUAL_GRAPH)); + if (tag) params.set('tag', tag); + params.set('batch', String(batch === -1 ? -1 : batch - 1)); + params.set('step', String(step === -1 ? -1 : step - 1)); + const componentsPath = `components?${String(params)}`; + params.set('node', 'root'); + const graphPath = `subgraph?${String(params)}`; + this._setCompoments(componentsPath).then(() => { + // _setCompoments 完成后执行此行 + this._fetchAndConstructHierarchicalGraph(graphPath).then(() => { + this._graphRunTag = { run, tag }; // 图形构建完成后执行 + }); + }); + return null; + } + default: + console.error(`Unknown selection type: ${selectionType}`); + } + } + + _readAndParseMetadata(path: string): void { + // Reset the progress bar to 0. + this.set('progress', { + value: 0, + msg: '', + }); + let tracker = tf_graph_util.getTracker(this); + tf_graph_parser.fetchAndParseMetadata(path, tracker).then( + function (stats): void { + this._setOutStats(stats); + }.bind(this), + ); + } + + _fetchAndConstructHierarchicalGraph(path: string | null, pbTxtFile?: Blob): Promise { + // Reset the progress bar to 0. + this.set('progress', { + value: 0, + msg: '', + }); + const tracker = tf_graph_util.getTracker(this); + return tf_graph_loader + .fetchAndConstructHierarchicalGraph( + tracker, + path, + pbTxtFile !== undefined ? pbTxtFile : null, + this.hierarchyParams, + ) + .then( + function ({ graph, graphHierarchy }): void { + this._setOutGraph(graph); + this._setOutGraphHierarchy(graphHierarchy); + }.bind(this), + ); + } + + @observe('selectedFile') + _selectedFileChanged(): void { + let e = this.selectedFile; + if (!e) { + return; + } + const target = (e as any).target as HTMLInputElement; + const file = target.files?.[0]; + if (!file) { + return; + } + // Clear out the value of the file chooser. This ensures that if the user + // selects the same file, we'll re-read it. + target.value = ''; + this._fetchAndConstructHierarchicalGraph(null, file); + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_resize_height/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_resize_height/index.ts new file mode 100644 index 000000000..8a71b2e87 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_resize_height/index.ts @@ -0,0 +1,112 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import { PolymerElement, html } from '@polymer/polymer'; +import { customElement, property, observe } from '@polymer/decorators'; + +@customElement('tf-resize-height') +class ResizableTabsheet extends PolymerElement { + static get template(): HTMLTemplateElement { + return html` + + +
    +
    + +
    + `; + } + + @property({ + type: Number, + notify: true, + }) + height: number = 300; + + _resize: (event: MouseEvent) => void = () => {}; + _stopResize: (this: Document, ev: MouseEvent) => any = () => {}; + + @observe('height') + _updateHeight(newHeight): void { + this.updateStyles({ '--tabsheet-height': `${newHeight}px` }); + } + + override ready(): void { + super.ready(); + this._initResizeHandle(); + } + + _initResizeHandle(): void { + const tabsheet = this.$.tabsheet as HTMLElement; + const resizeHandle = this.$.resizeHandle as HTMLElement; + + let isResizing = false; + let startY = 0; + let startHeight = 0; + + // 开始拖拽 + resizeHandle.addEventListener('mousedown', (event: MouseEvent) => { + isResizing = true; + startY = event.clientY; + startHeight = tabsheet.offsetHeight; + document.body.style.cursor = 'ns-resize'; + document.addEventListener('mousemove', this._resize); + document.addEventListener('mouseup', this._stopResize); + }); + + // 拖拽过程 + this._resize = (event): void => { + if (!isResizing) return; + const deltaY = startY - event.clientY; // 向上拖拽为正 + this.set('height', Math.max(10, startHeight + deltaY)); // 更新高度 + }; + + // 停止拖拽 + this._stopResize = (): void => { + isResizing = false; + document.body.style.cursor = ''; + document.removeEventListener('mousemove', this._resize); + document.removeEventListener('mouseup', this._stopResize); + }; + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_vaadin_table/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_vaadin_table/index.ts new file mode 100644 index 000000000..4f66637ae --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_vaadin_table/index.ts @@ -0,0 +1,191 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import { PolymerElement, html } from '@polymer/polymer'; +import { customElement, property, query } from '@polymer/decorators'; +import '@vaadin/grid'; // 引入新的 Vaadin Grid 组件 +import '@vaadin/tooltip'; +import type { GridEventContext } from '@vaadin/grid'; +@customElement('tf-vaadin-table') +class TfVaadinTable extends PolymerElement { + static get template(): HTMLTemplateElement { + return html` + + + + `; + } + + @property({ type: Object }) + syncGrid?: HTMLElement; // 点击高亮需要同步的表格元素 + + @property({ type: Boolean }) + isSingleGraphNode = false; // 是否是单节点图 + + @property({ type: Object }) + tooltips: any; + + @property({ type: Object }) + handleCellClick!: (e: MouseEvent, syncGrid: HTMLElement) => void; + + @property({ + type: Array, + computed: '_computeHeaders(ioDataset)', + }) + headers!: any[]; + + @property({ + type: Boolean, + computed: '_isEmptyGrid(ioDataset)', + }) + isEmptyGrid!: false; + + renderDefaultValue!: (root: HTMLElement, column: any, rowData: any) => void; + + override connectedCallback(): void { + super.connectedCallback(); + this.renderDefaultValue = this._renderDefaultValue.bind(this); + } + + /** + * 计算表头（所有唯一的键） + * @param {Array} data 数据源 + * @return {Array} 表头数组 + */ + _computeHeaders(data): any[] { + if (this._isEmptyGrid(data)) { + return []; + } + const ignoreDataIndex = ['data_name', 'isBench', 'isMatched', 'value']; + const headers = Array.from( + data.reduce((keys, item) => { + // 只取前5个数据项，避免性能问题 + Object.keys(item).forEach((key) => { + if (!ignoreDataIndex.includes(key)) { + keys.add(String(key)); + } + }); + return keys; + }, new Set()), + ); + return headers; + } + + _isEmptyGrid(data): boolean { + return !Array.isArray(data) || data.length === 0; + } + + _renderDefaultValue(root: HTMLElement, column: any, rowData: any): void { + const selectedColor = this._getCssVariable('--selected-color'); + const matchedColor = this._getCssVariable('--matched-color'); + root.classList.remove('splitter'); + if (rowData.item['isBench']) { + root.style.backgroundColor = matchedColor; + if (rowData.item['isMatched']) root.classList.add('splitter'); + } else root.style.backgroundColor = selectedColor; + if (column.path === 'name' && !this.isSingleGraphNode) { + const className = rowData.item['isMatched'] ? 'avater-matched' : 'avater-unmatched'; + root.innerHTML = `${rowData.item[column.path]}`; + return; + } + let tooltip = rowData.item[column.path] ?? '-'; + if (this.tooltips?.[column.path]) { + tooltip = `${this.tooltips[column.path]}:\n${tooltip}`; + } + root.title = tooltip; + root.textContent = rowData.item[column.path] ?? '-'; + } + + handleGridClick(e: MouseEvent): void { + this.handleCellClick(e, this.syncGrid as HTMLElement); // 调用后方法的this会指向当前组件，无法拿到同级别的表格组件，所以需要回传 + } + + _getCssVariable(variableName): string { + const computedStyle = getComputedStyle(this); + return computedStyle.getPropertyValue(variableName).trim(); // 去掉多余的空格 + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_vaddin_text_table/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_vaddin_text_table/index.ts new file mode 100644 index 000000000..1dde35344 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_vaddin_text_table/index.ts @@ -0,0 +1,234 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +import { PolymerElement, html } from '@polymer/polymer'; +import { customElement, property, query } from '@polymer/decorators'; +import '@vaadin/grid'; // 引入新的 Vaadin Grid 组件 +import '@vaadin/tooltip'; +import type { GridEventContext } from '@vaadin/grid'; +import { Notification } from '@vaadin/notification'; +@customElement('tf-vaadin-text-table') +class TfVaadinTable extends PolymerElement { + static get template(): HTMLTemplateElement { + return html` + + + + `; + } + + @property({ type: Object }) + syncGrid!: HTMLElement; // 点击高亮需要同步的表格元素 + + @property({ type: Object }) + handleCellClick!: (e: MouseEvent, syncGrid: HTMLElement) => void; + + @property({ + type: Array, + computed: '_computeHeaders(dataset)', + }) + headers!: any[]; + + @property({ + type: Boolean, + computed: '_isEmptyGrid(dataset)', + }) + isEmptyGrid!: false; + + renderDefaultValue!: (root: HTMLElement, column: any, rowData: any) => void; + tooltipGenerator!: (context: GridEventContext>) => string; + + override connectedCallback(): void { + super.connectedCallback(); + this.renderDefaultValue = this._renderDefaultValue.bind(this); + } + + /** + * 计算表头（所有唯一的键） + * @param {Array} data 数据源 + * @return {Array} 表头数组 + */ + _computeHeaders(data): any[] { + if (this._isEmptyGrid(data)) { + return []; + } + const ignoreDataIndex = ['title']; + const headers = Array.from( + data.slice(0, 5).reduce((keys, item) => { + // 只取前5个数据项，避免性能问题 + Object.keys(item).forEach((key) => { + if (!ignoreDataIndex.includes(key)) { + keys.add(key); + } + }); + return keys; + }, new Set()), + ); + return headers; + } + + _isEmptyGrid(data): boolean { + return !Array.isArray(data) || data.length === 0; + } + + _renderDefaultValue(root: HTMLElement, column: any, rowData: any): void { + const propertyName = column.path; + const titleName = rowData.item.title; + if (!root.firstElementChild) { + switch (titleName) { + case 'stackInfo': + case 'suggestions': + this._createCopyableTextarea(root, propertyName, rowData); + break; + default: + root.style.fontWeight = 'bold'; + root.textContent = `${titleName}：${rowData.item[propertyName] || 'null'}`; + break; + } + } else { + switch (titleName) { + case 'stackInfo': + case 'suggestions': + this._updateCopyableTextarea(root, propertyName, rowData); + break; + default: + root.textContent = `${titleName}：${rowData.item[propertyName] || 'null'}`; + } + } + } + + _createCopyableTextarea(root: HTMLElement, propertyName: any, rowData: any): void { + const container = document.createElement('div'); + container.className = 'copyable-input'; + + const title = document.createElement('div'); + title.className = 'copyable-input-title'; + title.style.fontWeight = 'bold'; + title.textContent = `${rowData.item['title']}:`; + container.appendChild(title); + + const textarea = document.createElement('textarea'); + textarea.readOnly = true; + textarea.value = rowData.item[propertyName]; + container.appendChild(textarea); + + const button = document.createElement('button'); + button.className = 'copy-button'; + button.textContent = '复制'; + button.addEventListener('click', () => { + navigator.clipboard + .writeText(textarea.value) + .then(() => { + Notification.show('复制成功', { + position: 'middle', + duration: 1000, + theme: 'success', + }); + }) + .catch((err) => { + Notification.show('复制失败，请重试', { + position: 'middle', + duration: 1000, + theme: 'error', + }); + console.error('Failed to copy text:', err); + }); + }); + container.appendChild(button); + + root.appendChild(container); + } + + _updateCopyableTextarea(root: HTMLElement, propertyName: any, rowData: any): void { + const title = root.querySelector('.copyable-input-title'); + if (title) title.textContent = `${rowData.item['title']}:`; + const textarea = root.querySelector('textarea'); + if (textarea) textarea.value = rowData.item[propertyName]; + } + + _tooltipGenerator = (context: GridEventContext>): string => { + const { column, item } = context; + return item?.[column?.path || ''] || ''; + }; + + handleGridClick(e: MouseEvent): void { + this.handleCellClick(e, this.syncGrid); // 调用后方法的this会指向当前组件，无法拿到同级别的表格组件，所以需要回传 + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/domain/useNodeInfoDomain.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/domain/useNodeInfoDomain.ts new file mode 100644 index 000000000..a7f3702e2 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/domain/useNodeInfoDomain.ts @@ -0,0 +1,38 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +import { fetchPbTxt } from '../../tf_graph_common/parser'; + +const useNodeInfoDomain = (): { getMatchNodeInfo: (nodeInfo: any, metaData: any) => Promise } => { + const getMatchNodeInfo = async (nodeInfo: any, metaData: any): Promise => { + const params = new URLSearchParams(); + params.set('nodeInfo', JSON.stringify(nodeInfo)); + params.set('metaData', JSON.stringify(metaData)); + // 接口请求 + const precisionPath = `getNodeInfo?${String(params)}`; + const precisionStr = await fetchPbTxt(precisionPath); // 获取异步的 ArrayBuffer + const decoder = new TextDecoder(); + const decodedStr = decoder.decode(precisionStr); // 解码 ArrayBuffer 到字符串 + // 接口返回 + const mactchResult = JSON.parse(decodedStr.replace(/"None"/g, '{}')); + return mactchResult; + }; + + return { + getMatchNodeInfo, + }; +}; + +export default useNodeInfoDomain; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/index.ts new file mode 100644 index 000000000..40e7c83e7 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/index.ts @@ -0,0 +1,316 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +import '@vaadin/tabs'; +import '@vaadin/tabsheet'; +import { Notification } from '@vaadin/notification'; +import { isEmpty } from 'lodash'; +import { PolymerElement, html } from '@polymer/polymer'; +import { observe, customElement, property } from '@polymer/decorators'; +import useNodeInfo from './useNodeInfo'; +import './components/tf_vaadin_table/index'; +import './components/tf_vaddin_text_table/index'; +import './components/tf_resize_height/index'; +import * as tf_graph_hierarchy from '../tf_graph_common/hierarchy'; +import type { UseNodeInfoType } from './useNodeInfo'; +import { GroupNode, Metanode, OpNode } from '../tf_graph_common/graph'; +import { BENCH_PREFIX, NPU_PREFIX } from '../tf_graph_common/common'; + +@customElement('tf-graph-vaadin-tab') +class TfGraphNodeInfo extends PolymerElement { + static get template(): HTMLTemplateElement { + return html` + + + + + + + + 节点信息 + + +
    + +
    +
    +
    + + +
    + +
    + + + +
    +     +
    +
    + +
    + + +
    +     +
    +     + `; + } + + @property({ + type: Object, + computed: '_getNode(selectedNode)', + }) + _node: GroupNode | OpNode | undefined | null; + + @property({ + type: Object, + }) + _matchedNode: any; + + @property({ type: String }) + selectedNode: string = ''; + + @property({ type: Object }) + selection: any; + + @property({ type: Object }) + graphHierarchy?: tf_graph_hierarchy.MergedHierarchy; + + @property({ type: Array }) + ioDataset: any[] = []; + + @property({ type: Array }) + detailData: any[] = []; + + @property({ type: String }) + npuNodeName?: string; + + @property({ type: String }) + benchNodeName?: string; + + @property({ type: Number }) + isSingleGraphNode: boolean = false; + + useNodeInfo: UseNodeInfoType = useNodeInfo(); + + @observe('_node') + async _updateTableData(): Promise { + if (!this._node) { + this.set('ioDataset', []); + this.set('detailData', []); + this.set('npuNodeName', ''); + this.set('benchNodeName', ''); + return; + } + const isNodeStartWithN = this._node.name.startsWith(NPU_PREFIX); + const isSingleGraphNode = !isNodeStartWithN && !this._node?.name?.startsWith(BENCH_PREFIX); + this.set('isSingleGraphNode', isSingleGraphNode); + if (!isSingleGraphNode) await this._updateMatchedNodeLink(this.selectedNode); + // 考虑选中的节点是匹配节点的情况 + const npuNode = isNodeStartWithN || isSingleGraphNode ? this._node : this._matchedNode; + let benchNode; + if (!isSingleGraphNode) { + benchNode = isNodeStartWithN ? this._matchedNode : this._node; + } else { + benchNode = undefined; + } + this.set('npuNodeName', npuNode?.name?.replace(NPU_PREFIX, '')); + this.set('benchNodeName', benchNode?.name?.replace(BENCH_PREFIX, '')); + const inputDataset = this.useNodeInfo.getIoDataSet(npuNode, benchNode, 'inputData'); + const outputDataSet = this.useNodeInfo.getIoDataSet(npuNode, benchNode, 'outputData'); + const ioDataset = [ + ...inputDataset.matchedIoDataset, + ...outputDataSet.matchedIoDataset, + ...inputDataset.unMatchedNpuIoDataset, + ...outputDataSet.unMatchedNpuIoDataset, + ...inputDataset.unMatchedBenchIoDataset, + ...outputDataSet.unMatchedBenchIoDataset, + ]; + this.set('ioDataset', ioDataset); + const detailData = this.useNodeInfo.getDetailDataSet(npuNode, benchNode); + this.set('detailData', detailData); + } + + _getNode(selectedNode): GroupNode | OpNode | undefined | null { + if (!selectedNode) { + return null; + } + const isBench = selectedNode.startsWith(BENCH_PREFIX); + return isBench ? this.graphHierarchy?.bench?.node(selectedNode) : this.graphHierarchy?.npu.node(selectedNode); + } + + async _updateMatchedNodeLink(selectedNode: string): Promise { + const isBench = selectedNode.startsWith(BENCH_PREFIX); + const [selectedHierarchy, matchedHierarchy] = isBench + ? [this.graphHierarchy?.bench, this.graphHierarchy?.npu] + : [this.graphHierarchy?.npu, this.graphHierarchy?.bench]; + const matchedNodes: Array = (selectedHierarchy?.node(selectedNode) as Metanode | OpNode)?.matchedNodeLink; + if (isEmpty(matchedNodes)) { + this.set('_matchedNode', null); + return; + } + const matchNodeName = matchedNodes[matchedNodes.length - 1]; + let matchNode = matchNodeName ? matchedHierarchy?.node(matchNodeName) : null; + // 如果没有匹配节点，则通过接口获取匹配节点的信息 + if (isEmpty(matchNode)) { + const nodeInfo = { + nodeName: matchNodeName?.replace(new RegExp(`^(${NPU_PREFIX}|${BENCH_PREFIX})`), ''), // 去掉前缀 + nodeType: this._node?.name?.startsWith(NPU_PREFIX) ? 'Bench' : 'NPU', + }; + const { success, data, error } = await this.useNodeInfo.getNodeInfo(nodeInfo, this.selection); + if (success) { + this.set('_matchedNode', data); + } else { + Notification.show(`获取匹配节点失败：${error}`, { + position: 'middle', + duration: 2000, + theme: 'error', + }); + } + } else { + this.set('_matchedNode', matchNode); + } + } + + // 点击单元格高亮 + handleGridCellClick(e: MouseEvent, syncGrid: HTMLElement): void { + const target = e.composedPath()[0] as HTMLElement; // 获取点击的目标元素 + const slotValue = target.getAttribute('slot'); // 提取 slot 属性 + if (!slotValue || !slotValue.startsWith('vaadin-grid-cell-content-')) return; + const cellIndex = parseInt(slotValue.split('-').pop() || '0', 10); + if (cellIndex <= 8) return; // 前8个元素是表头不可选中，所以跳过 + const highlightedCells = this.shadowRoot?.querySelectorAll('.highlight-cell'); + highlightedCells?.forEach((cell) => cell.classList.remove('highlight-cell')); // 清除所有高亮样式 + target.classList.add('highlight-cell'); // 添加高亮样式到当前单元格 + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/type/index.d.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/type/index.d.ts new file mode 100644 index 000000000..fcb10e13f --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/type/index.d.ts @@ -0,0 +1,28 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +export interface MatchNodeInfo { + success: boolean; + data?: { + name?: string; + inputData?: Record; + outputData?: Record; + stackData?: string; + suggestions?: Record; + include?: number; + subnodes?: Array; + }; + error?: string; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts new file mode 100644 index 000000000..bb3b5b9ce --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts @@ -0,0 +1,262 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +import { isEmpty, cloneDeep } from 'lodash'; +import useNodeInfoDomain from './domain/useNodeInfoDomain'; +import type { MatchNodeInfo } from './type'; +import type { MactchResult } from '../types/service'; +import { BENCH_PREFIX, NPU_PREFIX } from '../tf_graph_common/common'; + +export interface UseNodeInfoType { + getNodeInfo: ( + nodeInfo: { + nodeName: string; + nodeType: string; + }, + metaData: any, + ) => Promise; + getIoDataSet: ( + npuNode: any, + benchNode: any, + type: 'inputData' | 'outputData', + ) => { + matchedIoDataset: Array>; + unMatchedNpuIoDataset: Array>; + unMatchedBenchIoDataset: Array>; + }; + getDetailDataSet: (npuNode: any, benchNode: any) => Array>; + converMatchArrayToObject: (resArray: Array) => Array; +} + +const useNodeInfo = (): UseNodeInfoType => { + const useNodeInfoService = useNodeInfoDomain(); + /** + * 获取节点信息 + * @param node_name + * @param graph_name + * @param run_name + * @returns + */ + const getNodeInfo = async ( + nodeInfo: { nodeName: string; nodeType: string }, + metaData: any, + ): Promise => { + if (sessionStorage.getItem(JSON.stringify(nodeInfo))) { + // 缓存中存在 + return JSON.parse(sessionStorage.getItem(JSON.stringify(nodeInfo)) || '') as MatchNodeInfo; + } + const mactchResult = await useNodeInfoService.getMatchNodeInfo(nodeInfo, metaData); + mactchResult.data = convertNodeInfo(mactchResult.data); // 提取有效数据，统一命名 + sessionStorage.setItem(JSON.stringify(nodeInfo), JSON.stringify(mactchResult)); // 缓存 + return mactchResult; + }; + + const convertNodeInfo = (nodeInfo: any): MatchNodeInfo['data'] => { + if (isEmpty(nodeInfo)) { + return {}; + } + return { + name: nodeInfo.id, + inputData: nodeInfo.input_data, + outputData: nodeInfo.output_data, + stackData: !isEmpty(nodeInfo.stack_info) ? JSON.stringify(nodeInfo.stack_info) : '', + suggestions: nodeInfo.suggestions, + subnodes: nodeInfo.subnodes, + include: nodeInfo.subnodes?.length, + }; + }; + + /** + * 将匹配结果数组转换为对象 + * @param resArray + * @example + * [request.args.get("NPU"), + * max_precision_index, + * [ + * [ + ['npu_key', npu_key], + ['Max diff', NPU_max - Bench_max], + ['Min diff', NPU_min - Bench_min], + ['Mean diff', NPU_mean - Bench_mean], + ['L2norm diff', NPU_norm - Bench_norm], + ['MaxRelativeErr', max_relative_err], + ['MinRelativeErr', min_relative_err], + ['MeanRelativeErr', mean_relative_err], + ['NormRelativeErr', norm_relative_err] + ] + ..... + ], + * output(同上)] + * @returns + * { + * NPU_node_name: string, + * max_precision_error: number, + * input: {inputargs:{ + * Max diff: number, + * Min diff: number, + * Mean diff: number, + * },{}} + * output: [{ + * Max diff: number, + * Min diff: number, + * Mean diff: number, + * }] + */ + const converMatchArrayToObject = (resArray: Array): Array => { + if (resArray.length === 0) return []; + //内部函数，将二维数组转换为对象 + const _covertIo = (arrayData: Array): Record | undefined => { + if (isEmpty(arrayData)) return undefined; + const inputItems = {}; + arrayData.forEach((inputArray: any) => { + const inputKey = inputArray[0]; + const inputValue = {}; + inputArray.slice(1).map((item: any) => { + inputValue[item[0]] = item[1]; + }); + inputItems[inputKey] = inputValue; + }); + return inputItems; + }; + + // 将数组转换为对象 + const matchedeDataset = resArray.map((item) => { + return { + NPU_node_name: item?.[0], + max_precision_error: item?.[1], + inputData: _covertIo(item?.[2]), + outputData: _covertIo(item?.[3]), + }; + }); + + return matchedeDataset as Array; + }; + + /** + * 获取匹配的输入输出数据 + * @param npuNode NPU节点信息 + * @param benchNode 匹配的节点信息 + * @param name 'inputData' | 'outputData' + * @returns { matchedDataset: Array<{}>, unMatchedNpuDataset: Array<{}>, unMatchedBenchDataset: Array<{}> } + */ + const getIoDataSet = ( + npuNode: any, + benchNode: any, + type: 'inputData' | 'outputData', + ): { + matchedIoDataset: Array>; + unMatchedNpuIoDataset: Array>; + unMatchedBenchIoDataset: Array>; + } => { + if (isEmpty(npuNode?.[type]) && isEmpty(benchNode?.[type])) { + return { + matchedIoDataset: [], + unMatchedNpuIoDataset: [], + unMatchedBenchIoDataset: [], + }; + } + const npuNodeName = npuNode?.name.replace(new RegExp(`^(${NPU_PREFIX}|${BENCH_PREFIX})`), ''); + const benchNodeName = benchNode?.name?.replace(new RegExp(`^(${NPU_PREFIX}|${BENCH_PREFIX})`), ''); + const npuData = cloneDeep(npuNode?.[type]); // 获取当前节点的输入数据 + const benchData = cloneDeep(benchNode?.[type]); // 获取匹配节点的输入数据 + + const matchedIoDataset: Array> = []; // 初始化输入数据集 + const unMatchedBenchIoDataset: Array> = []; + const unMatchedNpuIoDataset: Array> = []; + const npuKeys = Object.keys(npuData || {}); + const benchKeys = Object.keys(benchData || {}); + const minLength = Math.min(npuKeys.length, benchKeys.length); + for (let i = 0; i < minLength; i++) { + const npuKey = npuKeys[i]; + const benchKey = benchKeys[i]; + matchedIoDataset.push({ + name: npuKey.replace(`${npuNodeName}.`, ''), + isMatched: true, + ...npuData[npuKey], + }); + matchedIoDataset.push({ + name: benchKey.replace(`${benchNodeName}.`, ''), + isBench: true, + isMatched: true, + ...benchData[benchKey], + }); + delete npuData[npuKey]; + delete benchData[benchKey]; + } + Object.keys(npuData || {}).forEach((key) => { + if (npuData[key] !== 'None') { + unMatchedNpuIoDataset.push({ + name: key.replace(`${npuNodeName}.`, ''), + ...npuData[key], + }); + } + }); + Object.keys(benchData || {}).forEach((key) => { + if (benchData[key] !== 'None') { + unMatchedBenchIoDataset.push({ + name: key.replace(`${benchNodeName}.`, ''), + isBench: true, + ...benchData[key], + }); + } + }); + return { matchedIoDataset, unMatchedNpuIoDataset, unMatchedBenchIoDataset }; + }; + + const getDetailDataSet = (npuNode: any, benchNode: any): Array> => { + if (isEmpty(npuNode) && isEmpty(benchNode)) { + return []; + } + const nodeName = `NPU节点：${npuNode?.name?.replace(new RegExp(`^(${NPU_PREFIX}|${BENCH_PREFIX})`), '')}`; + const benchNodeName = `标杆节点：${benchNode?.name?.replace(new RegExp(`^(${NPU_PREFIX}|${BENCH_PREFIX})`), '')}`; + const detailData: Array> = []; + // 获取stackInfo + const stackInfo: Record = {}; + const npustackInfo = npuNode?.stackData; + const benchstackInfo = benchNode?.stackData; + if (!isEmpty(npustackInfo)) stackInfo[nodeName] = JSON.parse(npustackInfo.replace(/'/g, '"')).join('\n'); + if (!isEmpty(benchstackInfo)) stackInfo[benchNodeName] = JSON.parse(benchstackInfo.replace(/'/g, '"')); + if (!isEmpty(stackInfo)) { + stackInfo['title'] = 'stackInfo'; + detailData.push(stackInfo); + } + // 获取suggestions + const suggestion: Record = {}; + const npusuggestion = npuNode?.suggestions; + const benchsuggestion = benchNode?.suggestions; + if (!isEmpty(npusuggestion)) suggestion[nodeName] = converObjectToString(npusuggestion); + if (!isEmpty(benchsuggestion)) suggestion[benchNodeName] = converObjectToString(benchsuggestion); + if (!isEmpty(suggestion)) { + suggestion['title'] = 'suggestions'; + detailData.push(suggestion); + } + return detailData; + }; + + const converObjectToString = (obj: any): string => { + return Object.entries(obj) + .map(([key, value]) => `${key}: ${value}`) + .join('\n'); + }; + + return { + getNodeInfo, + getIoDataSet, + getDetailDataSet, + converMatchArrayToObject, + }; +}; + +export default useNodeInfo; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/index.ts new file mode 100644 index 000000000..e0d7e905a --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/index.ts @@ -0,0 +1,16 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +export * from './listeners'; +export * from './storage'; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/listeners.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/listeners.ts new file mode 100644 index 000000000..8d4785ab8 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/listeners.ts @@ -0,0 +1,49 @@ +/* Copyright 2018 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +export class ListenKey { + public readonly listener: () => void; + constructor(listener: () => void) { + this.listener = listener; + } +} +const hashListeners = new Set(); +const storageListeners = new Set(); +window.addEventListener('hashchange', () => { + hashListeners.forEach((listenKey) => listenKey.listener()); +}); +// [1]: The event only triggers when another tab edits the storage. Changing a +// value in current browser tab will NOT trigger below event. +window.addEventListener('storage', () => { + storageListeners.forEach((listenKey) => listenKey.listener()); +}); +export function addHashListener(fn: () => void): ListenKey { + const key = new ListenKey(fn); + hashListeners.add(key); + return key; +} +export function addStorageListener(fn: () => void): ListenKey { + const key = new ListenKey(fn); + storageListeners.add(key); + return key; +} +export function fireStorageChanged(): void { + storageListeners.forEach((listenKey) => listenKey.listener()); +} +export function removeHashListenerByKey(key: ListenKey): void { + hashListeners.delete(key); +} +export function removeStorageListenerByKey(key: ListenKey): void { + storageListeners.delete(key); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/storage.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/storage.ts new file mode 100644 index 000000000..fcff8da99 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/storage.ts @@ -0,0 +1,217 @@ +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import * as _ from 'lodash'; +import { + addHashListener, + addStorageListener, + fireStorageChanged, + ListenKey, + removeHashListenerByKey, + removeStorageListenerByKey, +} from './listeners'; +import { + componentToDict, + dictToComponent, + readComponent, + TAB_KEY, + unsetFromURI, + updateUrlDict, + writeComponent, +} from './storage_utils'; + +export { getUrlDict as getUrlHashDict } from './storage_utils'; + +/** + * The name of the property for users to set on a Polymer component + * in order for its stored properties to be stored in the URI unambiguously. + * (No need to set this if you want multiple instances of the component to + * share URI state) + * + * Example: + * + * + * The disambiguator should be set to any unique value so that multiple + * instances of the component can store properties in URI storage. + * + * Because it's hard to dereference this variable in HTML property bindings, + * it is NOT safe to change the disambiguator string without find+replace + * across the codebase. + */ +export const DISAMBIGUATOR = 'disambiguator'; + +export const { + get: getString, + set: setString, + getInitializer: getStringInitializer, + getObserver: getStringObserver, + disposeBinding: disposeStringBinding, +} = makeBindings( + (x) => x, + (x) => x, +); +export const { + get: getBoolean, + set: setBoolean, + getInitializer: getBooleanInitializer, + getObserver: getBooleanObserver, + disposeBinding: disposeBooleanBinding, +} = makeBindings( + (s) => { + if (s === 'true') { + return true; + } else if (s === 'false') { + return false; + } else { + return undefined; + } + }, + (b) => b.toString(), +); +export const { + get: getNumber, + set: setNumber, + getInitializer: getNumberInitializer, + getObserver: getNumberObserver, + disposeBinding: disposeNumberBinding, +} = makeBindings( + (s) => Number(s), + (n) => n.toString(), +); +export const { + get: getObject, + set: setObject, + getInitializer: getObjectInitializer, + getObserver: getObjectObserver, + disposeBinding: disposeObjectBinding, +} = makeBindings( + (s) => JSON.parse(atob(s)) as Record, + (o) => btoa(JSON.stringify(o)), +); +export interface StorageOptions { + defaultValue?: T; + useLocalStorage?: boolean; +} +export interface AutoStorageOptions extends StorageOptions { + polymerProperty?: string; +} +export interface SetterOptions extends StorageOptions { + defaultValue?: T; + useLocalStorage?: boolean; + useLocationReplace?: boolean; +} +export function makeBindings( + fromString: (string) => T, + toString: (T) => string, +): { + get: (key: string, option?: StorageOptions) => T; + set: (key: string, value: T, option?: SetterOptions) => void; + getInitializer: (key: string, options: AutoStorageOptions) => () => T; + getObserver: (key: string, options: AutoStorageOptions) => () => void; + disposeBinding: () => void; +} { + const hashListeners: ListenKey[] = []; + const storageListeners: ListenKey[] = []; + function get(key: string, options: StorageOptions = {}): T { + const { defaultValue, useLocalStorage = false } = options; + const value = useLocalStorage ? window.localStorage.getItem(key) : componentToDict(readComponent())[key]; + return (value === undefined ? _.cloneDeep(defaultValue) : fromString(value)) as T; + } + function set(key: string, value: T, options: SetterOptions = {}): void { + const { defaultValue, useLocalStorage = false, useLocationReplace = false } = options; + const stringValue = toString(value); + if (useLocalStorage) { + window.localStorage.setItem(key, stringValue); + // Because of listeners.ts:[1], we need to manually notify all UI elements + // listening to storage within the tab of a change. + fireStorageChanged(); + } else if (!_.isEqual(value, get(key, { useLocalStorage }))) { + if (_.isEqual(value, defaultValue)) { + unsetFromURI(key, useLocationReplace); + } else { + const items = componentToDict(readComponent()); + items[key] = stringValue; + writeComponent(dictToComponent(items), useLocationReplace); + } + } + } + /** + * Returns a function that can be used on a `value` declaration to a Polymer + * property. It updates the `polymerProperty` when storage changes -- i.e., + * when `useLocalStorage`, it listens to storage change from another tab and + * when `useLocalStorage=false`, it listens to hashchange. + */ + function getInitializer(key: string, options: StorageOptions): () => T { + const fullOptions = { + defaultValue: options.defaultValue, + polymerProperty: key, + useLocalStorage: false, + ...options, + }; + return function () { + const uriStorageName = getURIStorageName(this, key); + // setComponentValue will be called every time the underlying storage + // changes and is responsible for ensuring that new state will propagate + // to the component with specified property. It is important that this + // function does not re-assign needlessly, to avoid Polymer observer + // churn. + const setComponentValue = (): void => { + const storedValue = get(uriStorageName, fullOptions); + const currentValue = this[fullOptions.polymerProperty]; + if (!_.isEqual(storedValue, currentValue)) { + this[fullOptions.polymerProperty] = storedValue; + } + }; + const addListener = fullOptions.useLocalStorage ? addStorageListener : addHashListener; + const listenKey = addListener(() => setComponentValue()); + if (fullOptions.useLocalStorage) { + storageListeners.push(listenKey); + } else { + hashListeners.push(listenKey); + } + // Set the value on the property. + setComponentValue(); + return this[fullOptions.polymerProperty]; + }; + } + function disposeBinding(): void { + hashListeners.forEach((key) => removeHashListenerByKey(key)); + storageListeners.forEach((key) => removeStorageListenerByKey(key)); + } + function getObserver(key: string, options: StorageOptions): () => void { + const fullOptions = { + defaultValue: options.defaultValue, + polymerProperty: key, + useLocalStorage: false, + ...options, + }; + return function () { + const uriStorageName = getURIStorageName(this, key); + const newVal = this[fullOptions.polymerProperty]; + set(uriStorageName, newVal, fullOptions); + }; + } + return { get, set, getInitializer, getObserver, disposeBinding }; +} +/** + * Get a unique storage name for a (Polymer component, propertyName) tuple. + * + * DISAMBIGUATOR must be set on the component, if other components use the + * same propertyName. + */ +function getURIStorageName(component: Record, propertyName: string): string { + const d = component[DISAMBIGUATOR]; + const components = d == null ? [propertyName] : [d, propertyName]; + return components.join('.'); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/storage_utils.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/storage_utils.ts new file mode 100644 index 000000000..59619ca08 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/storage_utils.ts @@ -0,0 +1,121 @@ +/* Copyright 2021 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import { getFakeHash, setFakeHash, useHash } from '../tf_globals/globals'; +import { addHashListener } from './listeners'; + +/** + * A keyword that users cannot use, since TensorBoard uses this to store info + * about the active tab. + */ +export const TAB_KEY = '__tab__'; + +export interface StringDict { + [key: string]: string; +} + +// Keep an up-to-date store of URL params, which iframed plugins can request. +let urlDict: StringDict = {}; + +export function getUrlDict(): StringDict { + return urlDict; +} + +export function updateUrlDict(dict: StringDict): void { + urlDict = dict; +} + +addHashListener(() => { + urlDict = componentToDict(readComponent()); +}); + +/** + * Read component from URI (e.g. returns "events&runPrefix=train*"). + */ +export function readComponent(): string { + return useHash() ? window.location.hash.slice(1) : getFakeHash(); +} + +/** + * Convert a URI Component into a dictionary of strings. + * Component should consist of key-value pairs joined by a delimiter + * with the exception of the tabName. + * Returns dict consisting of all key-value pairs and + * dict[TAB] = tabName + */ +export function componentToDict(component: string): StringDict { + const items = {} as StringDict; + const tokens = component.split('&'); + tokens.forEach((token) => { + const kv = token.split('='); + // Special backwards compatibility for URI components like #scalars. + if (kv.length === 1) { + items[TAB_KEY] = kv[0]; + } else if (kv.length === 2) { + items[decodeURIComponent(kv[0])] = decodeURIComponent(kv[1]); + } + }); + return items; +} + +/** + * Write component to URI. + */ +export function writeComponent(component: string, useLocationReplace = false): void { + if (useHash()) { + if (useLocationReplace) { + const url = new URL(window.location.href); + url.hash = component; + window.history.replaceState(window.history.state, '', url.toString()); + } else { + window.location.hash = component; + } + } else { + setFakeHash(component); + } +} + +/** + * Convert dictionary of strings into a URI Component. + * All key value entries get added as key value pairs in the component, + * with the exception of a key with the TAB value, which if present + * gets prepended to the URI Component string for backwards compatibility + * reasons. + */ +export function dictToComponent(items: StringDict): string { + let component = ''; + // Add the tab name e.g. 'events', 'images', 'histograms' as a prefix + // for backwards compatbility. + if (items[TAB_KEY] !== undefined) { + component += items[TAB_KEY]; + } + // Join other strings with &key=value notation + const nonTab = Object.keys(items) + .map((key) => [key, items[key]]) + .filter((pair) => pair[0] !== TAB_KEY) + .map((pair) => { + return `${encodeURIComponent(pair[0])}=${encodeURIComponent(pair[1])}`; + }) + .join('&'); + return nonTab.length > 0 ? `${component}&${nonTab}` : component; +} + +/** + * Delete a key from the URI. + */ +export function unsetFromURI(key, useLocationReplace = false): void { + const items = componentToDict(readComponent()); + delete items[key]; + writeComponent(dictToComponent(items), useLocationReplace); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/tf-storage-polymer.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/tf-storage-polymer.ts new file mode 100644 index 000000000..8b0dd8a2c --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_storage/tf-storage-polymer.ts @@ -0,0 +1,23 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +import { customElement } from '@polymer/decorators'; +import { PolymerElement } from '@polymer/polymer'; +import * as tf_storage from './index'; + +@customElement('tf-storage') +class TfStorage extends PolymerElement { + override _template = null; + tf_storage = tf_storage; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_wbr_string/tf-wbr-string.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_wbr_string/tf-wbr-string.ts new file mode 100644 index 000000000..e6bc56fdf --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_wbr_string/tf-wbr-string.ts @@ -0,0 +1,62 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +import { computed, customElement, property } from '@polymer/decorators'; +import { html, PolymerElement } from '@polymer/polymer'; + +// tf-wbr-string safely renders a string, with word break elements inserted +// after substrings that match a regular expression pattern. +@customElement('tf-wbr-string') +class TfWbrString extends PolymerElement { + static readonly template = html` + + + `; + + @property({ type: String }) + value: string = ''; + + /** + * Regular expression pattern for specifying delimiters. elements + * are inserted after all nonoverlapping matches. A match that is + * overlapped by another match further to the left is ignored. Empty + * matches will consume the remainder of the string so it is advised + * to not allow empty matches in your pattern. + */ + @property({ type: String }) + delimiterPattern: string = ''; + + @computed('value', 'delimiterPattern') + get _parts(): unknown[] { + let value = this.value; + let delimiterPattern = this.delimiterPattern; + const result: string[] = []; + while (true) { + const delimiterRegExp = new RegExp(delimiterPattern, 'g'); + delimiterRegExp.test(value); + if (delimiterRegExp.lastIndex === 0) { + result.push(value); + break; + } else { + result.push(value.slice(0, delimiterRegExp.lastIndex)); + value = value.slice(delimiterRegExp.lastIndex); + } + } + return result; + } +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/types/service.d.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/types/service.d.ts new file mode 100644 index 000000000..a8061fc01 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/types/service.d.ts @@ -0,0 +1,57 @@ +/* Copyright (c) 2025, Huawei Technologies. + * All rights reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +/** + * /mactch 接口返回值 + * @typedef {Object} mactchResult + * @property {boolean} success 是否匹配成功 + * @property {string} error 错误信息 + * @property {Object} data 匹配成功的数据 + */ +export interface MactchResult { + success: boolean; + error?: string; + data?: []; + result?: { + NPU_node_name: string; + max_precision_error: string; + inputData: { + [key: string]: { + 'Max diff': number; + 'Min diff': number; + 'Mean diff': number; + 'L2norm diff': number; + MaxRelativeErr: number; + MinRelativeErr: number; + MeanRelativeErr: number; + NormRelativeErr: number; + }; + }; + outputData: { + [key: string]: { + 'Max diff': number; + 'Min diff': number; + 'Mean diff': number; + 'L2norm diff': number; + MaxRelativeErr: number; + MinRelativeErr: number; + MeanRelativeErr: number; + NormRelativeErr: number; + }; + }; + result_array: []; + }; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/vz_sorting/sorting.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/vz_sorting/sorting.ts new file mode 100644 index 000000000..b45bb38e1 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/vz_sorting/sorting.ts @@ -0,0 +1,110 @@ +/* Copyright 2016 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ +/** + * Compares tag names asciinumerically broken into components. + * + *

    This is the comparison function used for sorting most string values in + * TensorBoard. Unlike the standard asciibetical comparator, this function + * knows that 'a10b' > 'a2b'. Fixed point and engineering notation are + * supported. This function also splits the input by slash and underscore to + * perform array comparison. Therefore it knows that 'a/a' < 'a+/a' even + * though '+' < '/' in the ASCII table. + */ +export function compareTagNames(a, b: string): number { + let ai = 0; + let bi = 0; + while (true) { + if (ai === a.length) { + return bi === b.length ? 0 : -1; + } + if (bi === b.length) { + return 1; + } + if (isDigit(a[ai]) && isDigit(b[bi])) { + const ais = ai; + const bis = bi; + ai = consumeNumber(a, ai + 1); + bi = consumeNumber(b, bi + 1); + const an = parseFloat(a.slice(ais, ai)); + const bn = parseFloat(b.slice(bis, bi)); + if (an < bn) { + return -1; + } + if (an > bn) { + return 1; + } + continue; + } + if (isBreak(a[ai])) { + if (!isBreak(b[bi])) { + return -1; + } + } else if (isBreak(b[bi])) { + return 1; + } else if (a[ai] < b[bi]) { + return -1; + } else if (a[ai] > b[bi]) { + return 1; + } else { } + ai++; + bi++; + } +} + +function consumeNumber(s: string, i: number): number { + enum State { + NATURAL = 0, + REAL = 1, + EXPONENT_SIGN = 2, + EXPONENT = 3, + } + let state = State.NATURAL; + for (; i < s.length; i++) { + if (state === State.NATURAL) { + if (s[i] === '.') { + state = State.REAL; + } else if (s[i] === 'e' || s[i] === 'E') { + state = State.EXPONENT_SIGN; + } else if (!isDigit(s[i])) { + break; + } else { } + } else if (state === State.REAL) { + if (s[i] === 'e' || s[i] === 'E') { + state = State.EXPONENT_SIGN; + } else if (!isDigit(s[i])) { + break; + } else { } + } else if (state === State.EXPONENT_SIGN) { + if (isDigit(s[i]) || s[i] === '+' || s[i] === '-') { + state = State.EXPONENT; + } else { + break; + } + } else if (state === State.EXPONENT) { + if (!isDigit(s[i])) { + break; + } + } else { } + } + return i; +} + +function isDigit(c: string): boolean { + return c >= '0' && c <= '9'; +} + +function isBreak(c: string): boolean { + return c === '/' || c === '_' || isDigit(c); +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/tsconfig.json b/plugins/tensorboard-plugins/tb_graph_ascend/fe/tsconfig.json new file mode 100644 index 000000000..89892c562 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/tsconfig.json @@ -0,0 +1,24 @@ +{ + "compilerOptions": { + "downlevelIteration": true, + "emitDecoratorMetadata": true, + "exactOptionalPropertyTypes": true, + "experimentalDecorators": true, + "importHelpers": true, + "inlineSourceMap": true, + "lib": [ + "dom", + "ES2022", + "dom.iterable" + ], + "noImplicitAny": false, + "moduleResolution": "node", + "module": "ES2022", + "noFallthroughCasesInSwitch": true, + "noImplicitReturns": true, + "noImplicitOverride": true, + "skipLibCheck": true, + "strict": true, + "target": "es2018" + } +} \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/webpack.config.js b/plugins/tensorboard-plugins/tb_graph_ascend/fe/webpack.config.js new file mode 100644 index 000000000..c7c0115bc --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/webpack.config.js @@ -0,0 +1,66 @@ +/* ------------------------------------------------------------------------- + Copyright (c) 2024, Huawei Technologies. + All rights reserved. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +--------------------------------------------------------------------------------------------*/ + +const path = require('path'); +const HtmlWebpackPlugin = require('html-webpack-plugin'); +const { CleanWebpackPlugin } = require('clean-webpack-plugin'); +const InlineChunkHtmlPlugin = require('inline-chunk-html-plugin'); + +module.exports = { + entry: { + app: './src/index', + }, + output: { + filename: 'index.js', + path: path.resolve(__dirname, 'dist'), + }, + module: { + rules: [ + { + test: /\.(html)$/, + use: { + loader: 'html-loader', + }, + }, + { + test: /\.ts?$/, + use: { + loader: 'ts-loader', + options: { + transpileOnly: true, + }, + }, + exclude: /node_modules/, + }, + { + test: /\.css$/i, + use: ['style-loader', 'css-loader'], + }, + ], + }, + resolve: { + extensions: ['.ts', '.js'], + }, + plugins: [ + new CleanWebpackPlugin(), + new HtmlWebpackPlugin({ + inject: 'body', + template: './index.html', + }), + new InlineChunkHtmlPlugin(HtmlWebpackPlugin, [/.*/]), + ], +}; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/__init__.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/__init__.py new file mode 100644 index 000000000..767773499 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2024, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/__init__.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/__init__.py new file mode 100644 index 000000000..ee2432f47 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/__init__.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/__init__.py new file mode 100644 index 000000000..ee2432f47 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py new file mode 100644 index 000000000..4707e1cd6 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py @@ -0,0 +1,257 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== + +from ..utils.graph_utils import GraphUtils +from ..utils.global_state import ADD_MATCH_KEYS + + +class MatchNodesController: + + @staticmethod + def process_md5_task_add(graph_data, npu_node_name, bench_node_name): + npu_match_nodes_list = graph_data.get('npu_match_nodes', {}) + bench_match_nodes_list = graph_data.get('bench_match_nodes', {}) + npu_node_data = graph_data.get('NPU', {}).get('node', {}).get(npu_node_name) + bench_node_data = graph_data.get('Bench', {}).get('node', {}).get(bench_node_name) + # 去除节点名称前缀 + npu_input_data = GraphUtils.remove_prefix(npu_node_data.get('input_data', {}), npu_node_name + '.') + bench_input_data = GraphUtils.remove_prefix(bench_node_data.get('input_data', {}), bench_node_name + '.') + npu_output_data = GraphUtils.remove_prefix(npu_node_data.get('output_data', {}), npu_node_name + '.') + bench_output_data = GraphUtils.remove_prefix(bench_node_data.get('output_data', {}), bench_node_name + '.') + # 计算精度误差 + precision_input_error = MatchNodesController.calculate_md5_diff(npu_input_data, bench_input_data) + precision_output_error = MatchNodesController.calculate_md5_diff(npu_output_data, bench_output_data) + precision_error = precision_input_error and precision_output_error + # 在原始数据上，添加匹配节点，和匹配节点信息 + npu_node_data['matched_node_link'] = [bench_node_name] + bench_node_data['matched_node_link'] = [npu_node_name] + npu_node_data['data']['precision_index'] = precision_error + # 后端维护一个匹配节点列表，前端展示 + npu_match_nodes_list[npu_node_name] = bench_node_name + bench_match_nodes_list[bench_node_name] = npu_node_name + graph_data['npu_match_nodes'] = npu_match_nodes_list + graph_data['bench_match_nodes'] = bench_match_nodes_list + return { + 'success': True, + 'data': { + 'precision_error': precision_error, + }, + } + + @staticmethod + def process_md5_task_delete(graph_data, npu_node_name, bench_node_name): + npu_match_nodes_list = graph_data.get('npu_match_nodes', {}) + bench_match_nodes_list = graph_data.get('bench_match_nodes', {}) + npu_node_data = graph_data.get('NPU', {}).get('node', {}).get(npu_node_name) + bench_node_data = graph_data.get('Bench', {}).get('node', {}).get(bench_node_name) + # 在原始数据上，删除匹配节点，和匹配节点信息 + npu_node_data['matched_node_link'] = [] + bench_node_data['matched_node_link'] = [] + # 后端维护一个匹配节点列表，前端展示 + try: + del npu_node_data['data']['precision_index'] + del npu_match_nodes_list[npu_node_name] + del bench_match_nodes_list[bench_node_name] + except KeyError: + return { + 'success': False, + 'error': "操作失败：删除节点信息失败", + } + graph_data['npu_match_nodes'] = npu_match_nodes_list + graph_data['bench_match_nodes'] = bench_match_nodes_list + return { + 'success': True, + 'data': {}, + } + + @staticmethod + def process_summary_task_add(graph_data, npu_node_name, bench_node_name): + npu_match_nodes_list = graph_data.get('npu_match_nodes', {}) + bench_match_nodes_list = graph_data.get('bench_match_nodes', {}) + npu_node_data = graph_data.get('NPU', {}).get('node', {}).get(npu_node_name) + bench_node_data = graph_data.get('Bench', {}).get('node', {}).get(bench_node_name) + # 计算统计误差 + intput_statistical_diff = MatchNodesController.calculate_statistical_diff( + npu_node_data.get('input_data'), bench_node_data.get('input_data'), npu_node_name, bench_node_name + ) + output_statistical_diff = MatchNodesController.calculate_statistical_diff( + npu_node_data.get('output_data'), bench_node_data.get('output_data'), npu_node_name, bench_node_name + ) + # 计算精度误差 + precision_error = MatchNodesController.calculate_max_relative_error(output_statistical_diff) + # 有一个没有匹配上，则认为匹配失败 + if not intput_statistical_diff or not output_statistical_diff: + return { + 'success': False, + 'error': '输入或输出统计误差值为空(Input and output statistical error calculation failed)', + } + + if precision_error == -1: + return { + 'success': False, + 'error': '输出统计误差值为空，计算精度误差失败(Calculation of precision error failed)', + } + # 在原始数据上，添加匹配节点，和匹配节点信息 + npu_node_data['matched_node_link'] = [bench_node_name] + bench_node_data['matched_node_link'] = [npu_node_name] + MatchNodesController.update_graph_node_data(npu_node_data.get('input_data'), intput_statistical_diff) + MatchNodesController.update_graph_node_data(npu_node_data.get('output_data'), output_statistical_diff) + npu_node_data['data']['precision_index'] = precision_error + # 后端维护一个匹配节点列表，前端展示 + npu_match_nodes_list[npu_node_name] = bench_node_name + bench_match_nodes_list[bench_node_name] = npu_node_name + graph_data['npu_match_nodes'] = npu_match_nodes_list + graph_data['bench_match_nodes'] = bench_match_nodes_list + return { + 'success': True, + 'data': { + 'precision_error': precision_error, + 'intput_statistical_diff': intput_statistical_diff, + 'output_statistical_diff': output_statistical_diff, + }, + } + + @staticmethod + def process_summary_task_delete(graph_data, npu_node_name, bench_node_name): + npu_match_nodes_list = graph_data.get('npu_match_nodes', {}) + bench_match_nodes_list = graph_data.get('bench_match_nodes', {}) + npu_node_data = graph_data.get('NPU', {}).get('node', {}).get(npu_node_name) + bench_node_data = graph_data.get('Bench', {}).get('node', {}).get(bench_node_name) + # 在原始数据上，删除匹配节点，和匹配节点信息 + npu_node_data['matched_node_link'] = [] + bench_node_data['matched_node_link'] = [] + + MatchNodesController.delete_matched_node_data(npu_node_data.get('input_data')) + MatchNodesController.delete_matched_node_data(npu_node_data.get('output_data')) + # 后端维护一个匹配节点列表，前端展示 + try: + del npu_node_data['data']['precision_index'] + del npu_match_nodes_list[npu_node_name] + del bench_match_nodes_list[bench_node_name] + except KeyError: + return { + 'success': False, + 'error': "操作失败：删除节点信息失败", + } + graph_data['npu_match_nodes'] = npu_match_nodes_list + graph_data['bench_match_nodes'] = bench_match_nodes_list + return { + 'success': True, + 'data': {}, + } + + @staticmethod + def calculate_statistical_diff(npu_data, bench_data, npu_node_name, bench_node_name): + result = {} + # 去除节点名称前缀并转化为列表形式 + npu_data_simple = list(GraphUtils.remove_prefix(npu_data, npu_node_name + '.').values()) + bench_data_simple = list(GraphUtils.remove_prefix(bench_data, bench_node_name + '.').values()) + npu_data_keys = list(GraphUtils.remove_prefix(npu_data, npu_node_name + '.').keys()) + # 使用 zip 只对比最短的列表长度 + for npu_values, bench_values in zip(npu_data_simple, bench_data_simple): + npu_max = GraphUtils.convert_to_float(npu_values.get('Max', float('nan'))) + bench_max = GraphUtils.convert_to_float(bench_values.get('Max', float('nan'))) + npu_min = GraphUtils.convert_to_float(npu_values.get('Min', float('nan'))) + bench_min = GraphUtils.convert_to_float(bench_values.get('Min', float('nan'))) + npu_norm = GraphUtils.convert_to_float(npu_values.get('Norm', float('nan'))) + bench_norm = GraphUtils.convert_to_float(bench_values.get('Norm', float('nan'))) + npu_mean = GraphUtils.convert_to_float(npu_values.get('Mean', float('nan'))) + bench_mean = GraphUtils.convert_to_float(bench_values.get('Mean', float('nan'))) + + # Calculate absolute differences + max_diff_abs = abs(npu_max - bench_max) + min_diff_abs = abs(npu_min - bench_min) + norm_diff_abs = abs(npu_norm - bench_norm) + mean_diff_abs = abs(npu_mean - bench_mean) + + # Calculate relative differences (avoid division by zero) + max_diff_rel = abs(max_diff_abs / (bench_max if bench_max != 0 else 1)) + min_diff_rel = abs(min_diff_abs / (bench_min if bench_min != 0 else 1)) + norm_diff_rel = abs(norm_diff_abs / (bench_norm if bench_norm != 0 else 1)) + mean_diff_rel = abs(mean_diff_abs / (bench_mean if bench_mean != 0 else 1)) + + # 将结果记录到字典中 + result[npu_node_name + '.' + npu_data_keys[len(result)]] = dict( + zip( + ADD_MATCH_KEYS, + [ + max_diff_abs, + min_diff_abs, + mean_diff_abs, + norm_diff_abs, + max_diff_rel, + min_diff_rel, + mean_diff_rel, + norm_diff_rel, + ], + ) + ) + + return result + + # 计算最大相对误差 + @staticmethod + def calculate_max_relative_error(result): + max_rel_error = -1 + for _, diff_values in result.items(): + max_diff_rel = diff_values.get('MaxRelativeErr', float('nan')) + min_diff_rel = diff_values.get('MinRelativeErr', float('nan')) + norm_diff_rel = diff_values.get('NormRelativeErr', float('nan')) + mean_diff_rel = diff_values.get('MeanRelativeErr', float('nan')) + + max_rel_error_for_key = max(max_diff_rel, min_diff_rel, norm_diff_rel, mean_diff_rel) + max_rel_error = max(max_rel_error, max_rel_error_for_key) + + return min(max_rel_error, 1) + + @staticmethod + def calculate_md5_diff(npu_data, bench_data): + # 对比每个NPU和Bench所有数据md值，如果有一个不一样则返回0,否则返回1 + for key in zip(npu_data, npu_data): + npu_md5 = npu_data[key].get('md5', '') + bench_md5 = bench_data[key].get('md5', '') + if npu_md5 != bench_md5: + return 0 + return 1 + + @staticmethod + def update_graph_node_data(graph_npu_node_data, statistical_diff): + if not statistical_diff or not graph_npu_node_data: + return + for key, diff_values in statistical_diff.items(): + # 格式化相对误差字段 + for field in ['MaxRelativeErr', 'MinRelativeErr', 'NormRelativeErr', 'MeanRelativeErr']: + diff_values[field] = GraphUtils.format_relative_err(diff_values.get(field, float('nan'))) + + # 转换 absErr 为 NaN 字符串 + for field in ['MaxAbsErr', 'MinAbsErr', 'MeanAbsErr', 'NormAbsErr']: + diff_values[field] = GraphUtils.nan_to_str(diff_values.get(field, float('nan'))) + if key in graph_npu_node_data: + graph_npu_node_data[key].update(diff_values) + else: + graph_npu_node_data[key] = diff_values + + @staticmethod + def delete_matched_node_data(graph_npu_node_data): + keys_to_remove = ADD_MATCH_KEYS + # 遍历graph_npu_node_data中的每个主键和对应的子字典 + for key, fild_obj in graph_npu_node_data.items(): + # 使用字典解析创建新的子字典，排除不需要的键 + graph_npu_node_data[key] = { + sub_key: value + for sub_key, value in fild_obj.items() + if sub_key not in keys_to_remove + } diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/service/__init__.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/service/__init__.py new file mode 100644 index 000000000..ee2432f47 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/service/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/service/graph_service.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/service/graph_service.py new file mode 100644 index 000000000..5a1748f8b --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/service/graph_service.py @@ -0,0 +1,96 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== + +from ..utils.graph_utils import GraphUtils +from ..controllers.match_nodes_controller import MatchNodesController + + +class GraphService: + + @staticmethod + def get_node_info(node_info, meta_data): + graph_data, error_message = GraphUtils.get_graph_data(meta_data) + if error_message: + return {'success': False, 'error': error_message} + + node_type = node_info.get('nodeType') + node_name = node_info.get('nodeName') + node_details = graph_data.get(node_type, {}).get('node', {}).get(node_name) + return {'success': True, 'data': node_details} + + @staticmethod + def add_match_nodes(npu_node_name, bench_node_name, meta_data): + graph_data, error_message = GraphUtils.get_graph_data(meta_data) + if error_message: + return {'success': False, 'error': error_message} + + task = graph_data.get('task') + # 根据任务类型计算误差 + if task == 'md5': + result = MatchNodesController.process_md5_task_add(graph_data, npu_node_name, bench_node_name) + return result + elif task == 'summary': + result = MatchNodesController.process_summary_task_add(graph_data, npu_node_name, bench_node_name) + return result + else: + return {'success': False, 'error': '任务类型不支持(Task type not supported) '} + + @staticmethod + def delete_match_nodes(npu_node_name, bench_node_name, meta_data): + graph_data, error_message = GraphUtils.get_graph_data(meta_data) + if error_message: + return {'success': False, 'error': error_message} + + task = graph_data.get('task') + # 根据任务类型计算误差 + if task == 'md5': + result = MatchNodesController.process_md5_task_delete(graph_data, npu_node_name, bench_node_name) + return result + elif task == 'summary': + result = MatchNodesController.process_summary_task_delete(graph_data, npu_node_name, bench_node_name) + return result + else: + return {'success': False, 'error': '任务类型不支持(Task type not supported) '} + + @staticmethod + def get_matched_state_list(meta_data): + graph_data, error_message = GraphUtils.get_graph_data(meta_data) + if error_message: + return {'success': False, 'error': error_message} + + npu_match_nodes_list = graph_data.get('npu_match_nodes', {}) + bench_match_nodes_list = graph_data.get('bench_match_nodes', {}) + return { + 'success': True, + 'data': { + 'npu_match_nodes': npu_match_nodes_list, + 'bench_match_nodes': bench_match_nodes_list, + }, + } + + @staticmethod + def save_data(meta_data): + graph_data, error_message = GraphUtils.get_graph_data(meta_data) + if error_message: + return {'success': False, 'error': error_message} + + run = meta_data.get('run') + tag = meta_data.get('tag') + try: + GraphUtils.save_data(graph_data, run, tag) + except (ValueError, IOError, PermissionError) as e: + return {'success': False, 'error': f"Error: {e}"} + return {'success': True} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/__init__.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/__init__.py new file mode 100644 index 000000000..ee2432f47 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/global_state.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/global_state.py new file mode 100644 index 000000000..3eeeab556 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/global_state.py @@ -0,0 +1,61 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== +import re + +# 模块级全局变量 + +ADD_MATCH_KEYS = [ + 'MaxAbsErr', + 'MinAbsErr', + 'MeanAbsErr', + 'NormAbsErr', + 'MaxRelativeErr', + 'MinRelativeErr', + 'MeanRelativeErr', + 'NormRelativeErr', +] +FILE_NAME_REGEX = r'^[a-zA-Z0-9_\-\.]+$' # 文件名正则表达式 + +_state = {'logdir': '', "current_tag": '', "current_file_path": '', 'current_file_data': {}} + + +def init_defaults(): + """ + 初始化全局变量的默认值 + """ + global _state + _state = {'logdir': '', "current_tag": '', "current_file_path": '', 'current_file_data': {}} + + +def set_global_value(key, value): + """ + 设置全局变量的值 + """ + _state[key] = value + + +def get_global_value(key, default=None): + """ + 获取全局变量的值 + """ + return _state.get(key, default) + + +def reset_global_state(): + """ + 重置所有全局变量为默认值 + """ + init_defaults() diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py new file mode 100644 index 000000000..ba21454bf --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py @@ -0,0 +1,177 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== + +import math +import os +import json +import re +import stat + +from tensorboard.util import tb_logging +from .global_state import get_global_value, set_global_value, FILE_NAME_REGEX + +logger = tb_logging.get_logger() +MAX_FILE_SIZE = 1024 * 1024 * 1024 # 最大文件大小限制为1GB + + +class GraphUtils: + + @staticmethod + def get_graph_data(meta_data): + run = meta_data.get('run') + tag = meta_data.get('tag') + graph_data = GraphUtils.check_jsondata(tag) + if graph_data is None: + return GraphUtils.get_jsondata(run, tag) # 直接返回获取结果 + return graph_data, None + + # 检查是否使用缓存 + @staticmethod + def check_jsondata(tag): + _current_tag = get_global_value('current_tag') + if _current_tag == tag: + return get_global_value('current_file_data') + else: + return None + + # 读取json文件 + @staticmethod + def get_jsondata(run, tag): + json_data = None + error_message = None + logdir = get_global_value('logdir') + if run is None or tag is None: + error_message = 'The query parameters "run" and "tag" are required' + return json_data, error_message + run_dir = os.path.join(logdir, run) + run_dir = os.path.normpath(run_dir) # 标准化路径 + file_path = GraphUtils._load_json_file(run_dir, tag) + if not file_path: + error_message = f'vis file for tag "{tag}" not found in run "{run}"' + return json_data, error_message + json_data = GraphUtils._read_json_file(file_path) + set_global_value('current_file_data', json_data) + set_global_value('current_tag', tag) + if json_data is None: + error_message = f'Error reading vis file for tag "{tag}" in run "{run}"' + return json_data, error_message + + @staticmethod + def save_data(data, run, tag): + + # 检查 tag 是否为合法文件名 + if not re.match(FILE_NAME_REGEX, tag): + raise ValueError(f"Invalid tag: {tag}.") from e + + # 检查 run 目录是否存在，如果不存在则创建 + if not os.path.exists(run): + try: + os.makedirs(run, exist_ok=True) + os.chmod(run, stat.S_IRWXU | stat.S_IRGRP | stat.S_IXGRP) + except OSError as e: + raise PermissionError(f"Failed to create directory: {run}. Error: {e}\n") from e + + # 检查 data 是否为有效的 JSON 可序列化对象 + try: + json.dumps(data, ensure_ascii=False, indent=4) + except (TypeError, ValueError) as e: + raise ValueError(f"Invalid data: {e}") from e + + # 构建文件路径并标准化 + file_path = os.path.join(run, f"{tag}.vis") + file_path = os.path.normpath(file_path) + + # 检查文件路径是否合法，防止路径遍历攻击 + if not file_path.startswith(os.path.abspath(run)): + raise ValueError(f"Invalid file path: {file_path}. Potential path traversal attack.\n") + + # 权限校验：检查目录是否有写权限 + if not os.access(run, os.W_OK): + raise PermissionError(f"No write permission for directory: {run}\n") from e + + # 尝试写入文件 + try: + with open(file_path, "w", encoding="utf-8") as file: + json.dump(data, file, ensure_ascii=False, indent=4) + # 设置文件权限为仅所有者可读写 (0o600) + os.chmod(file_path, stat.S_IRUSR | stat.S_IWUSR) + except IOError as e: + raise IOError(f"Failed to write to file {file_path}: {e}\n") from e + + @staticmethod + def remove_prefix(node_data, prefix): + if node_data is None: + return {} + return {k[len(prefix):] if k.startswith(prefix) else k: v for k, v in node_data.items()} + + # 字符串转float + @staticmethod + def convert_to_float(value): + try: + # 尝试将值转换为float + return float(value) + except ValueError: + # 如果转换失败，返回默认值0.0 + return float('nan') + + @staticmethod + def format_relative_err(value): + """格式化相对误差为百分比，保留四位小数""" + if value is None or math.isnan(value): + return "NaN" + else: + return "{:.4%}".format(value) + + @staticmethod + def nan_to_str(value): + """将 NaN 转换为 'NaN' 字符串""" + return "NaN" if math.isnan(value) else value + + @staticmethod + def _load_json_file(run_dir, tag): + """Load a single .vis file from a given directory based on the tag.""" + file_path = os.path.join(run_dir, f"{tag}.vis") + file_path = os.path.normpath(file_path) # 标准化路径 + if os.path.exists(file_path): + # 校验文件的读权限 + if not os.access(file_path, os.R_OK): + logger.error(f'Error: No read permission for file "{file_path}"') + return None + # 校验文件大小 + if os.path.getsize(file_path) > MAX_FILE_SIZE: + logger.error(f'Error: File "{file_path}" exceeds the size limit of {MAX_FILE_SIZE // (1024 * 1024)}MB') + return None + set_global_value('current_file_path', file_path) + return file_path + else: + logger.error(f'Error: File "{file_path}" does not exist.') + return None + + @staticmethod + def _read_json_file(file_path): + """Read and parse a JSON file from disk.""" + if file_path and os.path.exists(file_path): + try: + with open(file_path, 'r', encoding='utf-8') as f: + # 尝试解析 JSON 文件 + return json.load(f) + except json.JSONDecodeError: + logger.error(f'Error: File "{file_path}" is not a valid JSON file!') + except Exception as e: + logger.error(f'Unexpected error while reading file "{file_path}": {e}') + else: + logger.error(f'Error: File "{file_path}" is not accessible.') + return None diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/views/__init__.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/views/__init__.py new file mode 100644 index 000000000..ee2432f47 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/views/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/views/graph_views.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/views/graph_views.py new file mode 100644 index 000000000..7588869c9 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/views/graph_views.py @@ -0,0 +1,68 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== + +import json +from werkzeug import wrappers, Response, exceptions +from tensorboard.backend import http_util +from ..service.graph_service import GraphService + + +class GraphView: + + # 获取当前节点对应节点的信息看板数据 + @staticmethod + @wrappers.Request.application + def get_node_info(request): + node_info = json.loads(request.args.get("nodeInfo")) + meta_data = json.loads(request.args.get("metaData")) + node_detail = GraphService.get_node_info(node_info, meta_data) + return http_util.Respond(request, node_detail, "application/json") + + # 添加匹配节点 + @staticmethod + @wrappers.Request.application + def add_match_nodes(request): + npu_node_name = json.loads(request.args.get("npuNodeName")) + beach_node_name = json.loads(request.args.get("beachNodeName")) + meta_data = json.loads(request.args.get("metaData")) + match_result = GraphService.add_match_nodes(npu_node_name, beach_node_name, meta_data) + return http_util.Respond(request, match_result, "application/json") + + # 取消节点匹配 + @staticmethod + @wrappers.Request.application + def delete_match_nodes(request): + npu_node_name = json.loads(request.args.get("npuNodeName")) + beach_node_name = json.loads(request.args.get("beachNodeName")) + meta_data = json.loads(request.args.get("metaData")) + match_result = GraphService.delete_match_nodes(npu_node_name, beach_node_name, meta_data) + return http_util.Respond(request, match_result, "application/json") + + # 获取匹配节点列表 + @staticmethod + @wrappers.Request.application + def get_matched_state_list(request): + meta_data = json.loads(request.args.get("metaData")) + matched_state_list = GraphService.get_matched_state_list(meta_data) + return http_util.Respond(request, matched_state_list, "application/json") + + # 保存匹配节点列表 + @staticmethod + @wrappers.Request.application + def save_data(request): + meta_data = json.loads(request.args.get("metaData")) + save_result = GraphService.save_data(meta_data) + return http_util.Respond(request, save_result, "application/json") diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/constants.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/constants.py new file mode 100644 index 000000000..04457951c --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/constants.py @@ -0,0 +1,52 @@ +# Copyright (c) 2024, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== + +MAX_FILE_SIZE = 1024 * 1024 * 1024 +PLUGIN_NAME = 'graph_ascend' +PLUGIN_NAME_RUN_METADATA_WITH_GRAPH = 'graph_ascend_run_metadata_graph' +SETS = { + 'Bench': ('Bench', 'B___', 'N___'), + 'NPU': ('NPU', 'N___', 'B___'), + 'B___': ('Bench', 'N___'), + 'N___': ('NPU', 'B___'), +} +NA_DATA = [ + ['Max diff', 'N/A'], + ['Min diff', 'N/A'], + ['Mean diff', 'N/A'], + ['L2norm diff', 'N/A'], + ['MaxRelativeErr', 'N/A'], + ['MinRelativeErr', 'N/A'], + ['MeanRelativeErr', 'N/A'], + ['NormRelativeErr', 'N/A'], +] +PREFIX_MAP = {'N___': 'NPU', 'B___': 'Bench'} +UNMATCH_NAME_SET = [ + 'Max diff', + 'Min diff', + 'Mean diff', + 'L2norm diff', + 'MaxRelativeErr', + 'MinRelativeErr', + 'MeanRelativeErr', + 'NormRelativeErr', + 'Cosine', + 'MaxAbsErr', + 'MaxRelativeErr', + 'One Thousandth Err Ratio', + 'Five Thousandth Err Ratio', +] +SCREEN_MAP = {'precision_index': 'precision_index', 'overflow_level': 'overflow_level'} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py new file mode 100644 index 000000000..5b3ad9c78 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py @@ -0,0 +1,649 @@ +# Copyright 2017 The TensorFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# Copyright (c) 2024, Huawei Technologies. +# Adapt to the model hierarchical visualization data collected by the msprobe tool +# ============================================================================== +"""The TensorBoard Graphs plugin.""" + +import json +import os +from werkzeug import wrappers, Response, exceptions +from tensorboard import errors +from tensorboard.backend import http_util +from tensorboard.plugins import base_plugin +from tensorboard.util import tb_logging + +from . import constants +from .app.views.graph_views import GraphView +from .app.utils.graph_utils import GraphUtils +from .app.utils.global_state import set_global_value + +logger = tb_logging.get_logger() + + +class GraphsPlugin(base_plugin.TBPlugin): + """Graphs Plugin for TensorBoard.""" + + plugin_name = constants.PLUGIN_NAME + headers = [('X-Content-Type-Options', 'nosniff')] + + def __init__(self, context): + """Instantiates GraphsPlugin via TensorBoard core. + + Args: + context: A base_plugin.TBContext instance. + """ + super().__init__(context) + self._data_provider = context.data_provider + self.logdir = os.path.abspath(os.path.expanduser(context.logdir.rstrip('/'))) + # 将logdir赋值给global_state中的logdir属性,方便其他模块使用 + set_global_value('logdir', os.path.abspath(os.path.expanduser(context.logdir.rstrip('/')))) + self._current_file_path = None # Store the path of the currently loaded file + self._current_file_data = None # Store the data of the currently loaded file + self._current_tag = None # Store the tag of the currently loaded file + self.batch_id = 0 # 将 batch_id 声明为实例变量 + self.step_id = 0 # 可以同样声明 step_id + self.dfs_node_ids = [] # batch和step没变的话就将所有的nodename存起来，方便快速读取 + self.check_batch_id = 0 # 来配合node_ids监察用的，他不变node_ids就不用重新读取了 + self.check_step_id = 0 # 同上 + self.check_tag = None + + def get_plugin_apps(self): + return { + '/index.js': self.static_file_route, + '/index.html': self.static_file_route, + "/info": self.info_route, + "/components": self.get_all_data, + "/expandnodes": self.get_all_upnodes, + "/screen": self.get_all_screen_nodes, + "/parent": self.get_parent_node, + "/rank": self.get_rank, + "/subgraph": self.subgraph_route, + '/getNodeInfo': GraphView.get_node_info, + '/addMatchNodes': GraphView.add_match_nodes, + '/deleteMatchNodes': GraphView.delete_match_nodes, + '/getMatchedStateList': GraphView.get_matched_state_list, + '/saveData': GraphView.save_data, + '/setNewColors': self.set_new_colors, + } + + def is_active(self): + """The graphs plugin is active iff any run has a graph.""" + for _, _, files in os.walk(self.logdir): + for file in files: + if file.endswith('.vis'): + return True + return False + + def data_plugin_names(self): + return ( + constants.PLUGIN_NAME, + constants.PLUGIN_NAME_RUN_METADATA_WITH_GRAPH, + ) + + def frontend_metadata(self): + return base_plugin.FrontendMetadata( + es_module_path='/index.js', + disable_reload=True, + ) + + def info_impl(self): + """Returns a dict of all runs and their data availabilities""" + result = {} + + def add_row_item(run, tag=None, is_vis=False): + run_item = result.setdefault( + run, + {"run": run, "tags": {}}, + ) + + tag_item = None + if tag: + tag_item = run_item.get("tags").setdefault( + tag, + { + "tag": tag, + "conceptual_graph": False, + "op_graph": False, + "profile": False, + }, + ) + return (run_item, tag_item) + + run_tag_pairs = self._get_run_dirs() + for run, tag in run_tag_pairs: + try: + add_row_item(run, tag, is_vis=True) + except ValueError as e: + logger.error(f"Warning: Skipping invalid run/tag pair ({run}, {tag}). Error: {e}") + + return result + + # 拿所有nodename的 + def get_all_node_names(self, json_data, request): + npu_ids, bench_ids = [], [] + try: + batch = request.args.get("batch") + step = request.args.get("step") + except ValueError: + logger.error('The param "batch" or "step" does not exist or not a valid value') + # 获取 NPU 和 Bench 数据 + npu_data = self.json_get(json_data, 'NPU') + bench_data = self.json_get(json_data, 'Bench') + + def extract_ids(nodes_data, id_list): + for node_name in nodes_data.get("node"): + id_list.append(node_name) + + def traverse_npu(subnodes): + for node in subnodes: + node_data = ( + self.json_get(npu_data, 'node', node) if npu_data else self.json_get(json_data, 'node', node) + ) + micro_step_id = str(node_data.get('micro_step_id')) + if micro_step_id == batch or micro_step_id is None: + npu_ids.append(node) + traverse_npu(node_data.get('subnodes', [])) + + # 提取 NPU 节点 ID + if batch == '-1' and step == '-1': + extract_ids(npu_data or json_data, npu_ids) + else: + root = (npu_data or json_data).get('root') + root_subnodes = self.json_get((npu_data or json_data), 'node', root, 'subnodes') + traverse_npu(root_subnodes) + + # 提取 Bench 节点 ID + if bench_data: + extract_ids(bench_data, bench_ids) + # 返回格式为 [[NPU节点ID列表], [Bench节点ID列表]] + return [npu_ids, bench_ids] + + def dfs_collect_nodes(self, json_data, request): + all_node_names = [] + try: + batch = request.args.get("batch") + step = request.args.get("step") + except ValueError: + logger.error('The param "batch" or "step" does not exist or not a valid value') + + def should_include_node(micro_step_id, step_id): + return (micro_step_id == batch or batch == '-1' or micro_step_id is None) and ( + step_id == step or step == '-1' or step_id is None + ) + + nodes_data = self.json_get(json_data, 'NPU', 'node') or self.json_get(json_data, 'node') + for node in nodes_data: + micro_step_id = self.json_get(nodes_data, node, 'micro_step_id') + step_id = self.json_get(nodes_data, node, 'step_id') + if should_include_node(micro_step_id, step_id) and not self.json_get(nodes_data, node, 'subnodes'): + all_node_names.append(node) + return all_node_names + + # 拿所有precisonNodes的，与controls的精度筛选联动 + @wrappers.Request.application + def get_all_screen_nodes(self, request): + grouped_screen_set, inaccuracy_node_ids = [], [] + precision_none = 0 + screen = '' + # 尝试获取 screen_set 和 screen 的值 + for key, value in constants.SCREEN_MAP.items(): + if request.args.get(key): + screen_set = request.args.get(key) + screen = value + break # 找到一个匹配的 key 后跳出循环 + + if screen == 'precision_index': + precision_set_str = screen_set.split(',') + if '无匹配节点' in precision_set_str: + precision_set_str = [p for p in precision_set_str if p != '无匹配节点'] + precision_none = 1 + grouped_screen_set = [ + list(map(float, precision_set_str[i: i + 2])) + for i in range(0, len(precision_set_str), 2) + ] + else: + grouped_screen_set = screen_set + tag = request.args.get("tag") + json_data = self.check_jsondata(request) + + def has_conditions_changed(tag): + return ( + self.check_batch_id != self.batch_id + or self.check_step_id != self.step_id + or self.check_tag != tag + or self.check_tag is None + ) + + if has_conditions_changed(tag): + self.dfs_node_ids = self.dfs_collect_nodes(json_data, request) + self.check_batch_id = self.batch_id + self.check_step_id = self.step_id + self.check_tag = tag + node_ids = self.dfs_node_ids + for node in node_ids: + node_data = self.json_get(json_data, 'NPU', 'node', node, 'data') or self.json_get( + json_data, 'node', node, 'data' + ) + matched = self.json_get(json_data, 'NPU', 'node', node, 'matched_node_link') or self.json_get( + json_data, 'node', node, 'matched_node_link' + ) + inaccuracy = node_data.get(screen) if node_data is not None else None + # 如果 inaccuracy 为 None，直接检查是否符合条件 + if inaccuracy is None and precision_none == 0: + continue # 跳过后续的处理，进入下一个 node + if inaccuracy is None and precision_none == 1: + if (node_data is None or node_data.get('overflow_level', False)) and not matched: + inaccuracy_node_ids.append(node) + continue # 跳过后续的处理，进入下一个 node + + # 对于 inaccuracy 是数字类型，检查是否在某个子范围内，精度误差 + if isinstance(inaccuracy, (int, float)): + for group in grouped_screen_set: + if all(g is not None for g in group) and group[0] <= inaccuracy <= group[1]: + inaccuracy_node_ids.append(node) + break # 找到符合条件的，跳出当前循环 + # 对于非数字的 inaccuracy，检查是否在 grouped_screen_set 中，溢出检测 + elif inaccuracy in grouped_screen_set: + inaccuracy_node_ids.append(node) + else: + logger.error(f'The inaccuracy in {node} is not a valid value') + + return http_util.Respond(request, inaccuracy_node_ids, "application/json") + + def group_precision_set(self, precision_set): + if len(precision_set) % 2 != 0: + raise ValueError('The number of elements in precision_set is not even') + grouped_precision_set = [precision_set[i: i + 2] for i in range(0, len(precision_set), 2)] + return grouped_precision_set + + def get_all_unmatched_nodes(self, all_node_names, json_data): + is_npu_present = 'NPU' in json_data + + def collect_unmatched_nodes(node_list, *path): + return [node for node in node_list if not self.json_get(json_data, *path, node, 'matched_node_link')] + + npu_unmatched = ( + collect_unmatched_nodes(all_node_names[0], 'NPU', 'node') + if is_npu_present + else collect_unmatched_nodes(all_node_names[0], 'node') + ) + bench_unmatched = collect_unmatched_nodes(all_node_names[1], 'Bench', 'node') if is_npu_present else [] + return [npu_unmatched, bench_unmatched] + + @wrappers.Request.application + def get_parent_node(self, request): + node = request.args.get("node")[4:] # 获取节点信息 + prefix = request.args.get("node")[:4] # 获取前缀 + json_data = self.check_jsondata(request) # 检查请求中的 JSON 数据 + + def find_upnode(node): + matched_node_link_list = self.json_get( + json_data, constants.PREFIX_MAP[prefix], 'node', node, 'matched_node_link' + ) + + if matched_node_link_list: + result = matched_node_link_list[-1] # 获取匹配的最后一个节点 + return http_util.Respond(request, result, "application/json") # 返回响应 + + # 如果没有找到 matched_node_link，继续递归查找上级节点 + else: + upnode = self.json_get(json_data, constants.PREFIX_MAP[prefix], 'node', node, 'upnode') + if upnode: + return find_upnode(upnode) # 递归查找上级节点 + else: + return http_util.Respond(request, {}, "application/json") # 如果没有找到上级节点，返回空响应 + + return find_upnode(node) + + # 多卡跳转后端的方法，负责拿到rank数据 + @wrappers.Request.application + def get_rank(self, request): + node_name = request.args.get('node') + side = request.args.get('side') + + # 构建 JSON 路径 + json_path = [side] if side else [] # 如果 side 存在，路径中包含 side + json_path.extend(['node', node_name, 'matched_distributed']) + + # 获取 matched_distributed + matched_distributed = self.json_get(self._current_file_data, *json_path) + + # 返回结果 + if matched_distributed: + return http_util.Respond(request, matched_distributed, "application/json") + else: + return http_util.Respond(request, {}, "application/json") + + # 拿json_data里面所有配置数据的 + @wrappers.Request.application + def get_all_data(self, request): + """Returns all data in json format.""" + keys = [] + response_data = {} + tag = request.args.get('tag') + json_data = self.check_jsondata(request) + if not json_data: + return http_util.Respond( + request, f"Failed to check file '{tag}', view the log for detail.", "text/plain", 400 + ) + self._current_file_data = json_data + all_node_names = self.get_all_node_names(json_data, request) + response_data['Menu'] = all_node_names + response_data['UnMatchedNode'] = self.get_all_unmatched_nodes(all_node_names, json_data) + for field in ['MicroSteps', 'StepList', 'match', 'ToolTip']: + if json_data.get(field, {}): + keys.append(field) + for key in keys: + if key == 'StepList' and 'ALL' not in json_data.get('StepList', {}): + json_data[key].insert(0, 'ALL') + response_data[key] = json_data.get(key, {}) + file_path = self._get_first_vis_file_path() + json_data = self._read_json_file(file_path) + if 'Colors' in json_data: + response_data['Colors'] = json_data.get('Colors', {}) + if 'OverflowCheck' in json_data: + response_data['OverflowCheck'] = json_data.get('OverflowCheck', {}) + return http_util.Respond(request, response_data, "application/json") + + # 设置新的精度误差颜色 + @wrappers.Request.application + def set_new_colors(self, request): + """Set new colors in jsondata.""" + try: + colors = json.loads(request.args.get('colors')) + file_path = self._get_first_vis_file_path() + json_data = self._read_json_file(file_path) + json_data['Colors'] = colors + with open(file_path, "w", encoding="utf-8") as file: + json.dump(json_data, file, ensure_ascii=False, indent=4) + # 返回成功响应 + response = {'success': True, 'error': None, 'data': {}} + return http_util.Respond(request, response, "application/json") + + except Exception as e: + # 返回错误响应 + response = {'success': False, 'error': str(e), 'data': None} + return http_util.Respond(request, response, "application/json") + + @wrappers.Request.application + def static_file_route(self, request): + filename = os.path.basename(request.path) + extension = os.path.splitext(filename)[1] + if extension == '.html': + mimetype = 'text/html' + elif extension == '.js': + mimetype = 'application/javascript' + else: + mimetype = 'application/octet-stream' + filepath = os.path.join(os.path.dirname(__file__), 'static', filename) + try: + with open(filepath, 'rb') as infile: + contents = infile.read() + except IOError as e: + raise exceptions.NotFound('404 Not Found') from e + return Response(contents, content_type=mimetype, headers=GraphsPlugin.headers) + + # 方便多层级展开的upnodes节点集合，与tf-graph的_menuSelectedNodeExpand联动 + @wrappers.Request.application + def get_all_upnodes(self, request): + npu_upnodes_list, matched_upnodes_list, node_list = [], [], [] + node, matched_node, prefix = '', '', '' + node_arg = request.args.get('node') + json_data = self.check_jsondata(request) + prefix = str(node_arg)[:4] if str(node_arg)[:4] in constants.PREFIX_MAP else '' + node = node_arg[4:] if prefix in constants.PREFIX_MAP else node_arg + if prefix in constants.PREFIX_MAP and json_data.get(constants.PREFIX_MAP[prefix], {}): + node_list = json_data[constants.PREFIX_MAP[prefix]].get('node', {}) + else: + node_list = json_data.get('node', {}) + matched_node = ( + node_list.get(node, {}).get('matched_node_link', [])[-1] + if node_list.get(node, {}).get('matched_node_link') + else None + ) + + def get_upnodes(node, prefix): + upnodes_list = [] + if prefix == '': + node_list = json_data.get('node', {}) + else: + node_list = json_data.get('NPU' if prefix == 'N___' else 'Bench', {}).get('node', {}) + while node in node_list: + upnode = node_list[node].get('upnode') + if not upnode or upnode == 'None': + break + upnodes_list.insert(0, upnode) + node = upnode + return upnodes_list + + npu_upnodes_list = get_upnodes(node, prefix) + # 如果 matched_node 是 None 的话 + if matched_node is None: + previous_node = None # 用于跟踪上一个 node + for node in reversed(npu_upnodes_list): + if node_list.get(node, {}).get('matched_node_link'): # 判断条件 + matched_node = previous_node # 将 matched_node 设置为上一个 node + break + previous_node = node # 更新 previous_node 为当前 node + if prefix in constants.PREFIX_MAP: + matched_upnodes_list = get_upnodes(matched_node, prefix) + return http_util.Respond(request, [[prefix], npu_upnodes_list, matched_upnodes_list], "application/json") + + # 检查到底是读一般还是用之前存的 + def check_jsondata(self, request): + tag = request.args.get("tag") + run = request.args.get('run') + graph_data = GraphUtils.check_jsondata(tag) + if graph_data is None: + graph_data, error_message = GraphUtils.get_jsondata(run, tag) + if error_message is not None: + logger.error(f"Failed to get json data: {error_message}") + return None + return graph_data + + # 处理xx.get + def json_get(self, data, *args): + result = data + for key in args: + if result is None: + return None + result = result.get(key) + return result + + # 获取子图数据，最核心且基本的所在 + @wrappers.Request.application + def subgraph_route(self, request): + """Returns a subgraph for a given node id, modified to use run and tag from query parameters.""" + json_data = self.check_jsondata(request) + if not json_data: + return http_util.Respond(request, "Failed to get subgraph, view the log for details.", "text/plain", 400) + node_id = request.args.get("node") + self.batch_id = request.args.get("batch") + self.step_id = request.args.get("step") + if node_id is None: + return http_util.Respond(request, 'The query parameter "node" is required', "text/plain", 400) + if node_id == 'root': + if json_data.get('Bench', {}): + subgraph_pbtxt_set = {} + for node_type in ('Bench', 'NPU'): + subgraph = {'node': {}, 'edge': {}} + node = self.json_get(json_data, constants.SETS[node_type][0], 'root') + node_data = self.json_get(json_data, constants.SETS[node_type][0], 'node', node) + node = constants.SETS[node_type][1] + node + matched_node_link = node_data['matched_node_link'] + if matched_node_link[0][:4] != constants.SETS[node_type][2]: + matched_node_link[0] = constants.SETS[node_type][2] + matched_node_link[0] + subgraph['node'][node] = node_data + subgraph_pbtxt_set[node_type] = self._convert_to_protobuf_format(subgraph) + subgraph_pbtxt = subgraph_pbtxt_set.get('NPU', '') + subgraph_pbtxt_set.get('Bench', '') + else: + subgraph = {'node': {}, 'edge': {}} + node = json_data.get('root') + node_data = self.json_get(json_data, 'node', node) + subgraph['node'][node] = node_data + subgraph_pbtxt = self._convert_to_protobuf_format(subgraph) + else: + subgraph = self._extract_subgraph(json_data, node_id) + subgraph_pbtxt = self._convert_to_protobuf_format(subgraph) + return http_util.Respond(request, subgraph_pbtxt, "text/x-protobuf") + + @wrappers.Request.application + def info_route(self, request): + info = self.info_impl() + return http_util.Respond(request, info, "application/json") + + # 同上二者一体 + def _extract_subgraph(self, json_data, node_id): + """提取子图，支持多种节点前缀逻辑""" + subgraph = {'node': {}, 'edge': []} + + # 检查前缀并获取节点集合 + prefix = node_id[:4] + if prefix in constants.SETS and len(prefix) == 4: + node_id = node_id[4:] + node_set = self.json_get(json_data, constants.SETS[prefix][0], 'node') + else: + prefix = '' + node_set = json_data.get('node', {}) + + # 获取当前节点数据 + node_data = node_set.get(node_id, {}) + subnodes = node_data.get('subnodes', []) + + # 遍历子节点 + for subnode_id in subnodes: + subnode_id_data = node_set.get(subnode_id, {}) + if subnode_id_data.get('micro_step_id') is not None: + self._process_subnode(subgraph, prefix, subnode_id, subnode_id_data, json_data) + else: + self._process_non_root_subnode(subgraph, prefix, subnode_id, subnode_id_data) + + return subgraph + + def _process_non_root_subnode(self, subgraph, prefix, subnode_id, subnode_id_data): + """处理非根子节点""" + # 更新匹配的节点链接 + self._update_matched_node_links(subnode_id_data, prefix) + + # 添加前缀并存入子图 + full_subnode_id = prefix + subnode_id + subgraph['node'][full_subnode_id] = subnode_id_data + + # 针对分micro_step_id和step_id取的部分节点 + def _process_subnode(self, subgraph, prefix, subnode_id, subnode_id_data, json_data): + batchid = subnode_id_data.get('micro_step_id') + stepid = subnode_id_data.get('step_id') + steplist = json_data.get('StepList') + + def should_update_node(): + """判断是否需要更新节点的条件逻辑""" + if self.batch_id == '-1': + if self.step_id == '-1': # batch_id 和 step_id 都为 -1 + return True + return stepid == str(steplist[int(self.step_id) + 1]) # 匹配 step_id + else: # batch_id 有效 + if self.step_id != '-1': # step_id 有效 + return batchid == int(self.batch_id) and stepid == str(steplist[int(self.step_id) + 1]) + return batchid == int(self.batch_id) # 仅匹配 batch_id + + if should_update_node(): + self._update_matched_node_links(subnode_id_data, prefix) + subnode_id = prefix + subnode_id + subgraph['node'][subnode_id] = subnode_id_data + + def _update_matched_node_links(self, subnode_id_data, prefix): + if 'matched_node_link' in subnode_id_data: + for index, matched_node_link in enumerate(subnode_id_data['matched_node_link']): + if matched_node_link[:4] != constants.SETS[prefix][1]: + matched_node_link = constants.SETS[prefix][1] + matched_node_link + subnode_id_data['matched_node_link'][index] = matched_node_link + + # 拼接成类json + def _convert_to_protobuf_format(self, subgraph): + """Converts subgraph data to the protobuf text format expected by the frontend.""" + nodes = subgraph.get('node', {}) + protobuf_format = "" + for node_id, node_data in nodes.items(): + protobuf_format += f'node {{\n name: "{node_id}"\n op: "{node_data.get("id")}"\n' + protobuf_format += f' node_type: {node_data.get("node_type", 0)}\n' + if node_data.get("matched_node_link"): + protobuf_format += f' matched_node_link: {node_data.get("matched_node_link")}\n' + protobuf_format += f' attr: "{node_data.get("data", "{}")}"\n'.replace('True', 'true').replace( + 'False', 'false' + ) + protobuf_format += f' precision_index: {(node_data.get("data", {}).get("precision_index"))}\n' + if node_data.get("input_data"): + protobuf_format += f' input_data: "{node_data.get("input_data", "{}")}"\n' + if node_data.get("output_data"): + protobuf_format += f' output_data: "{node_data.get("output_data", "{}")}"\n' + protobuf_format += f' suggestions: "{node_data.get("suggestions", "{}")}"\n' + if not node_data.get("subnodes"): + protobuf_format += f' isLeaf: true\n' + else: + protobuf_format += f' isLeaf: false\n' + protobuf_format += f' subnodes: {node_data.get("subnodes")}\n' + if node_data.get("stack_info"): + protobuf_format += f' stack_info: {node_data.get("stack_info")}\n' + protobuf_format += '}\n' + return protobuf_format + + def _get_run_dirs(self): + """Scan logdir for directories containing .vis files, modified to return a tuple of (run, tag).""" + run_tag_pairs = [] + for root, _, files in os.walk(self.logdir): + for file in files: + if file.endswith('.vis'): # check for .vis extension + run = os.path.abspath(root) + tag = os.path.splitext(file)[0] # Use the filename without extension as tag + file_path = os.path.join(root, file) + file_size = os.path.getsize(file_path) + if file_size > constants.MAX_FILE_SIZE: + logger.error( + f'Error: vis file "{file_path}" exceeds the maximum limit size of 1GB and will be skipped.' + ) + continue + run_tag_pairs.append((run, tag)) + return run_tag_pairs + + def _load_json_file(self, run_dir, tag): + """Load a single .vis file from a given directory based on the tag.""" + file_path = os.path.join(run_dir, f"{tag}.vis") + if os.path.exists(file_path): + # Store the path of the current file instead of loading it into memory + self._current_file_path = file_path + return file_path + return None + + def _read_json_file(self, file_path): + """Read and parse a JSON file from disk.""" + if file_path and os.path.exists(file_path): + with open(file_path, 'r', encoding='utf-8') as f: + try: + return json.load(f) + except Exception as e: + logger.error(f'Error: the vis file "{file_path}" is not a legal JSON file!') + else: + logger.error(f'Error: the vis file "{file_path}" is not a legal JSON file!') + return None + + def _get_first_vis_file_path(self): + for _, _, files in os.walk(self.logdir): + for file in files: + if file.endswith('.vis'): + tag = file.replace('.vis', '') + break + file_path = self._load_json_file(self.logdir, tag) + return file_path diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/static/index.js b/plugins/tensorboard-plugins/tb_graph_ascend/server/static/index.js new file mode 100644 index 000000000..e64f87ec8 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/static/index.js @@ -0,0 +1,6 @@ +/* + * Copyright (c) Huawei Technologies Co., Ltd. 2024-2024. All rights reserved. + */ +export async function render() { + document.location.href = 'index.html'; +} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/setup.py b/plugins/tensorboard-plugins/tb_graph_ascend/setup.py new file mode 100644 index 000000000..7cd68586c --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/setup.py @@ -0,0 +1,57 @@ +# ------------------------------------------------------------------------- +# Copyright (c) 2024, Huawei Technologies. +# All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# --------------------------------------------------------------------------------------------# +import setuptools + +VERSION = '1.0.0' +INSTALL_REQUIRED = ["tensorboard >= 2.11.2"] + +setuptools.setup( + name="tb-graph-ascend", + version=VERSION, + description="Model Hierarchical Visualization TensorBoard Plugin", + long_description="Model Hierarchical Visualization TensorBoard Plugin : \ + https://gitee.com/ascend/mstt/tree/master/plugins/tensorboard-plugins/tb_graph_ascend", + url="https://gitee.com/ascend/mstt/tree/master/plugins/tensorboard-plugins/tb_graph_ascend", + author="Ascend Team", + author_email="pmail_mindstudio@huawei.com", + packages=setuptools.find_packages(), + package_data={ + "server": ["static/**"], + }, + entry_points={ + "tensorboard_plugins": [ + "graph_ascend = server.plugin:GraphsPlugin", + ], + }, + python_requires=">=3.7", + install_requires=INSTALL_REQUIRED, + classifiers=[ + 'Intended Audience :: Developers', + 'Intended Audience :: Education', + 'Intended Audience :: Science/Research', + 'License :: OSI Approved :: BSD License', + 'Programming Language :: Python :: 3', + 'Topic :: Scientific/Engineering', + 'Topic :: Scientific/Engineering :: Mathematics', + 'Topic :: Scientific/Engineering :: Artificial Intelligence', + 'Topic :: Software Development', + 'Topic :: Software Development :: Libraries', + 'Topic :: Software Development :: Libraries :: Python Modules', + ], + license='BSD-3', + keywords='tensorboard graph ascend plugin', +) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py new file mode 100644 index 000000000..3d958e029 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py @@ -0,0 +1,488 @@ +# Copyright (c) 2025, Huawei Technologies. +# All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== + +import sys +import os +sys.path.append(os.path.pardir) +from unittest.mock import MagicMock, patch +import unittest +from server.plugin import GraphsPlugin + + +class TestGraphsPlugin(unittest.TestCase): + + @property + def plugin(self): + """提供对受保护实例属性 _plugin 的只读访问""" + return self._plugin + + @property + def instance(self): + """提供对受保护实例属性 _instance 的只读访问""" + return self._instance + + def setUp(self): + """在每个测试之前初始化环境""" + fake_context = MagicMock() + + # 创建 GraphsPlugin 实例并传递 context + self.plugin = GraphsPlugin(context=fake_context) + self.plugin._current_file_path = "" # 初始化文件路径 + self.plugin.batch_id = '-1' # 设置为 -1 来触发 _process_subnode 中的判断逻辑 + self.plugin.step_id = '-1' # 设置为 -1 来触发 _process_subnode 中的判断逻辑 + + self.plugin._current_file_data = { + "npu": { + "node": { + "npu_node_1": { + "matched_node_link": [] + } + } + }, + "bench": { + "node": { + "bench_node_1": { + "matched_node_link": [] + } + } + }, + "match": [], + 'task': 'md5' + } + + self.app = Flask(__name__) + self.app.debug = True + self.client = self.app.test_client() + + # 创建模拟的 data_provider + mock_data_provider = MagicMock() + mock_data_provider.some_method.return_value = "some_value" # 根据需要设置模拟的方法 + + # 创建一个模拟的 context，并将 mock_data_provider 赋值给它 + context = MagicMock() + context.data_provider = mock_data_provider + + # 使用 context 创建 GraphsPlugin 实例 + self._instance = GraphsPlugin(context=context) + + def test_get_all_node_name_with_valid_batch_and_step(self): + # 模拟 request.args + mock_request = MagicMock() + mock_request.args.get.return_value = '0' # 模拟 batch=0 和 step=0 + + # 构造 json_data + json_data = { + 'npu': { + 'root': 'root_node', + 'node': { + 'root_node': { + 'micro_step_id': 0, + 'subnodes': ['subnode1', 'subnode2'] + }, + 'subnode1': {'micro_step_id': 0}, + 'subnode2': {'micro_step_id': 0}, + } + }, + 'bench': { + 'node': { + 'bench1': {}, + 'bench2': {} + } + } + } + + # 调用 get_all_nodeName 方法 + npu_ids, bench_ids = self.plugin.get_all_node_names(json_data, mock_request) + + # 验证返回的 npu_ids 和 bench_ids + self.assertEqual(npu_ids, ['subnode1', 'subnode2']) + self.assertEqual(bench_ids, ['bench1', 'bench2']) + + def test_dfs_collect_nodes_with_valid_batch_and_step(self): + # 模拟 request.args + mock_request = MagicMock() + side_effect_dict = { + 'batch': '0', + 'step': '0' + } + + # 设置 mock_request.args.get 的 side_effect + mock_request.args.get.side_effect = side_effect_dict.get + + # 构造 json_data + json_data = { + 'npu': { + 'node': { + 'node1': {'micro_step_id': 0, 'step_id': 0, 'subnodes': []}, + 'node2': {'micro_step_id': 0, 'step_id': 0, 'subnodes': []}, + 'node3': {'micro_step_id': 1, 'step_id': 1, 'subnodes': []}, + 'node4': {'micro_step_id': 0, 'step_id': 1, 'subnodes': ['subnode1']} + } + } + } + + # 调用 dfs_collect_nodes 方法 + all_node_names = self.plugin.dfs_collect_nodes(json_data, mock_request) + + # 验证返回的 all_node_names + self.assertEqual(all_node_names, ['node1', 'node2']) + + def test_group_precision_set_with_even_number_of_elements(self): + # 测试正常的输入（偶数个元素） + precision_set = [1, 2, 3, 4, 5, 6] + expected_result = [[1, 2], [3, 4], [5, 6]] + + # 调用 group_precision_set 方法 + result = self.plugin.group_precision_set(precision_set) + + # 验证结果是否正确 + self.assertEqual(result, expected_result) + + def test_group_precision_set_with_odd_number_of_elements(self): + # 测试输入长度为奇数的情况 + precision_set = [1, 2, 3] + + # 验证是否抛出 ValueError 异常 + with self.assertRaises(ValueError) as context: + self.plugin.group_precision_set(precision_set) + + self.assertEqual(str(context.exception), 'The number of elements in precision_set is not even') + + def test_process_data_with_md5_mismatch(self): + # 测试 md5 不匹配的情况 + data = [] + data_set = { + 'npu_keys': ['npu_key_1'], + 'bench_keys': ['bench_key_1'], + 'input_data': {'npu_key_1': [1, 2, 3], 'md5': 'abcd'}, + 'output_data': {'bench_key_1': [1, 2, 3], 'md5': 'efgh'}, + 'precision_index': 0, + 'file_path': 'test_path', + 'data_type': 'test_type', + } + npu_node = 'test_node' + + # 调用方法 + result = self.plugin.process_data(data, data_set, npu_node) + + # 验证结果 + self.assertEqual(result, 0) + self.assertEqual(data_set['precision_index'], 0) + + def test_should_update_node_with_valid_batch_and_step(self): + # 模拟 json_data 和 subnode_id_data + subnode_id_data = {'micro_step_id': '-1', 'step_id': '-1', 'matched_node_link': ['N___subnode_1']} + subgraph = {'node': {}} + json_data = { + 'StepList': ['0', '1', '2'] # 测试 StepList 数据 + } + + prefix = 'N___' + subnode_id = 'subnode_1' + + # 调用 _process_subnode 方法 + self.plugin._process_subnode(subgraph, prefix, subnode_id, subnode_id_data, json_data) + + # 验证 subnode_id 是否更新 + self.assertIn(prefix + subnode_id, subgraph['node']) + self.assertEqual(subgraph['node'][prefix + subnode_id], subnode_id_data) + + def mock_json_get(self, *args): + """ 模拟 json_get 方法，返回不同层级的数据 """ + if len(args) == 4 and args[1] == "node": + # 返回节点的 matched_node_link 数据 + return self.plugin._current_file_data[args[0]][args[1]].get(args[2], {}).get('matched_node_link', []) + return None + + def test_should_update_node_with_invalid_batch_or_step(self): + # 测试 batch_id 和 step_id 为无效值时不会更新 + self.plugin.batch_id = '-1' + self.plugin.step_id = '-1' + + subnode_id_data = {'micro_step_id': '1', 'step_id': '1', 'matched_node_link': []} + subgraph = {'node': {}} + json_data = { + 'StepList': ['0', '1', '2'] + } + + prefix = 'B___' + subnode_id = 'subnode_1' + + # 调用 _process_subnode 方法 + self.plugin._process_subnode(subgraph, prefix, subnode_id, subnode_id_data, json_data) + + # 验证 subnode_id 是否被更新 + self.assertIn(prefix + subnode_id, subgraph['node']) + self.assertEqual(subgraph['node'][prefix + subnode_id], subnode_id_data) + + def test_update_matched_node_links(self): + subnode_id_data = { + 'matched_node_link': ['link_1', 'link_2'] + } + prefix = 'B___' + + # 调用 _update_matched_node_links 方法 + self.plugin._update_matched_node_links(subnode_id_data, prefix) + + # 验证 matched_node_link 是否被正确更新 + self.assertEqual(subnode_id_data['matched_node_link'], ['N___link_1', 'N___link_2']) + + def test_no_update_matched_node_links(self): + subnode_id_data = { + 'matched_node_link': ['link_1', 'link_2'] + } + prefix = 'N___' + + # 模拟常量 SETS + constants = MagicMock() + constants.SETS = { + 'bench': ('bench', 'B___', 'N___'), + 'npu': ('npu', 'N___', 'B___'), + 'B___': ('bench', 'N___'), + 'N___': ('npu', 'B___') + } + + # 不更新第一个 matched_node_link + subnode_id_data['matched_node_link'][0] = 'prefixlink_1' + + # 调用 _update_matched_node_links 方法 + self.plugin._update_matched_node_links(subnode_id_data, prefix) + + # 验证 linked node 是否正确更新 + self.assertEqual(subnode_id_data['matched_node_link'], ['B___prefixlink_1', 'B___link_2']) + + @patch('os.walk') # 模拟 os.walk + def test_get_run_dirs(self, mock_os_walk): + """测试 _get_run_dirs 方法""" + + # 设置模拟返回的文件夹和文件 + fake_logdir = os.path.join(os.getcwd(), "fake", "logdir") # 使用绝对路径 + mock_os_walk.return_value = [(fake_logdir, [], ["run1_tag1.vis", "run2_tag2.vis"])] + + # 设置文件大小返回值 + with patch('os.path.getsize', return_value=500): # 模拟文件小于限制 + run_tag_pairs = self.plugin._get_run_dirs() + + # 验证返回的 run_tag_pairs + # 使用 os.path.normpath 来确保路径在不同操作系统上被标准化 + expected_run_tag_pairs = [ + (os.path.normpath(os.path.join(fake_logdir)), 'run1_tag1'), + (os.path.normpath(os.path.join(fake_logdir)), 'run2_tag2') + ] + + self.assertEqual(run_tag_pairs, expected_run_tag_pairs) + + @patch('os.path.getsize') # 模拟 os.path.getsize + def test_get_run_dirs_with_large_file(self, mock_getsize): + """测试 _get_run_dirs 方法，当文件超过大小限制时""" + + # 模拟一个文件大于最大限制 + mock_getsize.return_value = 2000 * 1024 * 1024 # 文件超过 1GB + + # 使用 os.path.join 来构建路径，确保兼容 Windows 和 Linux + fake_logdir = os.path.join("fake", "logdir") + large_file = "large_file.vis" + + with patch('os.walk', return_value=[(fake_logdir, [], [large_file])]): + run_tag_pairs = self.plugin._get_run_dirs() + + # 验证文件被跳过，不会返回任何文件 + self.assertEqual(run_tag_pairs, []) # 文件被跳过，不会返回任何文件 + + def test_convert_to_protobuf_format(self): + """测试 _convert_to_protobuf_format 方法""" + # 模拟节点数据 + subgraph = { + 'node': { + 'npu_node_1': { + 'id': 'op_1', + 'node_type': 1, + 'matched_node_link': ['bench_node_1'], + 'data': { + 'precision_index': 10, + 'other_data': 'value' + }, + 'input_data': {}, + 'output_data': {}, + 'suggestions': {}, + 'subnodes': [], + 'stack_info': 'stack_1' + } + } + } + + # 调用方法 + protobuf_format = self.plugin._convert_to_protobuf_format(subgraph) + + # 验证 protobuf 格式是否正确 + self.assertIn('node {', protobuf_format) + self.assertIn('name: "npu_node_1"', protobuf_format) + self.assertIn('op: "op_1"', protobuf_format) + self.assertIn('precision_index: 10', protobuf_format) + self.assertIn('isLeaf: true', protobuf_format) + + @patch('json.load') # 模拟 json.load + def test_read_json_file_invalid(self, mock_json_load): + """测试 _read_json_file 方法，当文件无效时""" + # 设置模拟的文件路径 + mock_file_path = os.path.join("fake", "file.vis") # 使用 os.path.join 来构造路径 + + # 模拟 json.load 抛出异常 + mock_json_load.side_effect = Exception("Invalid JSON") + + # 使用模拟的路径读取文件 + result = self.plugin._read_json_file(mock_file_path) + + # 验证返回值是 None，并且日志中有错误消息 + self.assertIsNone(result) + + @patch('os.path.exists', return_value=False) + def test_load_json_file_not_found(self, mock_exists): + """测试 _load_json_file 方法，当文件不存在时""" + + # 使用 os.path.join 来确保路径的兼容性 + mock_file_path = os.path.join("fake", "file.vis") + mock_tag = "tag1" + + # 调用方法 + result = self.plugin._load_json_file(mock_file_path, mock_tag) + + # 验证返回值是否为 None + self.assertIsNone(result) + + # 验证 _current_file_path 是否为空 + self.assertEqual(self.plugin._current_file_path, "") + + def test_get_input_output_data(self): + npu_node_data = { + 'input_data': {'input_1': 'data1', 'input_2': 'data2'}, + 'output_data': {'output_1': 'data3'} + } + bench_node_data = { + 'input_data': {'input_1': 'dataA', 'input_2': 'dataB'}, + 'output_data': {'output_1': 'dataC', 'output_2': 'dataD'} + } + + # 调用方法 + ( + npu_input_data, + bench_input_data, + npu_output_data, + bench_output_data + ) = self.instance.get_input_output_data(npu_node_data, bench_node_data) + + # 验证返回结果 + self.assertEqual(npu_input_data, {'input_1': 'data1', 'input_2': 'data2'}) + self.assertEqual(bench_input_data, {'input_1': 'dataA', 'input_2': 'dataB'}) + self.assertEqual(npu_output_data, {'output_1': 'data3'}) + self.assertEqual(bench_output_data, {'output_1': 'dataC', 'output_2': 'dataD'}) + + def test_calculate_min_length(self): + # 模拟输入输出数据 + npu_input_data = {'input_1': 'data1', 'input_2': 'data2'} + bench_input_data = {'input_1': 'dataA', 'input_2': 'dataB', 'input_3': 'dataC'} + npu_output_data = {'output_1': 'data3'} + bench_output_data = {'output_1': 'dataC', 'output_2': 'dataD'} + + # 调用方法 + input_min_length, output_min_length = self.instance.calculate_min_length( + npu_input_data, + bench_input_data, + npu_output_data, + bench_output_data + ) + + # 验证返回值 + self.assertEqual(input_min_length, 2) # 最小输入数据长度 + self.assertEqual(output_min_length, 1) # 最小输出数据长度 + + def test_get_keys(self): + # 模拟 npu 和 bench 数据 + npu_data = { + 'input_data': {'input_1': 'data1', 'input_2': 'data2'}, + 'output_data': {'output_1': 'data3'} + } + bench_data = { + 'input_data': {'input_1': 'dataA', 'input_2': 'dataB'}, + 'output_data': {'output_1': 'dataC', 'output_2': 'dataD'} + } + + # 调用方法 + npu_keys, bench_keys = self.instance.get_keys(npu_data, bench_data) + + # 验证返回值 + self.assertEqual(npu_keys, ['input_data', 'output_data']) + self.assertEqual(bench_keys, ['input_data', 'output_data']) + + def test_calculate_diff_and_relative_error(self): + # 模拟 npu_data 和 bench_data + npu_data = { + 'Max': 10.0, + 'Min': 1.0, + 'Mean': 5.5, + 'Norm': 8.0 + } + bench_data = { + 'Max': 12.0, + 'Min': 2.0, + 'Mean': 5.0, + 'Norm': 7.0 + } + + # 调用方法 + results = self.instance.calculate_diff_and_relative_error(npu_data, bench_data) + + # 验证返回结果 + self.assertEqual(results['npu_Max'], 10.0) + self.assertEqual(results['bench_Max'], 12.0) + self.assertEqual(results['Max_relative_err'], "16.666667%") + + self.assertEqual(results['npu_Min'], 1.0) + self.assertEqual(results['bench_Min'], 2.0) + self.assertEqual(results['Min_relative_err'], "50.000000%") + + self.assertEqual(results['npu_Mean'], 5.5) + self.assertEqual(results['bench_Mean'], 5.0) + self.assertEqual(results['Mean_relative_err'], "10.000000%") + + self.assertEqual(results['npu_Norm'], 8.0) + self.assertEqual(results['bench_Norm'], 7.0) + self.assertEqual(results['Norm_relative_err'], "14.285714%") + + def test_calculate_diff_and_relative_error_with_zero_bench_value(self): + # 模拟 npu_data 和 bench_data，其中 bench_data 有零值 + npu_data = { + 'Max': 10.0, + 'Min': 1.0, + 'Mean': 5.5, + 'Norm': 8.0 + } + bench_data = { + 'Max': 12.0, + 'Min': 0.0, # bench Min 为 0，应该触发 "N/A" 处理 + 'Mean': 5.0, + 'Norm': 0.0 # bench Norm 为 0，应该触发 "N/A" 处理 + } + + # 调用方法 + results = self.instance.calculate_diff_and_relative_error(npu_data, bench_data) + + # 验证返回结果 + self.assertEqual(results['Min_relative_err'], "N/A") + self.assertEqual(results['Norm_relative_err'], "N/A") + +if __name__ == '__main__': + unittest.main() \ No newline at end of file -- Gitee From f2aa5d30a7da02d14878a631228fca74685ddc63 Mon Sep 17 00:00:00 2001 From: wuyulong17 <2284273586@qq.com> Date: Wed, 19 Mar 2025 21:45:43 +0800 Subject: [PATCH 012/750] =?UTF-8?q?=E6=A3=80=E8=A7=86=E6=84=8F=E8=A7=81?= =?UTF-8?q?=E4=BF=AE=E6=94=B9?= 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Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../accuracy_tools/msprobe/docs/19.monitor.md | 72 +++++++++++-------- .../msprobe/mindspore/monitor/module_hook.py | 7 +- .../msprobe/pytorch/monitor/module_hook.py | 7 +- 3 files changed, 51 insertions(+), 35 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/19.monitor.md b/debug/accuracy_tools/msprobe/docs/19.monitor.md index dd4da9c13..20e0fa259 100644 --- a/debug/accuracy_tools/msprobe/docs/19.monitor.md +++ b/debug/accuracy_tools/msprobe/docs/19.monitor.md @@ -444,6 +444,16 @@ csv2tensorboard_by_step( - config中途修改出错时，若此时不在监控就不生效，若在监控则用原配置继续。 - 达到collect_times之后会自动将该值置为false待下次改true重启。 +支持的使用场景说明如下： + +| 场景 | 操作方式 | 预期结果 | +|-----------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------| +| 场景1: 使用原始默认的静态模式 | ```export DYNAMIC_MONITOR=False ``` 或不设置 | 走默认分支保存，不受config.json中dynamic_on影响 | +| 场景2: 进入动态启停模式，一开始不想监控 | 1.```export DYNAMIC_MONITOR=True```
    2.config.json中```dynamic_on: false```或不设置 | 无监控，不保存 | +| 场景3: 进入动态启停模式，一开始就想启动监控 | 1.```export DYNAMIC_MONITOR=True```
    2.config.json中```dynamic_on: true``` | 训练开始根据config初始配置在下一步（从0计数时对应为第1步）开启监控并保存，采集collect_times次数后结束监控 | +| 场景4: 进入动态启停模式，一开始不想监控，但想在训练中途启动监控 | 1.```export DYNAMIC_MONITOR=True```
    2.一开始config.json中```dynamic_on: false```或不设置
    3.中途改```dynamic_on: true``` | 训练中途根据config最新配置在下一步开启监控并保存，采集collect_times次数后结束监控 | +| 场景5: 进入动态启停模式，在监控还未结束时中途修改config.json采集配置 | 1.```export DYNAMIC_MONITOR=True```
    2.期间```dynamic_on: true```启动采集
    3.在采集还未达到collect_times次数未结束前，中途修改config.json中采集配置 | 之前采集按照旧配置保存，修改后下一步以更新的config.json采集且collect_times重新按照最新配置从0开始计数。此功能可配合中途collect_times改0来实现提前停止监控 +| 场景6: 进入动态启停模式，在根据collect_times结束监控后，又需要重新启动监控 | 1.```export DYNAMIC_MONITOR=True```
    2.期间```dynamic_on: true```启动采集
    3.采集达到collect_times次数后结束，程序会自动改```dynamic_on:false```
    4.重新改```dynamic_on:true```重启监控 | 之前采集按照旧配置保存，中途停止监控后无保存，重启后下一步以最新config.json重启采集且collect_times重新按照最新配置从0开始计数 ### 功能重载 此功能将在2026年废弃。请使用[动态启停](#动态启停)功能代替。 @@ -578,35 +588,35 @@ TrainerMon.monitor_gnorm_with_ad(model, grad_acc_steps, optimizer, dp_group, tp_ 下面详细解释各个字段： -| 字段名字 | 是否必选 | 解释 | -| ----------------------- | -------- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| "targets" | 可选 | 指定需要监控的模型层和监控对象， 例如transformer的第0层language_model.encoder.layers.0，可选择监控input、output、input_grad、output_grad。如果不清楚模型结构， 可以将 "print_struct" 字段设置为 true， 监控工具会打印模型中torch module的名字和详细结构，并在第1个step后退出。未配置时默认为全量监控。 | -| "input" | 可选 | "tuple[2]:0"的意思是目标module的前向input参数为长度为2的tuple， 我们关心的是tuple第0个元素。 | -| "output" | 必选 | "tensor"的意思是目标module的前向output参数类型为tensor | -| "input_grad" | 可选 | "tuple[2]:0"的意思是目标module的后向input_grad参数是长度为2的tuple， 我们关心的是tuple的第0个元素。 | -| "output_grad" | 必选 | "tuple[1]:0"的意思是目标module的后向input_grad参数是长度为1的tuple， 我们关心的是tuple的第0个元素。 | -| "dynamic_on" | 可选 | 在动态启停时使用，true代表打开监控，false代表关闭监控，默认值为false，且达到collect_times之后会自动将该值置为false待下次改true重启。**仅PyTorch场景支持此参数**。 | -| "collect_times" | 可选 | 设置采集次数，达到该次数后停止监控，默认值为100000000，目的是一直采集。 | -| "start_step" | 可选 | 设置开始采集step，模型训练达到start_step后开始监控采集，默认值为0，表示从step0开始监控采集。 | -| "step_interval" | 可选 | 设置采集step间隔，默认值为1，表示每个step均采集监控数据。 | -| "print_struct" | 可选 | 设置为true后监控工具会打印模型中torch module的名字和详细结构，并在第1个step后退出。不填默认为false。**仅PyTorch场景支持此参数**。 | -| "module_ranks" | 可选 | 用于在分布式训练场景中希望控制在哪些rank开启module监控。如果不填，则默认在所有rank开启。 列表内rank要求为int类型。 | -| "ur_distribution" | 可选 | 若为true则会统计adam优化器指定模块（targets中指定）参数的update和ratio向量的数值分布，并展示在heatmap里，默认为false，同时format字段必须设置为tensorboard。
    依赖histc算子， 需要CANN8.0.rc2以上版本， 否则会有严重的性能问题。**仅PyTorch场景支持此参数**。 | -| "xy_distribution" | 可选 | 若为true则会监控指定module（targets中指定）的输入输出张量。 默认为false。 | -| "all_xy" | 可选 | 开启xy_distribution后生效，若为true，监控所有module。默认为false。
    与targets同时生效，all_xy配置为true时，若targets配置module_xx和指定对象，则module_xx按targets配置生效，其他module则监控全部对象，包含input、output、input_grad、output_grad。 | -| "forward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的前向，targets中的input_grad、output_grad不生效。默认为false。 | -| "backward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的反向，targets中的input、output不生效。默认为false。 | -| "mv_distribution" | 可选 | 若为true则会监控指定模块中的参数的优化器状态， 默认为false。版本依赖histc算子， 需要CANN8.0.rc2以上版本， 否则会有严重的性能问题。**仅PyTorch场景支持此参数**。 | +| "xy_distribution" | 可选 | 若为true则会监控指定module（targets中指定）的输入输出张量。 默认为false。 | +| "all_xy" | 可选 | 开启xy_distribution后生效，若为true，监控所有module。默认为false。
    与targets同时生效，all_xy配置为true时，若targets配置module_xx和指定对象，则module_xx按targets配置生效，其他module则监控全部对象，包含input、output、input_grad、output_grad。 | +| "forward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的前向，targets中的input_grad、output_grad不生效。默认为false。 | +| "backward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的反向，targets中的input、output不生效。默认为false。 | +| "mv_distribution" | 可选 | 若为true则会监控指定模块中的参数的优化器状态， 默认为false。版本 Date: Fri, 21 Mar 2025 10:35:16 +0800 Subject: [PATCH 039/750] =?UTF-8?q?=E2=9C=A8=20feat:=20md5=E5=8C=B9?= =?UTF-8?q?=E9=85=8D=E9=97=AE=E9=A2=98=E4=BC=98=E5=8C=96?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../server/app/controllers/match_nodes_controller.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py index b2c8e64ad..a61154c3e 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py @@ -220,9 +220,9 @@ class MatchNodesController: @staticmethod def calculate_md5_diff(npu_data, bench_data): # 对比每个NPU和Bench所有数据md值，如果有一个不一样则返回0,否则返回1 - for key in zip(npu_data, npu_data): - npu_md5 = npu_data[key].get('md5', '') - bench_md5 = bench_data[key].get('md5', '') + for npu_key, bench_key in zip(npu_data, npu_data): + npu_md5 = npu_data[npu_key].get('md5', '') + bench_md5 = bench_data[bench_key].get('md5', '') if npu_md5 != bench_md5: return 0 return 1 -- Gitee From 565860c2b540b8c3a21e328a36f5ff4c50dd30fb Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Thu, 20 Mar 2025 20:16:28 +0800 Subject: [PATCH 040/750] =?UTF-8?q?=E2=9C=A8=20feat:=20parse=E5=AE=89?= =?UTF-8?q?=E5=85=A8=E8=BD=AC=E6=8D=A2?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts index dcea1a1d9..f777e70f2 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/useNodeInfo.ts @@ -18,6 +18,7 @@ import useNodeInfoDomain from './domain/useNodeInfoDomain'; import type { MatchNodeInfo } from './type'; import type { MactchResult } from '../types/service'; import { BENCH_PREFIX, NPU_PREFIX } from '../tf_graph_common/common'; +import { safeJSONParse } from '../utils'; export interface UseNodeInfoType { getNodeInfo: ( @@ -232,10 +233,10 @@ const useNodeInfo = (): UseNodeInfoType => { const benchstackInfo = benchNode?.stackData; const title = 'title'; if (!isEmpty(npustackInfo)) { - stackInfo[nodeName] = JSON.parse(npustackInfo.replace(/'/g, '"')).join('\n'); + stackInfo[nodeName] = safeJSONParse(npustackInfo.replace(/'/g, '"'))?.join('\n'); } if (!isEmpty(benchstackInfo)) { - stackInfo[benchNodeName] = JSON.parse(benchstackInfo.replace(/'/g, '"')); + stackInfo[benchNodeName] = safeJSONParse(benchstackInfo.replace(/'/g, '"')); } if (!isEmpty(stackInfo)) { stackInfo[title] = 'stackInfo'; -- Gitee From 662efb26b3c5e8be2642e15b9b3960fdb4e124c1 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Thu, 20 Mar 2025 17:00:18 +0800 Subject: [PATCH 041/750] =?UTF-8?q?=E2=9C=A8=20feat:=20=E6=9B=B4=E6=94=B9?= =?UTF-8?q?=E8=83=8C=E6=99=AF=E8=89=B2?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../fe/src/tf_dashboard_common/tf-dashboard-layout.ts | 1 + 1 file changed, 1 insertion(+) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts index 4ae57964e..264d5d2c5 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts @@ -121,6 +121,7 @@ class TfDashboardLayout extends DarkModeMixin(PolymerElement) { flex-shrink: 1; height: 100%; overflow: hidden; + background:white; } ::slotted([slot='center']) { -- Gitee From 97e05122a6a269bed32a66608dce29a38f0c6033 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Thu, 20 Mar 2025 16:50:48 +0800 Subject: [PATCH 042/750] =?UTF-8?q?=F0=9F=90=8E=20ci:=20=E6=90=AD=E5=BB=BA?= =?UTF-8?q?webpack=E6=9C=AC=E5=9C=B0=E5=BC=80=E5=8F=91=E7=8E=AF=E5=A2=83?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../tb_graph_ascend/fe/package.json | 10 +- .../tb_graph_ascend/fe/webpack.dev.js | 133 ++++++++++++++++++ 2 files changed, 139 insertions(+), 4 deletions(-) create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/fe/webpack.dev.js diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/package.json b/plugins/tensorboard-plugins/tb_graph_ascend/fe/package.json index c3327c095..88c7bfb3c 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/package.json +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/package.json @@ -4,9 +4,9 @@ "private": "true", "main": "index.js", "scripts": { + "dev": "webpack serve --config webpack.dev.js", "buildLinux": "cross-env NODE_ENV=production webpack && cp dist/index.html ../server/static/", "buildWin": "cross-env NODE_ENV=production webpack && copy dist\\index.html ..\\server\\static\\", - "dev": "webpack server", "prettier": "prettier --config ./.prettierrc --write ./src/**/*.ts" }, "devDependencies": { @@ -24,7 +24,8 @@ "tslib": "^2.6.2", "typescript": "^5.4.5", "webpack": "^5.96.1", - "webpack-cli": "^5.1.4" + "webpack-cli": "^5.1.4", + "webpack-dev-server": "4.15.1" }, "dependencies": { "@polymer/decorators": "^3.0.0", @@ -84,6 +85,7 @@ "dagre": "^0.8.5", "lodash": "^4.17.21", "prettier": "^3.4.2", - "style-loader": "^4.0.0" + "style-loader": "^4.0.0", + "ws": "8.13.0" } -} +} \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/webpack.dev.js b/plugins/tensorboard-plugins/tb_graph_ascend/fe/webpack.dev.js new file mode 100644 index 000000000..1507db723 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/webpack.dev.js @@ -0,0 +1,133 @@ +const path = require('path'); +const HtmlWebpackPlugin = require('html-webpack-plugin'); + +module.exports = { + mode: 'development', // 明确指定开发模式 + devtool: 'eval-cheap-source-map', // 开发环境推荐使用的 source map 类型 + + entry: { + app: './src/index' // 保持与生产环境一致的入口 + }, + + output: { + filename: '[name].bundle.js', // 使用带 hash 的文件名 + path: path.resolve(__dirname, 'dist'), + publicPath: '/' // 确保 dev server 的静态资源路径正确 + }, + + devServer: { + static: { + directory: path.join(__dirname, 'dist'), // 服务资源目录 + }, + proxy: [ + { + context: (pathname) => { + return !pathname.match(/(\.js|\.css|\.html|\.ico|\.svg)$/); + }, + target: 'http://127.0.0.1:6006', + changeOrigin: true, + secure: false, + pathRewrite: { + '^/(.*)': '/data/plugin/graph_ascend/$1' // 路径转换核心逻辑 + }, + //ws: true, + on: { + error: (err, req, res) => { + // 安全处理响应对象 + console.error(`[HPM] 代理错误: ${err.message}`); + if (res && !res.headersSent) { + res.writeHead(500, { 'Content-Type': 'text/plain' }); + res.end('Proxy Error'); + } + }, + proxyReqWs: (proxyReq, req, socket) => { + // WebSocket 错误专属处理 + socket.on('error', (error) => { + console.error('[HPM] WebSocket 错误:', error.message); + }); + } + } + } + ], + webSocketServer: { + type: 'ws', + options: { + path: '/ws', + noInfo: true + } + }, + http2: true, // 推荐启用HTTP/2 + https: false // 根据实际需要配置 + , + hot: true, // 启用热模块替换 + liveReload: true, // 启用实时重新加载 + port: 8080, // 自定义端口号 + open: true, // 自动打开浏览器 + client: { + overlay: { + errors: true, + warnings: false, + }, // 在浏览器中显示编译错误 + }, + headers: { + 'X-Proxy-Source': 'webpack-dev-server' + }, + }, + + module: { + rules: [ + { + test: /\.html$/, + use: [ + { + loader: 'html-loader', + options: { + sources: false // 开发环境不需要优化资源路径 + } + } + ] + }, + { + test: /\.ts?$/, + use: { + loader: 'ts-loader', + options: { + transpileOnly: true, // 保持快速编译 + experimentalWatchApi: true // 启用 TypeScript 的监听 API + } + }, + exclude: /node_modules/ + }, + { + test: /\.css$/i, + use: [ + 'style-loader', + { + loader: 'css-loader', + options: { + sourceMap: true // 启用 CSS source maps + } + } + ] + } + ] + }, + + resolve: { + extensions: ['.ts', '.js', '.json'] // 添加 .json 扩展名解析 + }, + + plugins: [ + new HtmlWebpackPlugin({ + inject: 'body', + template: './index.html', + minify: false // 开发环境不压缩 HTML + }) + ], + + optimization: { + removeAvailableModules: false, + removeEmptyChunks: false, + splitChunks: false // 禁用代码拆分加速编译 + } +}; \ No newline at end of file -- Gitee From e4847716be3bb097bc735848cc6f9c02b5f456d9 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Sat, 22 Mar 2025 14:30:06 +0800 Subject: [PATCH 043/750] =?UTF-8?q?=E2=9C=A8=20feat:=E6=9B=B4=E6=96=B0?= =?UTF-8?q?=E7=89=88=E6=9C=AC?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- plugins/tensorboard-plugins/tb_graph_ascend/setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/setup.py b/plugins/tensorboard-plugins/tb_graph_ascend/setup.py index 4c4d59e96..ed8a9d06d 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/setup.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/setup.py @@ -16,7 +16,7 @@ # --------------------------------------------------------------------------------------------# import setuptools -VERSION = '1.0.0' +VERSION = '1.0.1' INSTALL_REQUIRED = ["tensorboard >= 2.11.2"] setuptools.setup( -- Gitee From d12cee3e21235cd0fbf92527a6fecb3826520208 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Sat, 22 Mar 2025 14:38:49 +0800 Subject: [PATCH 044/750] =?UTF-8?q?=E2=9C=A8=20feat:=20=E5=B1=95=E5=BC=80?= =?UTF-8?q?=E8=8A=82=E7=82=B9=E9=80=BB=E8=BE=91=E6=81=A2=E5=A4=8D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../src/tf_graph_controls/components/tf_manual_match/index.ts | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts index f6f6ebcbc..f6f7c9e8e 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts @@ -255,6 +255,8 @@ class Legend extends PolymerElement { if (this.isCompareGraph) { const node = NPU_PREFIX + this.selectedNpuUnMatchedNode; this.set('selectedNode', node); + // 展开对应侧节点 + this.set('selectedNode', BENCH_PREFIX + this.selectedBenchMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', @@ -268,6 +270,8 @@ class Legend extends PolymerElement { if (this.isCompareGraph) { const node = BENCH_PREFIX + this.selectedBenchUnMatchedNode; this.set('selectedNode', node); + // 展开对应侧节点 + this.set('selectedNode', NPU_PREFIX + this.selectedNpuMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', -- Gitee From 9e3833242b6fd112f704338975f783f8976700f4 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Sat, 22 Mar 2025 14:45:22 +0800 Subject: [PATCH 045/750] =?UTF-8?q?=E2=9C=A8=20feat:=20=E9=80=89=E4=B8=AD?= =?UTF-8?q?=E8=8A=82=E7=82=B9=E9=80=BB=E8=BE=91=E4=BF=AE=E6=94=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../components/tf_manual_match/index.ts | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts index f6f7c9e8e..c5e6c0f6d 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts @@ -229,6 +229,8 @@ class Legend extends PolymerElement { this.benchMatchedNodeList = bench_match_nodes; this.set('npuMatchedNodes', Object.keys(npu_match_nodes)); this.set('benchMatchedNodes', Object.keys(bench_match_nodes)); + this.set('selectedNpuMatchedNode', ''); + this.set('selectedBenchMatchedNode', ''); } else { Notification.show(`错误：${result.error}`, { position: 'middle', @@ -255,8 +257,6 @@ class Legend extends PolymerElement { if (this.isCompareGraph) { const node = NPU_PREFIX + this.selectedNpuUnMatchedNode; this.set('selectedNode', node); - // 展开对应侧节点 - this.set('selectedNode', BENCH_PREFIX + this.selectedBenchMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', @@ -270,8 +270,6 @@ class Legend extends PolymerElement { if (this.isCompareGraph) { const node = BENCH_PREFIX + this.selectedBenchUnMatchedNode; this.set('selectedNode', node); - // 展开对应侧节点 - this.set('selectedNode', NPU_PREFIX + this.selectedNpuMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', @@ -286,6 +284,8 @@ class Legend extends PolymerElement { const node = NPU_PREFIX + this.selectedNpuMatchedNode; this.set('selectedBenchMatchedNode', this.npuMatchedNodeList[this.selectedNpuMatchedNode]); this.set('selectedNode', node); + // 展开对应侧节点 + this.set('selectedNode', BENCH_PREFIX + this.selectedBenchMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', @@ -300,6 +300,8 @@ class Legend extends PolymerElement { const node = BENCH_PREFIX + this.selectedBenchMatchedNode; this.set('selectedNpuMatchedNode', this.benchMatchedNodeList[this.selectedBenchMatchedNode]); this.set('selectedNode', node); + // 展开对应侧节点 + this.set('selectedNode', NPU_PREFIX + this.selectedNpuMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', -- Gitee From f7aee35b4b2dd671b1d5d0d60c47a3b5c8456e41 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Sat, 22 Mar 2025 15:08:13 +0800 Subject: [PATCH 046/750] =?UTF-8?q?=E2=9C=A8=20feat:=20=E8=B5=84=E6=96=99?= =?UTF-8?q?=E6=9B=B4=E6=96=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- plugins/tensorboard-plugins/tb_graph_ascend/README.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/README.md b/plugins/tensorboard-plugins/tb_graph_ascend/README.md index 0cf6fcd34..7cd2166d9 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/README.md +++ b/plugins/tensorboard-plugins/tb_graph_ascend/README.md @@ -25,10 +25,10 @@ #### 2.2 从源代码安装 -1. 从仓库下载源码并切换到 poc 分支: +1. 从仓库下载源码并切换到 master 分支: ``` - git clone https://gitee.com/ascend/mstt.git -b poc + git clone https://gitee.com/ascend/mstt.git -b master ``` 2. 进入目录 `plugins/tensorboard-plugins/tb_graph_ascend` 下 @@ -114,6 +114,7 @@ ### 3.3 名称搜索 ![输入图片说明](./doc/images/vis_search_info.png) ### 3.4 精度筛选/溢出筛选 +注意：单图场景不存在精度筛选和溢出筛选，下图为双图比对场景。 ![输入图片说明](./doc/images/vis_precision_info.png) ### 3.5 未匹配节点筛选 参考匹配说明 ，不符合匹配规则的节点为无匹配节点，颜色标灰。适用于排查两个模型结构差异的场景。 -- Gitee From 4409a6a72bd1500fd7fa616ca1b6e8b90f5b9524 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Mon, 24 Mar 2025 10:01:18 +0800 Subject: [PATCH 047/750] =?UTF-8?q?=E2=9C=A8=20feat:=20=E6=96=87=E5=AD=97?= =?UTF-8?q?=E6=8D=A2=E8=A1=8C?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- plugins/tensorboard-plugins/tb_graph_ascend/README.md | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/README.md b/plugins/tensorboard-plugins/tb_graph_ascend/README.md index 7cd2166d9..83c13a427 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/README.md +++ b/plugins/tensorboard-plugins/tb_graph_ascend/README.md @@ -114,13 +114,16 @@ ### 3.3 名称搜索 ![输入图片说明](./doc/images/vis_search_info.png) ### 3.4 精度筛选/溢出筛选 -注意：单图场景不存在精度筛选和溢出筛选，下图为双图比对场景。 +注意：单图场景不存在精度筛选和溢出筛选，下图为双图比对场景。
    + ![输入图片说明](./doc/images/vis_precision_info.png) ### 3.5 未匹配节点筛选 -参考匹配说明 ，不符合匹配规则的节点为无匹配节点，颜色标灰。适用于排查两个模型结构差异的场景。 +参考匹配说明 ，不符合匹配规则的节点为无匹配节点，颜色标灰。适用于排查两个模型结构差异的场景。
    + ![输入图片说明](./doc/images/vis_unmatch_info.png) ### 3.6 手动选择节点匹配 -可通过浏览器界面，通过鼠标选择两个待匹配的灰色节点进行匹配。当前暂不支持真实数据模式。 +可通过浏览器界面，通过鼠标选择两个待匹配的灰色节点进行匹配。当前暂不支持真实数据模式。
    + ![输入图片说明](./doc/images/vis_match_info.png) -- Gitee From 17e6ab683a340e06616686eb5eae2b0beab3d3ea Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 24 Mar 2025 10:44:28 +0800 Subject: [PATCH 048/750] add dump situation --- .../msprobe/docs/05.data_dump_PyTorch.md | 51 +++++++++++++++++++ 1 file changed, 51 insertions(+) diff --git a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md index 6aea3126b..b453a1fa7 100644 --- a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md @@ -338,6 +338,57 @@ if __name__ == "__main__": debugger.stop() ``` +### 2.5 跨文件采集数据 +假设有两个文件，train.py和module.py。train.py为训练工程入口，module.py为模型定义文件。 +本场景目的：为了采集module.py中定义的ModuleOP模块中某些子模块或API的前反向数据。 + +train.py文件： + +```Python +# 根据需要import包 +from module import ModuleOP + +# 导入工具的数据采集接口 +from msprobe.pytorch import PrecisionDebugger + +# 在模型训练开始前实例化PrecisionDebugger +debugger = PrecisionDebugger(config_path='./config.json') + +if __name__ == "__main__": + module = ModuleOP() + + x = torch.randn(10, 8) + out = module(x) # module内部的child modules或API将不会被dump + loss = out.sum() # module_dump_end和stop接口之间的数据正常dump + loss.backward() +``` + +module.py文件： + +```Python +import torch +import torch.nn as nn +import torch.nn.functional as F + +from msprobe.pytorch import PrecisionDebugger + +# 定义网络 +class ModuleOP(nn.Module): + def __init__(self) -> None: + super().__init__() + self.linear_1 = nn.Linear(in_features=8, out_features=4) + self.linear_2 = nn.Linear(in_features=4, out_features=2) + + def forward(self, x): + PrecisionDebugger.start() + x1 = self.linear_1(x) + PrecisionDebugger.stop() + x2 = self.linear_2(x1) + r1 = F.relu(x2) + return r1 + +``` + ## 3 dump 结果文件介绍 训练结束后，工具将 dump 的数据保存在 dump_path 参数指定的目录下。目录结构示例如下： -- Gitee From 1a9474a49493226e672f37c0af1334239a86a521 Mon Sep 17 00:00:00 2001 From: RanZheng <364167184@qq.com> Date: Mon, 24 Mar 2025 11:11:29 +0800 Subject: [PATCH 049/750] =?UTF-8?q?=E8=A1=A5=E5=85=85dynamic=5Fon=E5=AD=97?= =?UTF-8?q?=E6=AE=B5=E6=A0=A1=E9=AA=8C?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../accuracy_tools/msprobe/docs/19.monitor.md | 62 +++++++++---------- .../msprobe/mindspore/monitor/utils.py | 8 +++ .../msprobe/pytorch/monitor/utils.py | 8 +++ 3 files changed, 47 insertions(+), 31 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/19.monitor.md b/debug/accuracy_tools/msprobe/docs/19.monitor.md index 20e0fa259..2b0e49fee 100644 --- a/debug/accuracy_tools/msprobe/docs/19.monitor.md +++ b/debug/accuracy_tools/msprobe/docs/19.monitor.md @@ -588,35 +588,35 @@ TrainerMon.monitor_gnorm_with_ad(model, grad_acc_steps, optimizer, dp_group, tp_ 下面详细解释各个字段： -| 字段名字 | 是否必选 | 解释 | -| ----------------------- | -------- |------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| "targets" | 可选 | 指定需要监控的模型层和监控对象， 例如transformer的第0层language_model.encoder.layers.0，可选择监控input、output、input_grad、output_grad。如果不清楚模型结构， 可以将 "print_struct" 字段设置为 true， 监控工具会打印模型中torch module的名字和详细结构，并在第1个step后退出。未配置时默认为全量监控。 | -| "input" | 可选 | "tuple[2]:0"的意思是目标module的前向input参数为长度为2的tuple， 我们关心的是tuple第0个元素。 | -| "output" | 必选 | "tensor"的意思是目标module的前向output参数类型为tensor | -| "input_grad" | 可选 | "tuple[2]:0"的意思是目标module的后向input_grad参数是长度为2的tuple， 我们关心的是tuple的第0个元素。 | -| "output_grad" | 必选 | "tuple[1]:0"的意思是目标module的后向input_grad参数是长度为1的tuple， 我们关心的是tuple的第0个元素。 | -| "dynamic_on" | 可选 | 在动态启停时使用，true代表打开监控，false代表关闭监控，默认值为false，且达到collect_times之后会自动将该值置为false待下次改true重启。 | -| "collect_times" | 可选 | 设置采集次数，达到该次数后停止监控，默认值为100000000，目的是一直采集。 | -| "start_step" | 可选 | 设置开始采集step，模型训练达到start_step后开始监控采集，默认值为0，表示从step0开始监控采集。注：在动态启停模式下该设置不生效，只会从下一步开始监控采集。 | -| "step_interval" | 可选 | 设置采集step间隔，默认值为1，表示每个step均采集监控数据。 | -| "print_struct" | 可选 | 设置为true后监控工具会打印模型中torch module的名字和详细结构，并在第1个step后退出。不填默认为false。**仅PyTorch场景支持此参数**。 | -| "module_ranks" | 可选 | 用于在分布式训练场景中希望控制在哪些rank开启module监控。如果不填，则默认在所有rank开启。 列表内rank要求为int类型。 | -| "ur_distribution" | 可选 | 若为true则会统计adam优化器指定模块（targets中指定）参数的update和ratio向量的数值分布，并展示在heatmap里，默认为false，同时format字段必须设置为tensorboard。
    依赖histc算子， 需要CANN8.0.rc2以上版本， 否则会有严重的性能问题。**仅PyTorch场景支持此参数**。 | -| "xy_distribution" | 可选 | 若为true则会监控指定module（targets中指定）的输入输出张量。 默认为false。 | -| "all_xy" | 可选 | 开启xy_distribution后生效，若为true，监控所有module。默认为false。
    与targets同时生效，all_xy配置为true时，若targets配置module_xx和指定对象，则module_xx按targets配置生效，其他module则监控全部对象，包含input、output、input_grad、output_grad。 | -| "forward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的前向，targets中的input_grad、output_grad不生效。默认为false。 | -| "backward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的反向，targets中的input、output不生效。默认为false。 | -| "mv_distribution" | 可选 | 若为true则会监控指定模块中的参数的优化器状态， 默认为false。版本依赖histc算子， 需要CANN8.0.rc2以上版本， 否则会有严重的性能问题。**仅PyTorch场景支持此参数**。 | +| "xy_distribution" | 可选 | 若为true则会监控指定module（targets中指定）的输入输出张量。 默认为false。 | +| "all_xy" | 可选 | 开启xy_distribution后生效，若为true，监控所有module。默认为false。
    与targets同时生效，all_xy配置为true时，若targets配置module_xx和指定对象，则module_xx按targets配置生效，其他module则监控全部对象，包含input、output、input_grad、output_grad。 | +| "forward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的前向，targets中的input_grad、output_grad不生效。默认为false。 | +| "backward_only" | 可选 | 开启xy_distribution后生效，若为true，仅监控指定module的反向，targets中的input、output不生效。默认为false。 | +| "mv_distribution" | 可选 | 若为true则会监控指定模块中的参数的优化器状态， 默认为false。版本 Date: Mon, 24 Mar 2025 11:16:32 +0800 Subject: [PATCH 050/750] =?UTF-8?q?=E5=86=97=E4=BD=99=E4=BB=A3=E7=A0=81?= =?UTF-8?q?=E5=88=A0=E9=99=A4?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../fe/src/tf_backend/canceller.ts | 68 --- .../fe/src/tf_backend/requestManager.ts | 16 - .../tf-dashboard-layout.ts | 1 + .../src/tf_graph/components/legend/index.ts | 9 - .../fe/src/tf_graph/tf-graph-scene.html.ts | 441 +----------------- .../fe/src/tf_graph/tf-graph-scene.ts | 8 - .../fe/src/tf_graph/tf-graph.ts | 51 -- .../fe/src/tf_graph_board/tf-graph-board.ts | 4 - .../fe/src/tf_graph_common/edge.ts | 173 +------ .../components/tf_manual_match/index.ts | 6 + .../fe/src/tf_graph_dashboard/index.ts | 4 - .../app/controllers/match_nodes_controller.py | 6 +- .../tb_graph_ascend/setup.py | 2 +- 13 files changed, 17 insertions(+), 772 deletions(-) delete mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/canceller.ts diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/canceller.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/canceller.ts deleted file mode 100644 index bc840bb4a..000000000 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/canceller.ts +++ /dev/null @@ -1,68 +0,0 @@ -/* Copyright 2017 The TensorFlow Authors. All Rights Reserved. - -Licensed under the Apache License, Version 2.0 (the 'License'); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an 'AS IS' BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. -==============================================================================*/ - -export interface CancelResult { - value: T; - cancelled: boolean; -} - -/** - * A class that allows marking promises as cancelled. - * - * This can be useful to, e.g., prevent old network requests from - * stomping new ones and writing bad data. - * - * Usage: - * - * const canceller = new Canceller(); - * let myPromise: Promise = getPromise(); - * myPromise.then(canceller.cancellable(({value, cancelled} => { - * if (cancelled) { - * console.warn("Don't make promises you can't keep >:-{"); - * } - * console.log("Enjoy your value:", value); - * })); - * - * // If `myPromise` is resolved now, then `cancelled` will be `false`. - * canceller.cancelAll(); - * // If `myPromise` is resolved now, then `cancelled` will be `true`. - */ -export class Canceller { - /** - * How many times has `cancelAll` been called? - */ - private cancellationCount = 0; - /** - * Create a cancellable task. This returns a new function that, when - * invoked, will pass its argument to the provided function as well as - * a `cancelled` argument. This argument will be `false` unless and - * until `cancelAll` is invoked after the creation of this task. - */ - public cancellable(f: (result: CancelResult) => U): (T) => U { - const originalCancellationCount = this.cancellationCount; - return (value) => { - const cancelled = this.cancellationCount !== originalCancellationCount; - return f({ value, cancelled }); - }; - } - - /** - * Mark all outstanding tasks as cancelled. Tasks not yet created will - * not be affected. - */ - public cancelAll(): void { - this.cancellationCount++; - } -} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/requestManager.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/requestManager.ts index 9fc04e490..d47635c83 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/requestManager.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_backend/requestManager.ts @@ -185,22 +185,6 @@ export class RequestManager { }); } - public clearQueue(): void { - while (this._queue.length > 0) { - this._queue.pop()?.reject(new RequestCancellationError('Request cancelled by clearQueue')); - } - } - - /* Return number of currently pending requests */ - public activeRequests(): number { - return this._nActiveRequests; - } - - /* Return total number of outstanding requests (includes queue) */ - public outstandingRequests(): number { - return this._nActiveRequests + this._queue.length; - } - /* Actually get promise from url using XMLHttpRequest */ protected _promiseFromUrl(url: string, requestOptions: RequestOptions): Promise { return new Promise((resolve, reject) => { diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts index 4ae57964e..264d5d2c5 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_dashboard_common/tf-dashboard-layout.ts @@ -121,6 +121,7 @@ class TfDashboardLayout extends DarkModeMixin(PolymerElement) { flex-shrink: 1; height: 100%; overflow: hidden; + background:white; } ::slotted([slot='center']) { diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/components/legend/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/components/legend/index.ts index c4e85d38e..88e97a6a9 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/components/legend/index.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/components/legend/index.ts @@ -38,15 +38,6 @@ class Legend extends PolymerElement { margin-left: 5px; font-size: 12px; } - .legend-clarifier { - } - .legend-item { - margin-right: 10px; - } - .legend-item-value { - margin-left: 5px; - font-size: 12px; - } .legend-clarifier { color: #266236; cursor: pointer; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.html.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.html.ts index 769b67f53..80cfea0b9 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.html.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.html.ts @@ -214,105 +214,6 @@ export const template = html` stroke-width: 4; } - .faded, - .faded rect, - .faded ellipse, - .faded path, - .faded use, - #rectHatch line, - #ellipseHatch line { - color: #e0d4b3 !important; - fill: white; - stroke: #e0d4b3 !important; - } - - .faded path { - stroke-width: 1px !important; - } - - .faded rect { - fill: url(#rectHatch) !important; - } - - .faded ellipse, - .faded use { - fill: url(#ellipseHatch) !important; - } - - .faded text { - opacity: 0; - } - - /* Rules used for input-tracing. */ - .input-highlight > * > rect, - .input-highlight > * > ellipse, - .input-highlight > * > use { - fill: white; - stroke: #ff9800 !important; - } - - /* - Faded non-input styling */ - .non-input > * > rect, - .non-input > * > ellipse, - .non-input > * > use, - /* For Const nodes. */ - .non-input > * > .constant:not([class*="input-highlight"]) > - .annotation-node > ellipse, - /* For styling of annotation nodes of non-input nodes. */ - .non-input > g > .annotation > .annotation-node > rect { - stroke: #e0d4b3 !important; - stroke-width: inherit; - stroke-dasharray: inherit; - } - - .non-input path { - visibility: hidden; - } - - .non-input > .nodeshape > rect, - .non-input > .annotation-node > rect, - /* For styling of annotation nodes of non-input nodes. */ - .non-input > g > .annotation > .annotation-node > rect { - fill: url(#rectHatch) !important; - } - - .non-input ellipse, - .non-input use { - fill: url(#ellipseHatch) !important; - } - - .non-input > text { - opacity: 0; - } - - .non-input .annotation > .annotation-edge { - marker-end: url(#annotation-arrowhead-faded); - } - - .non-input .annotation > .annotation-edge.refline { - marker-start: url(#ref-annotation-arrowhead-faded); - } - - /* Input edges. */ - .input-edge-highlight > text { - fill: black !important; - } - .input-highlight > .in-annotations > .annotation > .annotation-edge, - .input-highlight-selected > .in-annotations > .annotation > .annotation-edge { - stroke: #999 !important; - } - - /* Non-input edges. */ - .non-input-edge-highlight, - .non-input > g > .annotation > path, - /* Annotation styles (label and edges respectively). */ - .non-input > g > - .annotation:not(.input-highlight):not(.input-highlight-selected) > - .annotation-label - /*.annotation-edge*/ { - visibility: hidden; - } - /* --- Op Node --- */ .op > .nodeshape > .nodecolortarget, @@ -355,18 +256,10 @@ export const template = html` font-size: 9px; } - .series > text.nodelabel { - font-size: 8px; - } - .op > text.nodelabel { font-size: 6px; } - .bridge > text.nodelabel { - display: none; - } - .node.meta.expanded > text.nodelabel { cursor: normal; } @@ -396,153 +289,12 @@ export const template = html` stroke-dasharray: 1, 1; } - .annotation.summary > .annotation-node > *, - .annotation.constant > .annotation-node > * { - stroke-width: 1; - stroke-dasharray: none; - } - - .annotation > .annotation-edge { - fill: none; - stroke: #aaa; - stroke-width: 0.5; - marker-end: url(#annotation-arrowhead); - } - - .faded .annotation > .annotation-edge { - marker-end: url(#annotation-arrowhead-faded); - } - - .annotation > .annotation-edge.refline { - marker-start: url(#ref-annotation-arrowhead); - } - - .faded .annotation > .annotation-edge.refline { - marker-start: url(#ref-annotation-arrowhead-faded); - } - - .annotation > .annotation-control-edge { - stroke-dasharray: 1, 1; - } - - #annotation-arrowhead { - fill: #aaa; - } - - #annotation-arrowhead-faded { - fill: #e0d4b3; - } - - #ref-annotation-arrowhead { - fill: #aaa; - } - - #ref-annotation-arrowhead-faded { - fill: #e0d4b3; - } - - .annotation > .annotation-label { - font-size: 5px; - cursor: pointer; - } - .annotation > .annotation-label.annotation-ellipsis { - cursor: default; - } - /* Hide annotations on expanded meta nodes since they're redundant. */ .expanded > .in-annotations, .expanded > .out-annotations { display: none; } - /* --- Annotation: Constant --- */ - - .constant > .annotation-node > ellipse { - cursor: pointer; - fill: white; - stroke: #848484; - } - - .constant.selected > .annotation-node > ellipse { - fill: white; - stroke: red; - } - - .constant.highlighted > .annotation-node > ellipse { - stroke-width: 1.5; - } - - /* --- Annotation: Summary --- */ - - .summary > .annotation-node > ellipse { - cursor: pointer; - fill: #db4437; - stroke: #db4437; - } - - .summary.selected > .annotation-node > ellipse { - fill: #a52714; - stroke: #a52714; - } - - .summary.highlighted > .annotation-node > ellipse { - stroke-width: 1.5; - } - - /* --- Edge --- */ - - .edge > path.edgeline { - display: none; - fill: none; - stroke: #bbb; - stroke-linecap: round; - stroke-width: 0.75; - } - - .highlighted > path.edgeline { - cursor: pointer; - stroke: #5ae; - } - - .edge .selectableedge { - cursor: pointer; - } - - .selectededge > path.edgeline { - cursor: default; - stroke: #f00; - } - - .edge.selectededge text { - fill: #000; - } - - /* Labels showing tensor shapes on edges */ - .edge > text { - font-size: 3.5px; - fill: #666; - } - - .dataflow-arrowhead { - fill: #bbb; - } - - .reference-arrowhead { - fill: #ffb74d; - } - - .selected-arrowhead { - fill: #f00; - } - - .highlighted-arrowhead { - fill: #5ae; - } - - .edge .control-dep { - stroke-dasharray: 2, 2; - } - /* --- Group node expand/collapse button --- */ /* Hides expand/collapse buttons when a node isn't expanded or highlighted. Using @@ -554,12 +306,6 @@ export const template = html` .node.highlighted > .nodeshape > .buttoncontainer { cursor: pointer; } - .buttoncircle { - fill: #e7811d; - } - .buttoncircle:hover { - fill: #b96717; - } .expandbutton, .collapsebutton { stroke: white; @@ -578,17 +324,6 @@ export const template = html` display: none; } - .health-pill-stats { - font-size: 4px; - text-anchor: middle; - } - - .health-pill rect { - filter: url(#health-pill-shadow); - rx: 3; - ry: 3; - } - .titleContainer { position: relative; top: 20px; @@ -638,183 +373,9 @@ export const template = html`

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -`; +`; \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts index 17d388d71..6ef9ba1fe 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts @@ -605,14 +605,6 @@ class TfGraphScene2 extends LegacyElementMixin(DarkModeMixin(PolymerElement)) im delete this._nodeGroupIndex[n]; } - addEdgeGroup(n, selection): void { - this._edgeGroupIndex[n] = selection; - } - - getEdgeGroup(e): any { - return this._edgeGroupIndex[e]; - } - /** * Update node and annotation node of the given name. * @param {String} n node name diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts index 78c19e1f6..51f6039d4 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts @@ -563,55 +563,4 @@ class TfGraph extends LegacyElementMixin(PolymerElement) { // Rebuild the render hierarchy. this._buildRenderHierarchy(this.graphHierarchy); } - - _deselectPreviousEdge(): void { - const selectedSelector = `.${tf_graph_scene.Class.Edge.SELECTED}`; - const selectedEdge = this.$.scene.shadowRoot?.querySelector(selectedSelector); - const selectedPaths = this.$.scene.shadowRoot?.querySelectorAll('path.edgeline'); - // Visually mark the previously selected edge (if any) as deselected. - if (!!selectedEdge) { - d3.select(selectedEdge) - .classed(tf_graph_scene.Class.Edge.SELECTED, false) - .each((d: any, i) => { - // Reset its marker. - if (d.label && selectedPaths) { - const paths = d3.selectAll(selectedPaths); - if (d.label.startMarkerId) { - paths.style('marker-start', `url(#${d.label.startMarkerId})`); - } - if (d.label.endMarkerId) { - paths.style('marker-end', `url(#${d.label.endMarkerId})`); - } - } - }); - } - } - - _updateMarkerOfSelectedEdge(selectedEdge, isSelected): void { - if (selectedEdge.label) { - const statsName = isSelected ? 'selected-' : 'highlighted-'; - // The marker will vary based on the direction of the edge. - const markerId = selectedEdge.label.startMarkerId || selectedEdge.label.endMarkerId; - if (markerId) { - // Find the corresponding marker for a selected edge. - const selectedMarkerId = markerId.replace('dataflow-', statsName); - let selectedMarker = this.$.scene.shadowRoot?.querySelector(`#${selectedMarkerId}`) as HTMLElement; - if (!selectedMarker) { - // The marker for a selected edge of this size does not exist yet. Create it. - const originalMarker = this.$.scene.shadowRoot?.querySelector(`#${markerId}`); - selectedMarker = originalMarker?.cloneNode(true) as HTMLElement; - selectedMarker.setAttribute('id', selectedMarkerId); - selectedMarker.classList.add(`${statsName}arrowhead`); - originalMarker?.parentNode?.appendChild(selectedMarker); - } - // Make the path use this new marker while it is selected. - const markerAttribute = selectedEdge.label.startMarkerId ? 'marker-start' : 'marker-end'; - if (isSelected) { - this._lastSelectedEdgeGroup.selectAll('path.edgeline').style(markerAttribute, `url(#${selectedMarkerId})`); - } else { - this._lastHighlightedEdgeGroup.selectAll('path.edgeline').style(markerAttribute, `url(#${selectedMarkerId})`); - } - } - } - } } diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts index 39f7ec831..496506940 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts @@ -307,8 +307,4 @@ class TfGraphBoard extends LegacyElementMixin(PolymerElement) { } return result; } - - _onNodeInclusionToggled(event): void { - (this.$.graph as any).nodeToggleExtract(event.detail.name); - } } diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/edge.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/edge.ts index 09f3a6a93..a2d881ead 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/edge.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/edge.ts @@ -97,32 +97,6 @@ export function buildGroup(sceneGroup, graph: graphlib.Graph, sceneElement: TfGr d.label.edgeGroup = edgeGroup; // index node group for quick highlighting sceneComponent._edgeGroupIndex[getEdgeKey(d)] = edgeGroup; - - edgeGroup - .on('click', (dClick) => { - // Stop this event's propagation so that it isn't also considered - // a graph-select. - (d3.event).stopPropagation(); - sceneComponent.fire('edge-select', { - edgeData: dClick, - edgeGroup: edgeGroup, - }); - }) - .on('mouseover', (dMouseOver) => { - sceneElement.fire('edge-highlight', { - edgeData: dMouseOver, - edgeGroup: edgeGroup, - }); - }) - .on('mouseout', (dMouseOut) => { - sceneElement.fire('edge-unhighlight', { - edgeData: dMouseOut, - edgeGroup: edgeGroup, - }); - }); - // Add line during enter because we're assuming that type of line - // normally does not change. - appendEdge(edgeGroup, d, sceneComponent); }) .merge(edgeGroups) .each(function () { @@ -167,6 +141,7 @@ export function getLabelForBaseEdge(baseEdge: BaseEdge, renderInfo: render.Rende }) .join(TENSOR_SHAPE_DELIM); } + /** * Creates the label for the given metaedge. If the metaedge consists * of only 1 tensor, and it's shape is known, the label will contain that @@ -179,89 +154,7 @@ export function getLabelForEdge(metaedge: Metaedge, renderInfo: render.RenderGra ? `${metaedge.baseEdgeList.length}tensors` : getLabelForBaseEdge(metaedge.baseEdgeList[0], renderInfo); } -/** - * Computes the index into a set of points that constitute a path for which the - * distance along the path from the initial point is as large as possible - * without exceeding the length. This function was introduced after the - * native getPathSegAtLength method got deprecated by SVG 2. - * @param points Array of path control points. A point has x and y properties. - * Must be of length at least 2. - * @param length The length (float). - * @param lineFunc A function that takes points and returns the "d" attribute - * of a path made from connecting the points. - * @return The index into the points array. - */ -function getPathSegmentIndexAtLength( - points: render.Point[], - length: number, - lineFunc: (points: render.Point[]) => string, -): number { - const path = document.createElementNS(tf_graph_common.SVG_NAMESPACE, 'path'); - for (let i = 1; i < points.length; i++) { - path.setAttribute('d', lineFunc(points.slice(0, i))); - if (path.getTotalLength() > length) { - // This many points has already exceeded the length. - return i - 1; - } - } - // The entire path is shorter than the specified length. - return points.length - 1; -} -/** - * Shortens the path enought such that the tip of the start/end marker will - * point to the start/end of the path. The marker can be of arbitrary size. - * - * @param points Array of path control points. - * @param marker D3 selection of the svg element. - * @param isStart Is the marker a `start-marker`. If false, the marker is - * an `end-marker`. - * @return The new array of control points. - */ -function adjustPathPointsForMarker( - points: render.Point[], - marker: d3.Selection, - isStart: boolean, -): render.Point[] { - let lineFunc = d3 - .line() - .x((d) => d.x) - .y((d) => d.y); - let path = d3.select(document.createElementNS('http://www.w3.org/2000/svg', 'path')).attr('d', lineFunc(points)); - let markerWidth = Number(marker.attr('markerWidth')); - let viewBox = marker.attr('viewBox').split(' ').map(Number); - let viewBoxWidth = viewBox[2] - viewBox[0]; - let refX = Number(marker.attr('refX')); - let pathNode = path.node(); - if (isStart) { - // The edge flows downwards. Do not make the edge go the whole way, lest we - // clobber the arrowhead. - const fractionStickingOut = 1 - (refX / viewBoxWidth); - const length = markerWidth * fractionStickingOut; - const point = pathNode.getPointAtLength(length); - // Figure out how many segments of the path we need to remove in order - // to shorten the path. - // @ts-expect-error TS2345: Argument of type 'Line' is not assignable to parameter of type '(points: Point[]) => string'. - const segIndex = getPathSegmentIndexAtLength(points, length, lineFunc); - // Update the very first segment. - points[segIndex - 1] = { x: point.x, y: point.y }; - // Ignore every point before segIndex - 1. - return points.slice(segIndex - 1); - } else { - // The edge flows upwards. Do not make the edge go the whole way, lest we - // clobber the arrowhead. - const fractionStickingOut = 1 - refX / viewBoxWidth; - const length = pathNode.getTotalLength() - (markerWidth * fractionStickingOut); - const point = pathNode.getPointAtLength(length); - // Figure out how many segments of the path we need to remove in order - // to shorten the path. - // @ts-expect-error TS2345: Argument of type 'Line' is not assignable to parameter of type '(points: Point[]) => string'. - const segIndex = getPathSegmentIndexAtLength(points, length, lineFunc); - // Update the very last segment. - points[segIndex] = { x: point.x, y: point.y }; - // Ignore every point after segIndex. - return points.slice(0, segIndex + 1); - } -} + /** * For a given d3 selection and data object, create a path to represent the * edge described in d.label. @@ -330,8 +223,6 @@ export function appendEdge( // We have no information to show on this edge. return; } - // Put edge label in the middle of edge only if the edge is thick enough. - let baseline = strokeWidth > CENTER_EDGE_LABEL_MIN_STROKE_WIDTH ? 'central' : 'text-after-edge'; edgeGroup .append('text') .append('textPath') @@ -341,6 +232,7 @@ export function appendEdge( .attr('dominant-baseline', 'central') .text(labelForEdge); } + export const interpolate: d3.Line<{ x: number; y: number; @@ -356,68 +248,13 @@ export const interpolate: d3.Line<{ .y((d) => { return d.y; }); -/** - * Returns a tween interpolator for the endpoint of an edge path. - */ -function getEdgePathInterpolator( - component: HTMLElement, - renderPath: SVGPathElement, - d: EdgeData, - i: number, - a: SVGPathElement[], -): ((t: number) => string) | ((t: any) => string | null) { - let renderMetaedgeInfo = d.label; - let adjoiningMetaedge = renderMetaedgeInfo.adjoiningMetaedge; - let points = renderMetaedgeInfo.points; - // Adjust the path so that start/end markers point to the end - // of the path. - const { shadowRoot } = component; - if (d.label.startMarkerId) { - points = adjustPathPointsForMarker( - points, - d3.select(shadowRoot?.querySelector(`#${d.label.startMarkerId}`) as Element), - true, - ); - } - if (d.label.endMarkerId) { - points = adjustPathPointsForMarker( - points, - d3.select(shadowRoot?.querySelector(`#${d.label.endMarkerId}`) as Element), - false, - ); - } - if (!adjoiningMetaedge) { - return d3.interpolate(a, interpolate(points) ?? ''); - } - // Get the adjoining path that matches the adjoining metaedge. - let adjoiningPath = (adjoiningMetaedge.edgeGroup.node()).firstChild; - // Find the desired SVGPoint along the adjoining path, then convert those - // coordinates into the space of the renderPath using its Current - // Transformation Matrix (CTM). - let inbound = renderMetaedgeInfo.metaedge?.inbound; - return function (t): string | null { - let adjoiningPoint = adjoiningPath - .getPointAtLength(inbound ? adjoiningPath.getTotalLength() : 0) - .matrixTransform(adjoiningPath.getCTM() as DOMMatrixInit) - .matrixTransform(renderPath.getCTM()?.inverse()); - // Update the relevant point in the renderMetaedgeInfo's points list, then - // re-interpolate the path. - let index = inbound ? 0 : points.length - 1; - points[index].x = adjoiningPoint.x; - points[index].y = adjoiningPoint.y; - let dPath = interpolate(points); - return dPath; - }; -} + function position(component: HTMLElement, edgeGroup: HTMLElement): void { d3.select(edgeGroup) .select(`path.${Class.Edge.LINE}`) .transition() - // @ts-expect-error TS2769: No overload matches this call. complicated return type mismatch issue - .attrTween('d', function (d: EdgeData, i: number, a: SVGPathElement[]) { - return getEdgePathInterpolator(component, this as SVGPathElement, d, i, a); - }); } + /** * For a given d3 selection and data object, mark the edge as a control * dependency if it contains only control edges. diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts index f6f6ebcbc..c5e6c0f6d 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_controls/components/tf_manual_match/index.ts @@ -229,6 +229,8 @@ class Legend extends PolymerElement { this.benchMatchedNodeList = bench_match_nodes; this.set('npuMatchedNodes', Object.keys(npu_match_nodes)); this.set('benchMatchedNodes', Object.keys(bench_match_nodes)); + this.set('selectedNpuMatchedNode', ''); + this.set('selectedBenchMatchedNode', ''); } else { Notification.show(`错误：${result.error}`, { position: 'middle', @@ -282,6 +284,8 @@ class Legend extends PolymerElement { const node = NPU_PREFIX + this.selectedNpuMatchedNode; this.set('selectedBenchMatchedNode', this.npuMatchedNodeList[this.selectedNpuMatchedNode]); this.set('selectedNode', node); + // 展开对应侧节点 + this.set('selectedNode', BENCH_PREFIX + this.selectedBenchMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', @@ -296,6 +300,8 @@ class Legend extends PolymerElement { const node = BENCH_PREFIX + this.selectedBenchMatchedNode; this.set('selectedNpuMatchedNode', this.benchMatchedNodeList[this.selectedBenchMatchedNode]); this.set('selectedNode', node); + // 展开对应侧节点 + this.set('selectedNode', NPU_PREFIX + this.selectedNpuMatchedNode); } else { Notification.show('提示：单图节点不支持匹配', { position: 'middle', diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_dashboard/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_dashboard/index.ts index 2848f927a..91b39feaa 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_dashboard/index.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_dashboard/index.ts @@ -20,7 +20,6 @@ import { customElement, observe, property } from '@polymer/decorators'; import { html, PolymerElement } from '@polymer/polymer'; import '../polymer/irons_and_papers'; import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; -import { Canceller } from '../tf_backend/canceller'; import { RequestManager } from '../tf_backend/requestManager'; import '../tf_dashboard_common/tf-dashboard-layout'; import * as tf_storage from '../tf_storage'; @@ -200,9 +199,6 @@ class TfGraphDashboard extends LegacyElementMixin(PolymerElement) { @property({ type: Object }) _requestManager: RequestManager = new RequestManager(); - @property({ type: Object }) - _canceller: Canceller = new Canceller(); - @property({ type: Boolean }) _debuggerDataEnabled: boolean; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py index b2c8e64ad..a61154c3e 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py @@ -220,9 +220,9 @@ class MatchNodesController: @staticmethod def calculate_md5_diff(npu_data, bench_data): # 对比每个NPU和Bench所有数据md值，如果有一个不一样则返回0,否则返回1 - for key in zip(npu_data, npu_data): - npu_md5 = npu_data[key].get('md5', '') - bench_md5 = bench_data[key].get('md5', '') + for npu_key, bench_key in zip(npu_data, npu_data): + npu_md5 = npu_data[npu_key].get('md5', '') + bench_md5 = bench_data[bench_key].get('md5', '') if npu_md5 != bench_md5: return 0 return 1 diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/setup.py b/plugins/tensorboard-plugins/tb_graph_ascend/setup.py index 4c4d59e96..ed8a9d06d 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/setup.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/setup.py @@ -16,7 +16,7 @@ # --------------------------------------------------------------------------------------------# import setuptools -VERSION = '1.0.0' +VERSION = '1.0.1' INSTALL_REQUIRED = ["tensorboard >= 2.11.2"] setuptools.setup( -- Gitee From 68a786b913b2573e5581df75f2b90c51a68455f1 Mon Sep 17 00:00:00 2001 From: liguanchi Date: Mon, 24 Mar 2025 11:18:20 +0800 Subject: [PATCH 051/750] =?UTF-8?q?=E5=90=8E=E7=AB=AF=E7=B2=BE=E5=BA=A6?= =?UTF-8?q?=E7=AD=9B=E9=80=89bug?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../tb_graph_ascend/server/plugin.py | 49 +++++++++++++------ 1 file changed, 33 insertions(+), 16 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py index 207e82b31..bfa84a53e 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py @@ -56,7 +56,7 @@ class GraphsPlugin(base_plugin.TBPlugin): self.batch_id = 0 # 将 batch_id 声明为实例变量 self.step_id = 0 # 可以同样声明 step_id self.dfs_node_ids = [] # batch和step没变的话就将所有的nodename存起来，方便快速读取 - self.check_batch_id = 0 # 来配合node_ids监察用的，他不变node_ids就不用重新读取了 + self.check_batch_id = -1 # 来配合node_ids监察用的，他不变node_ids就不用重新读取了 self.check_step_id = 0 # 同上 self.check_tag = None @@ -170,25 +170,42 @@ class GraphsPlugin(base_plugin.TBPlugin): # 返回格式为 [[NPU节点ID列表], [Bench节点ID列表]] return [npu_ids, bench_ids] - def dfs_collect_nodes(self, json_data, request): + def dfs_collect_nodes(self, json_data, request): + root_subnodes_set = [] all_node_names = [] try: batch = request.args.get("batch") - step = request.args.get("step") except ValueError: logger.error('The param "batch" or "step" does not exist or not a valid value') - def should_include_node(micro_step_id, step_id): - return (micro_step_id == batch or batch == '-1' or micro_step_id is None) and ( - step_id == step or step == '-1' or step_id is None - ) + root_node = self.json_get(json_data, 'NPU', 'root') or \ + self.json_get(json_data, 'root') + + root_subnodes = self.json_get(json_data, 'NPU', 'node', root_node, 'subnodes') \ + if 'NPU' in json_data else \ + self.json_get(json_data, 'node', root_node, 'subnodes') + + for node in root_subnodes: + micro_step_id = self.json_get(json_data, 'NPU', 'node', node, 'micro_step_id') \ + if 'NPU' in json_data else \ + self.json_get(json_data, 'node', node, 'micro_step_id') + + if batch == '-1' or str(micro_step_id) == batch: + root_subnodes_set.append(node) + + def traverse_npu(subnodes_set): + npu_data = self.json_get(json_data, 'NPU') + for node in subnodes_set: + node_data = ( + self.json_get(npu_data, 'node', node) if npu_data else self.json_get(json_data, 'node', node) + ) + if node_data.get('subnodes'): + traverse_npu(node_data.get('subnodes')) + else: + all_node_names.append(node) + + traverse_npu(root_subnodes_set) - nodes_data = self.json_get(json_data, 'NPU', 'node') or self.json_get(json_data, 'node') - for node in nodes_data: - micro_step_id = self.json_get(nodes_data, node, 'micro_step_id') - step_id = self.json_get(nodes_data, node, 'step_id') - if should_include_node(micro_step_id, step_id) and not self.json_get(nodes_data, node, 'subnodes'): - all_node_names.append(node) return all_node_names # 拿所有precisonNodes的，与controls的精度筛选联动 @@ -218,15 +235,15 @@ class GraphsPlugin(base_plugin.TBPlugin): tag = request.args.get("tag") json_data = self.check_jsondata(request) - def has_conditions_changed(tag): + def has_conditions_changed(tag, batch): return ( - self.check_batch_id != self.batch_id + self.check_batch_id != batch or self.check_step_id != self.step_id or self.check_tag != tag or self.check_tag is None ) - if has_conditions_changed(tag): + if has_conditions_changed(tag, self.batch_id): self.dfs_node_ids = self.dfs_collect_nodes(json_data, request) self.check_batch_id = self.batch_id self.check_step_id = self.step_id -- Gitee From 7f11e6baf5ed70978ce7265c8c22a8d9ee01baad Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 24 Mar 2025 15:30:49 +0800 Subject: [PATCH 052/750] fix --- debug/accuracy_tools/msprobe/docs/18.online_dispatch.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/debug/accuracy_tools/msprobe/docs/18.online_dispatch.md b/debug/accuracy_tools/msprobe/docs/18.online_dispatch.md index 27ea2d077..b8de3c6d6 100644 --- a/debug/accuracy_tools/msprobe/docs/18.online_dispatch.md +++ b/debug/accuracy_tools/msprobe/docs/18.online_dispatch.md @@ -70,7 +70,7 @@ PyTorch NPU在线精度比对是msprobe工具实现在PyTorch训练过程中直 | api_list | dump范围，dump_mode="list"时设置，需要Dump Aten Ir API名称，默认为None，Aten Ir API名称可以通过dir(torch.ops.aten)查看。 | 否 | | dump_path| dump文件生成的路径。 | 是 | | tag | 传入tag字符串，成为dump文件夹名一部分，默认为None。 | 否 | -| process_num | 多进程并发数，默认为0,最大不超过CPU核数的四分之一。 | 否 | +| process_num | 多进程并发数，默认为0，最大不超过CPU核数的四分之一。 | 否 | | debug | debug信息打印，默认为False。 | 否 | ### dump数据存盘说明 dump数据存盘目录名格式：`atat_tag_rankid_{timestamp}`。 -- Gitee From 9e0a6f4bac50168fcbcf3244afbf3f4bc3b3982f Mon Sep 17 00:00:00 2001 From: RanZheng <364167184@qq.com> Date: Mon, 24 Mar 2025 15:31:23 +0800 Subject: [PATCH 053/750] =?UTF-8?q?=E5=8A=A8=E6=80=81=E5=90=AF=E5=81=9C?= =?UTF-8?q?=E8=B5=84=E6=96=99=E6=B6=A6=E8=89=B2?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../accuracy_tools/msprobe/docs/19.monitor.md | 40 +++++++++---------- 1 file changed, 19 insertions(+), 21 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/19.monitor.md b/debug/accuracy_tools/msprobe/docs/19.monitor.md index 2b0e49fee..6463eaf47 100644 --- a/debug/accuracy_tools/msprobe/docs/19.monitor.md +++ b/debug/accuracy_tools/msprobe/docs/19.monitor.md @@ -426,34 +426,32 @@ csv2tensorboard_by_step( ### 动态启停 动态启停模式：支持用户在训练过程中随时启动/更新监控。 -用户可在训练开始前通过配置环境变量DYNAMIC_MONITOR=True来确认进入动态启停模式，该模式下需要配合config.json文件中的dynamic_on字段来使用。 +用户可在训练开始前通过配置环境变量`DYNAMIC_MONITOR=True`来确认进入动态启停模式，该模式下需要配合config.json文件中的`dynamic_on`字段来使用。 在动态启停模式下，启动和停止分别由如下控制： -- 启动： - 首次监控：查看config.json文件中dynamic_on字段，若为true则在下一步开启监控。 - 非首次监控：查看config文件时间戳，若时间戳更新且config.json文件中dynamic_on字段为true则在下一步开启监控。 -- 停止： - 到达collect_times之后自动停止并改config.json文件中dynamic_on字段为false，可再通过上述操作重启。 +- **启动**： + - 首次监控：查看config.json文件中`dynamic_on`字段，若为`true`则在下一步开启监控。 + - 非首次监控：查看config.json文件时间戳，若时间戳更新且config.json文件中`dynamic_on`字段为`true`则在下一步开启监控。 +- **停止**： + 到达`collect_times`之后自动停止并改config.json文件中`dynamic_on`字段为`false`，可再通过上述操作重启。 -大部分情况下，用户可在看到异常趋势后再手动更新config.json文件并设dynamic_on为true；此外，使用时若想要在一开始就启动监控，可直接设dynamic_on为true做基础配置的监测（首次不要求时间戳更新） +**注意事项：**： -注意事项： +- 默认监控启动皆统一在配置初始化或查询到更新后的下一步，即第n步挂上hook将在第n+1步启动采集，如需采集第0步数据请使用静态模式。 +- config.json中途修改出错时，若此时不在监控则不生效，若在监控则用原配置继续。 +- 达到`collect_times`之后程序会自动将该值置为`false`待下次改`true`重启。 -- 默认监控启动皆统一在配置初始化或查询到更新后的下一步，也就是若第n步挂上hook则第n+1步才启动采集，如需采集第0步数据请用静态模式。 -- config中途修改出错时，若此时不在监控就不生效，若在监控则用原配置继续。 -- 达到collect_times之后会自动将该值置为false待下次改true重启。 +**支持的使用场景说明如下：** -支持的使用场景说明如下： - -| 场景 | 操作方式 | 预期结果 | -|-----------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------| -| 场景1: 使用原始默认的静态模式 | ```export DYNAMIC_MONITOR=False ``` 或不设置 | 走默认分支保存，不受config.json中dynamic_on影响 | -| 场景2: 进入动态启停模式，一开始不想监控 | 1.```export DYNAMIC_MONITOR=True```
    2.config.json中```dynamic_on: false```或不设置 | 无监控，不保存 | -| 场景3: 进入动态启停模式，一开始就想启动监控 | 1.```export DYNAMIC_MONITOR=True```
    2.config.json中```dynamic_on: true``` | 训练开始根据config初始配置在下一步（从0计数时对应为第1步）开启监控并保存，采集collect_times次数后结束监控 | -| 场景4: 进入动态启停模式，一开始不想监控，但想在训练中途启动监控 | 1.```export DYNAMIC_MONITOR=True```
    2.一开始config.json中```dynamic_on: false```或不设置
    3.中途改```dynamic_on: true``` | 训练中途根据config最新配置在下一步开启监控并保存，采集collect_times次数后结束监控 | -| 场景5: 进入动态启停模式，在监控还未结束时中途修改config.json采集配置 | 1.```export DYNAMIC_MONITOR=True```
    2.期间```dynamic_on: true```启动采集
    3.在采集还未达到collect_times次数未结束前，中途修改config.json中采集配置 | 之前采集按照旧配置保存，修改后下一步以更新的config.json采集且collect_times重新按照最新配置从0开始计数。此功能可配合中途collect_times改0来实现提前停止监控 -| 场景6: 进入动态启停模式，在根据collect_times结束监控后，又需要重新启动监控 | 1.```export DYNAMIC_MONITOR=True```
    2.期间```dynamic_on: true```启动采集
    3.采集达到collect_times次数后结束，程序会自动改```dynamic_on:false```
    4.重新改```dynamic_on:true```重启监控 | 之前采集按照旧配置保存，中途停止监控后无保存，重启后下一步以最新config.json重启采集且collect_times重新按照最新配置从0开始计数 +| 场景 | 监控模式 | 操作步骤 | 结果描述 | +|----------------------------------------------|----|----------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------| +| 场景1: 使用默认静态模式 | 静态 | 1. 配置环境变量：`export DYNAMIC_MONITOR=False `
    或不设置该环境变量 | 走默认分支进行数据采集和保存，不受config.json中dynamic_on影响 | +| 场景2: 进入动态启停模式，初始不启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: false`或不设置该字段 | 初始状态下无监控，不进行数据采集和保存 | +| 场景3: 进入动态启停模式，初始即启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: true` | 根据初始配置在第1步（初始计数为0）开启监控并保存，采集`collect_times`次数后结束监控 | +| 场景4: 进入动态启停模式，初始暂不启动监控，训练中途启动 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.开始时配置config.json中`dynamic_on: false`或不设置该字段
    3.中途改`dynamic_on: true` | 训练中途根据最新配置在下一步开启监控并保存，采集collect_times次数后结束监控 | +| 场景5: 进入动态启停模式，监控还未结束时中途修改config.json采集配置 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间配置`dynamic_on: true`启动采集
    3.在采集还未达到`collect_times`次数前，中途修改config.json配置 | 更新前按旧配置采集并保存，更新后下一步以最新config.json采集且collect_times重新从0开始计数。此功能可配合中途collect_times改0来实现提前停止监控。 +| 场景6: 进入动态启停模式，在根据collect_times结束监控后，又需要重新启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间`dynamic_on: true`启动采集
    3.采集达到`collect_times`次数后结束监控，程序自动改`dynamic_on:false`
    4.重新配置`dynamic_on:true`启动监控 | 更新前按旧配置采集并保存，中途停止监控后无采集，重启后下一步以最新config.json重启采集且collect_times重新从0开始计数。 ### 功能重载 此功能将在2026年废弃。请使用[动态启停](#动态启停)功能代替。 -- Gitee From ec3f744e6fa951bc65516ec8736ac246e579e19c Mon Sep 17 00:00:00 2001 From: qianzhengxin Date: Mon, 24 Mar 2025 15:34:46 +0800 Subject: [PATCH 054/750] security remove --- debug/accuracy_tools/msprobe/core/grad_probe/constant.py | 1 + .../msprobe/mindspore/grad_probe/global_context.py | 3 +++ .../msprobe/mindspore/grad_probe/grad_analyzer.py | 3 ++- debug/accuracy_tools/msprobe/mindspore/grad_probe/hook.py | 6 ++---- 4 files changed, 8 insertions(+), 5 deletions(-) diff --git a/debug/accuracy_tools/msprobe/core/grad_probe/constant.py b/debug/accuracy_tools/msprobe/core/grad_probe/constant.py index 22a8b6c13..dead9d922 100644 --- a/debug/accuracy_tools/msprobe/core/grad_probe/constant.py +++ b/debug/accuracy_tools/msprobe/core/grad_probe/constant.py @@ -31,6 +31,7 @@ class GradConst: STEP = "step" BOUNDS = "bounds" OUTPUT_PATH = "output_path" + TIME_STAMP = "time_stamp" # level const LEVEL = "level" diff --git a/debug/accuracy_tools/msprobe/mindspore/grad_probe/global_context.py b/debug/accuracy_tools/msprobe/mindspore/grad_probe/global_context.py index 01e46e019..ca032e61e 100644 --- a/debug/accuracy_tools/msprobe/mindspore/grad_probe/global_context.py +++ b/debug/accuracy_tools/msprobe/mindspore/grad_probe/global_context.py @@ -16,6 +16,7 @@ import os import threading from typing import Dict, Union, Tuple +import time from msprobe.core.common.utils import is_int from msprobe.core.common.file_utils import create_directory, check_path_before_create @@ -69,6 +70,8 @@ class GlobalContext: else: logger.warning("The output_path exists, the data will be covered.") + self._setting[GradConst.TIME_STAMP] = str(int(time.time())) + def get_context(self, key: str): if key not in self._setting: logger.warning(f"Unrecognized {key}.") diff --git a/debug/accuracy_tools/msprobe/mindspore/grad_probe/grad_analyzer.py b/debug/accuracy_tools/msprobe/mindspore/grad_probe/grad_analyzer.py index 8a154f4d6..c46d55b7b 100644 --- a/debug/accuracy_tools/msprobe/mindspore/grad_probe/grad_analyzer.py +++ b/debug/accuracy_tools/msprobe/mindspore/grad_probe/grad_analyzer.py @@ -111,7 +111,8 @@ class CSVGenerator(Process): output_path = context.get_context(GradConst.OUTPUT_PATH) self.level = context.get_context(GradConst.LEVEL) self.bounds = context.get_context(GradConst.BOUNDS) - self.dump_dir = f"{output_path}/rank{rank_id}/Dump/" + time_stamp = context.get_context(GradConst.TIME_STAMP) + self.dump_dir = f"{output_path}/rank{rank_id}/Dump{time_stamp}/" self.save_dir = f"{output_path}/rank{rank_id}/" self.current_step = None self.stop_event = multiprocessing.Event() diff --git a/debug/accuracy_tools/msprobe/mindspore/grad_probe/hook.py b/debug/accuracy_tools/msprobe/mindspore/grad_probe/hook.py index 1aa9fcfad..36857636f 100644 --- a/debug/accuracy_tools/msprobe/mindspore/grad_probe/hook.py +++ b/debug/accuracy_tools/msprobe/mindspore/grad_probe/hook.py @@ -49,12 +49,10 @@ class HookInput: self.param_list = grad_context.get_context(GradConst.PARAM_LIST) self.rank_id = get_rank_id() output_path = grad_context.get_context(GradConst.OUTPUT_PATH) - self.dump_dir = os.path.join(output_path, f"rank{self.rank_id}", "Dump") + time_stamp = grad_context.get_context(GradConst.TIME_STAMP) + self.dump_dir = os.path.join(output_path, f"rank{self.rank_id}", f"Dump{time_stamp}") self.save_dir = os.path.join(output_path, f"rank{self.rank_id}") self.step_finish_flag = os.path.join(self.dump_dir, GradConst.STEP_FINISH) - if os.path.exists(self.save_dir): - logger.warning(f"Delete existing path {self.save_dir}.") - remove_path(self.save_dir) self.level = grad_context.get_context(GradConst.LEVEL) self.bounds = grad_context.get_context(GradConst.BOUNDS) self.mode = mindspore.get_context("mode") -- Gitee From 43f3717c76409ac4e8ff46284597787e19ad65bf Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 24 Mar 2025 15:36:07 +0800 Subject: [PATCH 055/750] fix bug --- debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md | 1 + 1 file changed, 1 insertion(+) diff --git a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md index b453a1fa7..4e6b4be5c 100644 --- a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md @@ -346,6 +346,7 @@ train.py文件： ```Python # 根据需要import包 +import torch from module import ModuleOP # 导入工具的数据采集接口 -- Gitee From 50c2855b061ba89d5c059fa4bb00998283540b94 Mon Sep 17 00:00:00 2001 From: RanZheng <364167184@qq.com> Date: Mon, 24 Mar 2025 15:38:08 +0800 Subject: [PATCH 056/750] =?UTF-8?q?=E5=8A=A8=E6=80=81=E5=90=AF=E5=81=9C?= =?UTF-8?q?=E8=B5=84=E6=96=99=E6=B6=A6=E8=89=B22?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- debug/accuracy_tools/msprobe/docs/19.monitor.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/19.monitor.md b/debug/accuracy_tools/msprobe/docs/19.monitor.md index 6463eaf47..b9b077197 100644 --- a/debug/accuracy_tools/msprobe/docs/19.monitor.md +++ b/debug/accuracy_tools/msprobe/docs/19.monitor.md @@ -444,14 +444,14 @@ csv2tensorboard_by_step( **支持的使用场景说明如下：** -| 场景 | 监控模式 | 操作步骤 | 结果描述 | -|----------------------------------------------|----|----------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------| -| 场景1: 使用默认静态模式 | 静态 | 1. 配置环境变量：`export DYNAMIC_MONITOR=False `
    或不设置该环境变量 | 走默认分支进行数据采集和保存，不受config.json中dynamic_on影响 | -| 场景2: 进入动态启停模式，初始不启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: false`或不设置该字段 | 初始状态下无监控，不进行数据采集和保存 | -| 场景3: 进入动态启停模式，初始即启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: true` | 根据初始配置在第1步（初始计数为0）开启监控并保存，采集`collect_times`次数后结束监控 | -| 场景4: 进入动态启停模式，初始暂不启动监控，训练中途启动 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.开始时配置config.json中`dynamic_on: false`或不设置该字段
    3.中途改`dynamic_on: true` | 训练中途根据最新配置在下一步开启监控并保存，采集collect_times次数后结束监控 | -| 场景5: 进入动态启停模式，监控还未结束时中途修改config.json采集配置 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间配置`dynamic_on: true`启动采集
    3.在采集还未达到`collect_times`次数前，中途修改config.json配置 | 更新前按旧配置采集并保存，更新后下一步以最新config.json采集且collect_times重新从0开始计数。此功能可配合中途collect_times改0来实现提前停止监控。 -| 场景6: 进入动态启停模式，在根据collect_times结束监控后，又需要重新启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间`dynamic_on: true`启动采集
    3.采集达到`collect_times`次数后结束监控，程序自动改`dynamic_on:false`
    4.重新配置`dynamic_on:true`启动监控 | 更新前按旧配置采集并保存，中途停止监控后无采集，重启后下一步以最新config.json重启采集且collect_times重新从0开始计数。 +| 场景 | 监控模式 | 操作步骤 | 结果描述 | +|-----------------------------------------------|----|----------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------| +| 场景1: 使用默认静态模式 | 静态 | 1. 配置环境变量：`export DYNAMIC_MONITOR=False `
    或不设置该环境变量 | 走默认分支进行数据采集和保存，不受config.json中`dynamic_on`影响 | +| 场景2: 进入动态启停模式，初始不启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: false`或不设置该字段 | 初始状态下无监控，不进行数据采集和保存 | +| 场景3: 进入动态启停模式，初始即启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: true` | 根据初始配置在第1步（初始计数为0）开启监控并保存，采集`collect_times`次数后结束监控 | +| 场景4: 进入动态启停模式，初始暂不启动监控，训练中途启动 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.开始时配置config.json中`dynamic_on: false`或不设置该字段
    3.中途改`dynamic_on: true` | 训练中途根据最新配置在下一步开启监控并保存，采集`collect_times`次数后结束监控 | +| 场景5: 进入动态启停模式，监控还未结束时中途修改config.json采集配置 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间配置`dynamic_on: true`启动采集
    3.在采集还未达到`collect_times`次数前，中途修改config.json配置 | 更新前按旧配置采集并保存，更新后下一步以最新config.json采集且`collect_times`重新从0开始计数。此功能可配合中途`collect_times`改0来实现提前停止监控。 +| 场景6: 进入动态启停模式，在根据`collect_times`结束监控后，需重新启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间`dynamic_on: true`启动采集
    3.采集达到`collect_times`次数后结束监控，程序自动改`dynamic_on:false`
    4.重新配置`dynamic_on:true`启动监控 | 更新前按旧配置采集并保存，中途停止监控后无采集，重启后下一步以最新config.json重启采集且`collect_times`重新从0开始计数。 ### 功能重载 此功能将在2026年废弃。请使用[动态启停](#动态启停)功能代替。 -- Gitee From a7ca4911db0feef981cdc537175c1b1e3ed3cad0 Mon Sep 17 00:00:00 2001 From: Henry Shi Date: Mon, 24 Mar 2025 15:16:31 +0800 Subject: [PATCH 057/750] delete jit switch --- debug/accuracy_tools/msprobe/mindspore/service.py | 1 - 1 file changed, 1 deletion(-) diff --git a/debug/accuracy_tools/msprobe/mindspore/service.py b/debug/accuracy_tools/msprobe/mindspore/service.py index fbf25114b..397e62884 100644 --- a/debug/accuracy_tools/msprobe/mindspore/service.py +++ b/debug/accuracy_tools/msprobe/mindspore/service.py @@ -311,7 +311,6 @@ class Service: if self.config.step and self.current_iter not in self.config.step: JitDump.jit_dump_switch = False return - JitDump.jit_dump_switch = True self.model = self.check_model_valid(model) logger.info(f"{Const.TOOL_NAME}: debugger.start() is set successfully") -- Gitee From a5800d8eb8dda440a1c187172810f542138a999f Mon Sep 17 00:00:00 2001 From: RanZheng <364167184@qq.com> Date: Mon, 24 Mar 2025 15:45:56 +0800 Subject: [PATCH 058/750] =?UTF-8?q?=E5=8A=A8=E6=80=81=E5=90=AF=E5=81=9C?= =?UTF-8?q?=E8=B5=84=E6=96=99=E6=B6=A6=E8=89=B23?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- debug/accuracy_tools/msprobe/docs/19.monitor.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/19.monitor.md b/debug/accuracy_tools/msprobe/docs/19.monitor.md index b9b077197..4d9d31188 100644 --- a/debug/accuracy_tools/msprobe/docs/19.monitor.md +++ b/debug/accuracy_tools/msprobe/docs/19.monitor.md @@ -444,14 +444,14 @@ csv2tensorboard_by_step( **支持的使用场景说明如下：** -| 场景 | 监控模式 | 操作步骤 | 结果描述 | -|-----------------------------------------------|----|----------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------| -| 场景1: 使用默认静态模式 | 静态 | 1. 配置环境变量：`export DYNAMIC_MONITOR=False `
    或不设置该环境变量 | 走默认分支进行数据采集和保存，不受config.json中`dynamic_on`影响 | -| 场景2: 进入动态启停模式，初始不启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: false`或不设置该字段 | 初始状态下无监控，不进行数据采集和保存 | -| 场景3: 进入动态启停模式，初始即启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: true` | 根据初始配置在第1步（初始计数为0）开启监控并保存，采集`collect_times`次数后结束监控 | -| 场景4: 进入动态启停模式，初始暂不启动监控，训练中途启动 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.开始时配置config.json中`dynamic_on: false`或不设置该字段
    3.中途改`dynamic_on: true` | 训练中途根据最新配置在下一步开启监控并保存，采集`collect_times`次数后结束监控 | -| 场景5: 进入动态启停模式，监控还未结束时中途修改config.json采集配置 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间配置`dynamic_on: true`启动采集
    3.在采集还未达到`collect_times`次数前，中途修改config.json配置 | 更新前按旧配置采集并保存，更新后下一步以最新config.json采集且`collect_times`重新从0开始计数。此功能可配合中途`collect_times`改0来实现提前停止监控。 -| 场景6: 进入动态启停模式，在根据`collect_times`结束监控后，需重新启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间`dynamic_on: true`启动采集
    3.采集达到`collect_times`次数后结束监控，程序自动改`dynamic_on:false`
    4.重新配置`dynamic_on:true`启动监控 | 更新前按旧配置采集并保存，中途停止监控后无采集，重启后下一步以最新config.json重启采集且`collect_times`重新从0开始计数。 +| 场景 | 监控模式 | 操作步骤 | 结果描述 | +|-----------------------------------------------|----|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------| +| 场景1: 使用默认静态模式 | 静态 | 1. 配置环境变量：`export DYNAMIC_MONITOR=False `
    或不设置该环境变量 | 走默认分支进行数据采集和保存，不受config.json中`dynamic_on`影响 | +| 场景2: 进入动态启停模式，初始不启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: false`或不设置该字段 | 初始状态下无监控，不进行数据采集和保存 | +| 场景3: 进入动态启停模式，初始即启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.配置config.json中`dynamic_on: true` | 根据初始配置在第1步（初始计数为0）开启监控并保存，采集`collect_times`次数后结束监控 | +| 场景4: 进入动态启停模式，初始暂不启动监控，训练中途启动 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.开始时配置config.json中`dynamic_on: false`或不设置该字段
    3.训练中途修改config.json中`dynamic_on: true` | 训练中途根据最新配置在下一步开启监控并保存，采集`collect_times`次数后结束监控 | +| 场景5: 进入动态启停模式，监控还未结束时中途修改config.json采集配置 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间配置`dynamic_on: true`启动采集
    3.在采集还未达到`collect_times`次数前，中途修改config.json配置 | 更新前按旧配置采集并保存，更新后下一步以最新config.json采集且`collect_times`重新从0开始计数。此功能可配合中途`collect_times`改0来实现提前停止监控。 +| 场景6: 进入动态启停模式，在根据`collect_times`结束监控后，需重新启动监控 | 动态 | 1.配置环境变量：`export DYNAMIC_MONITOR=True`
    2.期间`dynamic_on: true`启动采集
    3.采集达到`collect_times`次数后结束监控，程序自动改`dynamic_on:false`
    4.配置config.json中`dynamic_on:true`重启监控 | 更新前按旧配置采集并保存，中途停止监控后无采集，重启后下一步以最新config.json重启采集且`collect_times`重新从0开始计数。 ### 功能重载 此功能将在2026年废弃。请使用[动态启停](#动态启停)功能代替。 -- Gitee From 5bfa21a49c3de7ba3577bed7c19dbbb9184d1b9f Mon Sep 17 00:00:00 2001 From: yangxinxian <947098055@qq.com> Date: Mon, 24 Mar 2025 16:12:32 +0800 Subject: [PATCH 059/750] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E5=AE=89=E5=85=A8?= =?UTF-8?q?=E9=97=AE=E9=A2=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- debug/accuracy_tools/msprobe/pytorch/function_factory.py | 2 +- debug/accuracy_tools/msprobe/pytorch/pt_config.py | 4 +++- debug/accuracy_tools/msprobe/pytorch/service.py | 2 +- .../accuracy_tools/msprobe/test/pytorch_ut/test_pt_config.py | 2 +- 4 files changed, 6 insertions(+), 4 deletions(-) diff --git a/debug/accuracy_tools/msprobe/pytorch/function_factory.py b/debug/accuracy_tools/msprobe/pytorch/function_factory.py index 247e2cd0e..f515b5d47 100644 --- a/debug/accuracy_tools/msprobe/pytorch/function_factory.py +++ b/debug/accuracy_tools/msprobe/pytorch/function_factory.py @@ -70,7 +70,7 @@ class Register(dict): def add_register_item(key, value): if key in self._dict: - logger.warning(f"{value.__name__} has been registered before, so we will overriden it.") + logger.warning(f"{value.__name__} has been registered before, so we will override it.") self[key] = value return value diff --git a/debug/accuracy_tools/msprobe/pytorch/pt_config.py b/debug/accuracy_tools/msprobe/pytorch/pt_config.py index 8293ac969..64a11a092 100644 --- a/debug/accuracy_tools/msprobe/pytorch/pt_config.py +++ b/debug/accuracy_tools/msprobe/pytorch/pt_config.py @@ -95,6 +95,8 @@ class OverflowCheckConfig(BaseConfig): def check_overflow_config(self): if self.overflow_nums is not None and not is_int(self.overflow_nums): raise Exception("overflow_num is invalid") + if self.overflow_nums is not None and self.overflow_nums != -1 and self.overflow_nums <= 0: + raise Exception("overflow_nums should be -1 or positive integer") if self.check_mode is not None and self.check_mode not in ["all", "aicore", "atomic"]: raise Exception("check_mode is invalid") @@ -148,7 +150,7 @@ class FreeBenchmarkCheckConfig(BaseConfig): self.pert_mode in PytorchFreeBenchmarkConst.CPU_MODE_LIST ): msg = ( - f"You neet to and can only set fuzz_device as {DeviceType.CPU} " + f"You need to and can only set fuzz_device as {DeviceType.CPU} " f"when pert_mode in {PytorchFreeBenchmarkConst.CPU_MODE_LIST}" ) logger.error_log_with_exp( diff --git a/debug/accuracy_tools/msprobe/pytorch/service.py b/debug/accuracy_tools/msprobe/pytorch/service.py index b0b278032..27235292e 100644 --- a/debug/accuracy_tools/msprobe/pytorch/service.py +++ b/debug/accuracy_tools/msprobe/pytorch/service.py @@ -412,7 +412,7 @@ class Service: if self.config.nfs_path: self.attl.upload("end") elif self.attl.socket_manager is not None: - logger.info(f"pid: {os.getpid()} finished, start send STOP signal.") + logger.info(f"pid: {os.getpid()} finished, start sends STOP signal.") self.attl.socket_manager.send_stop_signal() def reset_status(self): diff --git a/debug/accuracy_tools/msprobe/test/pytorch_ut/test_pt_config.py b/debug/accuracy_tools/msprobe/test/pytorch_ut/test_pt_config.py index c1b8bac47..d5c7fdea2 100644 --- a/debug/accuracy_tools/msprobe/test/pytorch_ut/test_pt_config.py +++ b/debug/accuracy_tools/msprobe/test/pytorch_ut/test_pt_config.py @@ -268,7 +268,7 @@ class TestFreeBenchmarkCheckConfig(unittest.TestCase): invalid_config["fuzz_device"] = "cpu" invalid_config["pert_mode"] = "INVALID_CPU_MODE" config = FreeBenchmarkCheckConfig(invalid_config) - self.assertIn("You neet to and can only set fuzz_device as ", str(mock_error.call_args)) + self.assertIn("You need to and can only set fuzz_device as ", str(mock_error.call_args)) @patch('msprobe.core.common.log.logger.error_log_with_exp') def test_check_handler_type_invalid(self, mock_error): -- Gitee From b94dda344f6bafa307ae12110ac02265858d22a4 Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 24 Mar 2025 16:31:53 +0800 Subject: [PATCH 060/750] fix review --- debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md index 4e6b4be5c..25084af57 100644 --- a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md @@ -352,7 +352,7 @@ from module import ModuleOP # 导入工具的数据采集接口 from msprobe.pytorch import PrecisionDebugger -# 在模型训练开始前实例化PrecisionDebugger +# 将PrecisionDebugger的实例化放在文件的开始位置，即导包后的位置，确保所有API都被封装 debugger = PrecisionDebugger(config_path='./config.json') if __name__ == "__main__": -- Gitee From b242d55be570cd55697986abaf989942e95f4e92 Mon Sep 17 00:00:00 2001 From: qianzhengxin Date: Mon, 24 Mar 2025 16:53:19 +0800 Subject: [PATCH 061/750] fix ut --- .../test/mindspore_ut/grad_probe/test_grad_analyzer.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/debug/accuracy_tools/msprobe/test/mindspore_ut/grad_probe/test_grad_analyzer.py b/debug/accuracy_tools/msprobe/test/mindspore_ut/grad_probe/test_grad_analyzer.py index 802769d90..af8f6b047 100644 --- a/debug/accuracy_tools/msprobe/test/mindspore_ut/grad_probe/test_grad_analyzer.py +++ b/debug/accuracy_tools/msprobe/test/mindspore_ut/grad_probe/test_grad_analyzer.py @@ -1,6 +1,7 @@ import os import shutil import json +import time import numpy as np import mindspore as ms from unittest import TestCase, mock @@ -15,7 +16,8 @@ class TestGradAnalyzer(TestCase): @classmethod def setUpClass(cls): cls.output_path = "./test_output" - cls.dump_dir = f"{cls.output_path}/rank0/Dump" + cls.time_stamp = str(int(time.time())) + cls.dump_dir = f"{cls.output_path}/rank0/Dump{cls.time_stamp}" cls.save_dir = f"{cls.output_path}/rank0" os.makedirs(cls.dump_dir, exist_ok=True) @@ -31,7 +33,8 @@ class TestGradAnalyzer(TestCase): 'get_context.side_effect': lambda x: { GradConst.OUTPUT_PATH: self.output_path, GradConst.LEVEL: GradConst.LEVEL2, - GradConst.BOUNDS: [-0.1, 0.0, 0.1] + GradConst.BOUNDS: [-0.1, 0.0, 0.1], + GradConst.TIME_STAMP: self.time_stamp, }[x] })) # Clear dump directory before each test -- Gitee From 584e371d778c65150a50c62a7125bbe6a1acd9ca Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 24 Mar 2025 16:53:42 +0800 Subject: [PATCH 062/750] fix bug --- debug/accuracy_tools/msprobe/core/common/const.py | 1 + .../accuracy_tools/msprobe/pytorch/online_dispatch/dispatch.py | 2 ++ 2 files changed, 3 insertions(+) diff --git a/debug/accuracy_tools/msprobe/core/common/const.py b/debug/accuracy_tools/msprobe/core/common/const.py index f7ba9f90d..1ab203d85 100644 --- a/debug/accuracy_tools/msprobe/core/common/const.py +++ b/debug/accuracy_tools/msprobe/core/common/const.py @@ -52,6 +52,7 @@ class Const: SIX_SEGMENT = 6 SEVEN_SEGMENT = 7 MAX_DEPTH = 10 + CPU_QUARTER = 4 # dump mode ALL = "all" diff --git a/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dispatch.py b/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dispatch.py index b9201cfaa..9fafda46f 100644 --- a/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dispatch.py +++ b/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dispatch.py @@ -16,6 +16,7 @@ import json import os import time +import multiprocessing from multiprocessing import Pool import torch @@ -85,6 +86,7 @@ class PtdbgDispatch(TorchDispatchMode): self.get_ops(yaml_path) self.lock = None + max_process_num = max(int((multiprocessing.cpu_count() + 1) // Const.CPU_QUARTER), 1) if process_num > 0: self.pool = Pool(process_num) if debug: -- Gitee From c442ff63fa3468646590652964b39276d747f403 Mon Sep 17 00:00:00 2001 From: liguanchi Date: Mon, 24 Mar 2025 16:55:40 +0800 Subject: [PATCH 063/750] =?UTF-8?q?=E5=86=97=E4=BD=99=E5=88=A0=E9=99=A4?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../fe/src/tf_graph/tf-graph-scene.ts | 17 +- .../fe/src/tf_graph_board/tf-graph-board.ts | 60 --- .../fe/src/tf_graph_common/graph.ts | 26 - .../fe/src/tf_graph_common/hierarchy.ts | 459 +--------------- .../fe/src/tf_graph_common/layout.ts | 127 +---- .../fe/src/tf_graph_common/node.ts | 29 - .../fe/src/tf_graph_common/parser.ts | 48 +- .../fe/src/tf_graph_common/proto.ts | 138 ----- .../fe/src/tf_graph_common/render.ts | 510 ------------------ .../fe/src/tf_graph_common/scene.ts | 2 +- .../fe/src/tf_graph_common/tf-graph-icon.ts | 6 +- .../tf-graph-dashboard-loader.ts | 14 - 12 files changed, 9 insertions(+), 1427 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts index 6ef9ba1fe..84a90dc1e 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts @@ -231,19 +231,6 @@ class TfGraphScene2 extends LegacyElementMixin(DarkModeMixin(PolymerElement)) im setTimeout(this.fit.bind(this), tf_graph_layout.PARAMS.animation.duration); } - // When renderHierarchy changes, we need to first build the new SVG based - // on the new hierarchy (and it is asynchronous). We will let that observer - // update the input trace. - @observe('traceInputs', 'selectedNode') - _updateInputTrace(): void { - tf_graph_scene_node.updateInputTrace( - this.getGraphSvgRoot(), - this.renderHierarchy, - this.selectedNode, - this.traceInputs, - ); - } - getNode(nodeName): tf_graph_render.RenderNodeInfo { return this.renderHierarchy.getRenderNodeByName(nodeName); } @@ -313,7 +300,6 @@ class TfGraphScene2 extends LegacyElementMixin(DarkModeMixin(PolymerElement)) im (): void => { tf_graph_scene_node.buildGroupForScene(d3.select(this.$.root), renderHierarchy.root, this); tf_graph_scene.addGraphClickListener(this.$.svg, this); - this._updateInputTrace(); }, tb_debug.GraphDebugEventId.RENDER_SCENE_BUILD_SCENE, ); @@ -620,8 +606,7 @@ class TfGraphScene2 extends LegacyElementMixin(DarkModeMixin(PolymerElement)) im } if ( node.node.type === (tf_graph.NodeType.META || tf_graph.NodeType.API_LIST || tf_graph.NodeType.MULTI_COLLECTION) && - (node.node as any).associatedFunction && - !node.isLibraryFunction + (node.node as any).associatedFunction ) { // The node is that of a function call. Also link the node within the // function library. This clarifies to the user that the library function diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts index 496506940..81b79b708 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts @@ -203,32 +203,6 @@ class TfGraphBoard extends LegacyElementMixin(PolymerElement) { @property({ type: Object }) hierarchyParams: tf_graph_hierarchy.HierarchyParams = tf_graph_hierarchy.DefaultHierarchyParams; - /** - * A number between 0 and 100 denoting the % of progress - * for the progress bar and the displayed message. - * @type {{value: number, msg: string}} - */ - @property({ type: Object }) - progress: object; - - @property({ type: Boolean }) - traceInputs: boolean; - - @property({ type: Boolean }) - autoExtractNodes: boolean; - - @property({ type: Object, notify: true }) - renderHierarchy: tf_graph_render.MergedRenderGraphInfo; - - // Whether debugger data is enabled for this instance of Tensorboard. - @property({ type: Boolean }) - debuggerDataEnabled: boolean; - - @property({ type: Array, notify: true }) - // An array of alerts (in chronological order) provided by debugging libraries on when bad - // values (NaN, +/- Inf) appear. - debuggerNumericAlerts: unknown[]; - @property({ type: Boolean, notify: true }) allStepsModeEnabled: boolean = false; @@ -238,41 +212,7 @@ class TfGraphBoard extends LegacyElementMixin(PolymerElement) { @property({ type: Object }) colorset: any; - @property({ type: String, notify: true }) - selectedNode: string; - - @property({ type: Object, notify: true }) - selectedEdge: tf_graph_render.EdgeData; - - // A function with signature EdgeThicknessFunction that computes the - // thickness of a given edge. - @property({ type: Object }) - edgeWidthFunction: object; - - @property({ type: String }) - _highlightedNode: string; - - // An optional function that takes a node selected event (whose `detail` - // property is the selected node ... which could be null if a node is - // deselected). Called whenever a node is selected or deselected. - @property({ type: Object }) - handleNodeSelected: object; - - // An optional function that computes the label for an edge. Should - // implement the EdgeLabelFunction signature. - @property({ type: Object }) - edgeLabelFunction: object; - - // An optional callback that implements the tf.graph.edge.EdgeSelectionCallback signature. If - // provided, edges are selectable, and this callback is run when an edge is selected. - @property({ type: Object }) - handleEdgeSelected: object; - - @property({ type: Object }) - selection: object; - @property({ type: Object }) - tooltips: object; selectNodeCopy: string = ''; ready(): void { diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/graph.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/graph.ts index 7a29671a1..86de37513 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/graph.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/graph.ts @@ -724,32 +724,6 @@ class SeriesNodeImpl implements SeriesNode { nodeAttributes: { [key: string]: any; }; - - constructor( - prefix: string, - suffix: string, - parent: string, - clusterId: number, - name: string, - graphOptions: LabeledGraphOptions, - ) { - this.name = name || getSeriesNodeName(prefix, suffix, parent); - this.type = NodeType.SERIES; - this.hasLoop = false; - this.prefix = prefix; - this.suffix = suffix; - this.clusterId = clusterId; - this.ids = []; - this.parent = parent; - this.isGroupNode = true; - this.cardinality = 0; - this.metagraph = createGraph(name, GraphType.SERIES, graphOptions); - // bridgegraph must be constructed lazily-see hierarchy.getBridgegraph() - this.bridgegraph = null; - this.parentNode = null; - this.hasNonControlEdges = false; - this.include = InclusionType.UNSPECIFIED; - } } /** diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/hierarchy.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/hierarchy.ts index c8115a867..716c59a5b 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/hierarchy.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/hierarchy.ts @@ -27,19 +27,15 @@ import { createGraph, createMetaedge, createMetanode, - createSeriesNode, Edges, - getSeriesNodeName, GraphType, GroupNode, Metaedge, MetaedgeImpl, Metanode, Node, - NodeType, OpNode, ROOT_NAME, - SeriesNode, SlimGraph, MetanodeImpl, } from './graph'; @@ -52,9 +48,6 @@ export enum HierarchyEvent { TEMPLATES_UPDATED = 0, } -// A map from the name of a series node to its grouping type. -type SeriesGroupMap = Map; - // Including both the NPU and the benchmark hierarchy. export interface MergedHierarchy { npu: Hierarchy; @@ -87,40 +80,17 @@ export class Hierarchy extends tf_graph_util.Dispatcher { private index: { [nodeName: string]: GroupNode | OpNode; }; - private readonly seriesGroupMap: SeriesGroupMap; constructor(params: HierarchyParams) { super(); this.graphOptions.compound = true; this.graphOptions.rankdir = params.rankDirection; this.root = createMetanode(ROOT_NAME, this.graphOptions); - this.seriesGroupMap = new Map(params.seriesMap); - /** - * @type {Object} Dictionary object that maps node name to the node - * (could be op-node, metanode, or series-node) - */ this.index = {}; this.index[ROOT_NAME] = this.root; this.orderings = {}; } - getSeriesGroupType(nodeName: string): tf_graph.SeriesGroupingType { - // If grouping was not specified, assume it should be grouped by default. - return this.seriesGroupMap.get(nodeName) ?? tf_graph.SeriesGroupingType.GROUP; - } - - setSeriesGroupType(nodeName: string, groupType: tf_graph.SeriesGroupingType): SeriesGroupMap { - return this.seriesGroupMap.set(nodeName, groupType); - } - - buildSeriesGroupMapToggled(nodeName: string): Map { - const newGroupType = - this.getSeriesGroupType(nodeName) === tf_graph.SeriesGroupingType.GROUP - ? tf_graph.SeriesGroupingType.UNGROUP - : tf_graph.SeriesGroupingType.GROUP; - return new Map([...this.seriesGroupMap, [nodeName, newGroupType]]); - } - getNodeMap(): { [nodeName: string]: GroupNode | OpNode; } { @@ -410,24 +380,12 @@ function findEdgeTargetsInGraph(graph: graphlib.Graph, node: Node, inbound: bool export interface HierarchyParams { verifyTemplate: boolean; - seriesNodeMinSize: number; - // The initial map of explicit series group types. - seriesMap: SeriesGroupMap; - // This string is supplied to dagre as the 'rankdir' property for laying out - // the graph. TB, BT, LR, or RL. The default is 'BT' (bottom to top). rankDirection: string; - // Whether to detect numeric patterns for series nodes using entire names of - // nodes. If false, only uses numeric suffixes to find patterns to collapse - // into series nodes. - useGeneralizedSeriesPatterns: boolean; } export const DefaultHierarchyParams: HierarchyParams = { verifyTemplate: true, - seriesNodeMinSize: 5, - seriesMap: new Map(), rankDirection: 'TB', - useGeneralizedSeriesPatterns: false, }; /** @@ -440,9 +398,6 @@ export function build( tracker?: ProgressTracker, ): Promise { const h = new Hierarchy(params); - const seriesNames: { - [name: string]: string; - } = {}; return tf_graph_util .runAsyncTask( 'Adding nodes', @@ -453,26 +408,6 @@ export function build( tracker, tb_debug.GraphDebugEventId.HIERARCHY_ADD_NODES, ) - .then(() => { - return tf_graph_util.runAsyncTask( - 'Detect series', - 30, - () => { - if (params.seriesNodeMinSize > 0) { - groupSeries( - h.root, - h, - seriesNames, - params.seriesNodeMinSize, - params.seriesMap, - params.useGeneralizedSeriesPatterns, - ); - } - }, - tracker, - tb_debug.GraphDebugEventId.HIERARCHY_DETECT_SERIES, - ); - }) .then(() => { return tf_graph_util.runAsyncTask( 'Adding edges', @@ -568,396 +503,4 @@ function addEdgesInVis(h: Hierarchy, graph: SlimGraph, nodeName: string): void { } metaedge.addBaseEdge(baseEdge, h, true); }); -} - -/** - * Using the hierarchy template information, detect series in the provided - * metanode. For each detected series, create a new SeriesNode - * and remove series members from the metanode's metagraph and move them to - * the new series node's metagraph. - * - * @param metanode - * @param hierarchy - * @param seriesNames Map of node names to their series they are contained in. - * This should be provided empty and is populated by this method. - * @param threshold If the series has this many nodes or more, then group them - * into a series. - * @param map Map of series names to their series grouping type, if one has - * been set. - * @param useGeneralizedSeriesPatterns Whether to use find patterns for series - * nodes using any parts of names of nodes. If false, only uses patterns - * discovered within numeric suffixes of nodes names. - * @return A dictionary from node name to series node name that contains the - * node. - */ -function groupSeries( - metanode: Metanode, - hierarchy: Hierarchy, - seriesNames: { - [name: string]: string; - }, - threshold: number, - seriesMap: SeriesGroupMap, - useGeneralizedSeriesPatterns: boolean, -): void { - let metagraph = metanode.metagraph; - _.each(metagraph.nodes(), (n) => { - let child = metagraph.node(n); - if (child.type === (tf_graph.NodeType.META || tf_graph.NodeType.MULTI_COLLECTION || tf_graph.NodeType.API_LIST)) { - groupSeries( - child as unknown as Metanode, - hierarchy, - seriesNames, - threshold, - seriesMap, - useGeneralizedSeriesPatterns, - ); - } - }); - let clusters = clusterNodes(metagraph); - const detectSeriesMethod = useGeneralizedSeriesPatterns - ? detectSeriesAnywhereInNodeName - : detectSeriesUsingNumericSuffixes; - let seriesDict = detectSeriesMethod(clusters, metagraph, hierarchy.graphOptions); - // Add each series node to the graph and add its grouped children to its own - // metagraph. - _.each(seriesDict, (seriesNode: SeriesNode, seriesName: string) => { - let nodeMemberNames = seriesNode.metagraph.nodes(); - _.each(nodeMemberNames, (n) => { - let child = metagraph.node(n) as any; - if (!child.owningSeries) { - child.owningSeries = seriesName; - } - }); - // If the series contains less than the threshold number of nodes, then set - // this series to be shown ungrouped in the map. - if ( - nodeMemberNames.length < threshold && - hierarchy.getSeriesGroupType(seriesNode.name) === tf_graph.SeriesGroupingType.GROUP - ) { - hierarchy.setSeriesGroupType(seriesNode.name, tf_graph.SeriesGroupingType.UNGROUP); - } - // If the series is in the map as ungrouped then do not group the series. - if (hierarchy.getSeriesGroupType(seriesNode.name) === tf_graph.SeriesGroupingType.UNGROUP) { - return; - } - hierarchy.setNode(seriesName, seriesNode); // add to the index - metagraph.setNode(seriesName, seriesNode); - _.each(nodeMemberNames, (n) => { - let child = metagraph.node(n) as any; - seriesNode.metagraph.setNode(n, child); - seriesNode.parentNode = child.parentNode; - seriesNode.cardinality++; - child.parentNode = seriesNode; - seriesNames[n] = seriesName; - // Remove now-grouped node from its original parent's metagraph. - metagraph.removeNode(n); - }); - }); -} - -/** - * Cluster op-nodes with similar op. This examines only the direct children of - * the metagraph, does not recursively check descendants. - * @return A map from op to a list of node names. - */ -function clusterNodes(metagraph: graphlib.Graph): { - [clusterId: string]: string[]; -} { - let result: { - [clusterId: string]: string[]; - } = {}; - return _.reduce( - metagraph.nodes(), - ( - clusters: { - [clusterId: string]: string[]; - }, - n: string, - ) => { - let child = metagraph.node(n); - if (child.type === (NodeType.META || NodeType.MULTI_COLLECTION || NodeType.API_LIST)) { - // skip metanodes - return clusters; - } - let template = (child as any).op; - if (template) { - clusters[template] = clusters[template] || []; - clusters[template].push(child.name); - } - return clusters; - }, - result, - ); -} - -/** - * For each cluster of op-nodes based op type, try to detect groupings. - * Infer series name using by trying to find pattern '' towards the end - * of node names. - * - * @param clusters Dictionary output from clusterNodes(). - * @param metagraph - * @return A dictionary from series name => seriesNode - */ -function detectSeriesUsingNumericSuffixes( - clusters: { - [clusterId: string]: string[]; - }, - metagraph: graphlib.Graph, - graphOptions: tf_graph.LabeledGraphOptions, -): { - [seriesName: string]: SeriesNode; -} { - let seriesDict: { - [seriesName: string]: SeriesNode; - } = {}; - _.each(clusters, (members, clusterId: string) => { - if (members.length <= 1) { - return; - } // isolated clusters can't make series - /** @type {Object} A dictionary mapping seriesName to seriesInfoArray, - * which is an array that contains objects with name, id, prefix, suffix, - * and parent properties. - */ - let candidatesDict: { - [seriesName: string]: SeriesNode[]; - } = {}; - // Group all nodes that have the same name, with the exception of a - // number at the end of the name after an underscore, which is allowed to - // vary. - _.each(members, (name: string) => { - const isGroup = name.charAt(name.length - 1) === '*'; - const namepath = name.split('/'); - const leaf = namepath[namepath.length - 1]; - const parent = namepath.slice(0, namepath.length - 1).join('/'); - const matches = leaf.match(/^(?\D*)(?\d+)$/); - - let prefix; - let id; - let suffix = ''; - if (matches) { - // if found '' in the name, assign id. - prefix = matches[1]; // the front non-numeric characters - id = matches[2]; // the digits - } else { - // for node without '_', make them zero-th items. - prefix = isGroup ? leaf.substr(0, leaf.length - 1) : leaf; - id = 0; - suffix = isGroup ? '*' : ''; - } - const seriesName = getSeriesNodeName(prefix, suffix, parent); - candidatesDict[seriesName] = candidatesDict[seriesName] || []; - const seriesNode = createSeriesNode(prefix, suffix, parent, Number(id), name, graphOptions); - candidatesDict[seriesName].push(seriesNode); - }); - // In each group of nodes, group nodes in bunches that have monotonically - // increasing numbers in their names. Each of these bunches is a series. - _.each(candidatesDict, (seriesInfoArray: SeriesNode[], seriesName) => { - if (seriesInfoArray.length < 2) { - return; - } - seriesInfoArray.sort((a, b) => { - return Number(a.clusterId) - Number(b.clusterId); - }); - // Loop through the nodes sorted by its detected series number, grouping - // all nodes with monotonically-increasing series numbers. - let seriesNodes = [seriesInfoArray[0]]; - for (let index = 1; index < seriesInfoArray.length; index++) { - let nextNode = seriesInfoArray[index]; - if (nextNode.clusterId === seriesNodes[seriesNodes.length - 1].clusterId + 1) { - seriesNodes.push(nextNode); - continue; - } - addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); - seriesNodes = [nextNode]; - } - addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); - }); - }); - return seriesDict; -} - -/** - * For each cluster of op-nodes based op type, try to detect groupings. - * Infer series name using by trying to find a pattern of numbers - * anywhere within node names. - * - * @param clusters Dictionary output from clusterNodes(). - * @param metagraph - * @return A dictionary from series name => seriesNode - */ -function detectSeriesAnywhereInNodeName( - clusters: { - [clusterId: string]: string[]; - }, - metagraph: graphlib.Graph, - graphOptions: tf_graph.LabeledGraphOptions, -): { - [seriesName: string]: SeriesNode; -} { - let seriesDict: { - [seriesName: string]: SeriesNode; - } = {}; - _.each(clusters, (members, clusterId: string) => { - if (members.length <= 1) { - return; - } // isolated clusters can't make series - /** - * @type {Object} A dictionary mapping a series name to a SeriesNode. - */ - let forwardDict: { - [seriesName: string]: SeriesNode; - } = {}; - /** - * @type {Object} A dictionary mapping member name to an array of series - * names this member could potentially be grouped under and the - * corresponding ids. - */ - let reverseDict: { - [seriesName: string]: any[]; - } = {}; - // Group all nodes that have the same name, with the exception of a - // number at the end of the name after an underscore, which is allowed to - // vary. - _.each(members, (name: string) => { - let isGroup = name.charAt(name.length - 1) === '*'; - let namepath = name.split('/'); - let leaf = namepath[namepath.length - 1]; - let parent = namepath.slice(0, namepath.length - 1).join('/'); - const numRegex = /(?\d+)/g; - let matches = []; - let matchResult; - let prefix; - let id; - let suffix; - let seriesName; - let matched = 0; - // Scan over the entire leaf name and match any possible numbers, - // and put the results into corresponding dictionaries. - while ((matchResult = numRegex.exec(leaf))) { - ++matched; - prefix = leaf.slice(0, matchResult.index); - id = matchResult[0]; - suffix = leaf.slice(matchResult.index + matchResult[0].length); - seriesName = getSeriesNodeName(prefix, suffix, parent); - forwardDict[seriesName] = forwardDict[seriesName]; - if (!forwardDict[seriesName]) { - forwardDict[seriesName] = createSeriesNode(prefix, suffix, parent, Number(id), name, graphOptions); - } - forwardDict[seriesName].ids.push(id); - reverseDict[name] = reverseDict[name] || []; - reverseDict[name].push([seriesName, id]); - } - if (matched < 1) { - prefix = isGroup ? leaf.substr(0, leaf.length - 1) : leaf; - id = 0; - suffix = isGroup ? '*' : ''; - seriesName = getSeriesNodeName(prefix, suffix, parent); - forwardDict[seriesName] = forwardDict[seriesName]; - if (!forwardDict[seriesName]) { - forwardDict[seriesName] = createSeriesNode(prefix, suffix, parent, Number(id), name, graphOptions); - } - forwardDict[seriesName].ids.push(id); - reverseDict[name] = reverseDict[name] || []; - reverseDict[name].push([seriesName, id]); - } - }); - /** @type {Object} A dictionary mapping seriesName to seriesInfoArray, - * which is an array that contains objects with name, id, prefix, suffix, - * and parent properties. - */ - let candidatesDict: { - [seriesName: string]: SeriesNode[]; - } = {}; - // For each of the member, put it into the maximum possible series, - // and create candidatesDict accordingly. - _.each(reverseDict, (seriesNameIdArray, name) => { - seriesNameIdArray.sort((a, b) => { - return forwardDict[b[0]].ids.length - forwardDict[a[0]].ids.length; - }); - let seriesName = seriesNameIdArray[0][0]; - let id = seriesNameIdArray[0][1]; - candidatesDict[seriesName] = candidatesDict[seriesName] || []; - const namepath = name.split('/'); - const leaf = namepath[namepath.length - 1]; - const parent = namepath.slice(0, namepath.length - 1).join('/'); - let seriesNode = createSeriesNode( - forwardDict[seriesName].prefix, - forwardDict[seriesName].suffix, - parent, - Number(id), - name, - graphOptions, - ); - candidatesDict[seriesName].push(seriesNode); - }); - // In each group of nodes, group nodes in bunches that have monotonically - // increasing numbers in their names. Each of these bunches is a series. - _.each(candidatesDict, (seriesInfoArray: SeriesNode[], seriesName) => { - if (seriesInfoArray.length < 2) { - return; - } - seriesInfoArray.sort((a, b) => { - return Number(a.clusterId) - Number(b.clusterId); - }); - // Loop through the nodes sorted by its detected series number, grouping - // all nodes with monotonically-increasing series numbers. - let seriesNodes = [seriesInfoArray[0]]; - for (let index = 1; index < seriesInfoArray.length; index++) { - let nextNode = seriesInfoArray[index]; - if (nextNode.clusterId === seriesNodes[seriesNodes.length - 1].clusterId + 1) { - seriesNodes.push(nextNode); - continue; - } - addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); - seriesNodes = [nextNode]; - } - addSeriesToDict(seriesNodes, seriesDict, Number(clusterId), metagraph, graphOptions); - }); - }); - return seriesDict; -} - -/** - * Add a series to the provided dictionary mapping series names to series. - * - * @param seriesNodes the nodes in the series. Contains - * name, id, prefix, suffix and parent properties of the node. - * @param seriesDict the dictionary of series - * @param clusterId ID of the template of the nodes of the series - * @param metagraph - * @param graphOptions - */ -function addSeriesToDict( - seriesNodes: SeriesNode[], - seriesDict: { - [seriesName: string]: SeriesNode; - }, - clusterId: number, - metagraph: graphlib.Graph, - graphOptions: tf_graph.LabeledGraphOptions, -): void { - if (seriesNodes.length > 1) { - let curSeriesName = getSeriesNodeName( - seriesNodes[0].prefix, - seriesNodes[0].suffix, - seriesNodes[0].parent, - seriesNodes[0].clusterId, - seriesNodes[seriesNodes.length - 1].clusterId, - ); - let curSeriesNode = createSeriesNode( - seriesNodes[0].prefix, - seriesNodes[0].suffix, - seriesNodes[0].parent, - clusterId, - curSeriesName, - graphOptions, - ); - _.each(seriesNodes, (node) => { - curSeriesNode.ids.push(node.clusterId); - curSeriesNode.metagraph.setNode(node.name, metagraph.node(node.name)); - }); - seriesDict[curSeriesName] = curSeriesNode; - } -} +} \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/layout.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/layout.ts index 08f441b6a..485cacc7d 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/layout.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/layout.ts @@ -42,26 +42,6 @@ export const PARAMS = { */ edgeSep: 5, }, - /** Graph parameter for metanode. */ - series: { - /** - * Dagre's nodesep param - number of pixels that - * separate nodes horizontally in the layout. - * - */ - nodeSep: 5, - /** - * Dagre's ranksep param - number of pixels - * between each rank in the layout. - * - */ - rankSep: 25, - /** - * Dagre's edgesep param - number of pixels that separate - * edges horizontally in the layout. - */ - edgeSep: 5, - }, /** * Padding is used to correctly position the graph SVG inside of its parent * element. The padding amounts are applied using an SVG transform of X and @@ -85,13 +65,6 @@ export const PARAMS = { /** Y-space between each extracted node. */ extractYOffset: 20, }, - series: { - paddingTop: 10, - paddingBottom: 10, - paddingLeft: 10, - paddingRight: 10, - labelHeight: 10, - }, }, nodeSize: { /** Size of meta nodes. */ @@ -136,51 +109,15 @@ export const PARAMS = { labelOffset: -12, maxLabelWidth: 40, }, - /** Size of series nodes. */ - series: { - expanded: { - // For expanded series nodes, width and height will be - // computed to account for the subscene. - radius: 10, - labelOffset: 0, - }, - vertical: { - // When unexpanded, series whose underlying metagraphs contain - // one or more non-control edges will show as a vertical stack - // of ellipses. - width: 16, - height: 13, - labelOffset: -13, - }, - horizontal: { - // When unexpanded, series whose underlying metagraphs contain - // no non-control edges will show as a horizontal stack of - // ellipses. - width: 24, - height: 8, - radius: 10, - labelOffset: -10, - }, - }, - /** Size of bridge nodes. */ - bridge: { - // NOTE: bridge nodes will normally be invisible, but they must - // take up some space so that the layout step leaves room for - // their edges. - width: 20, - height: 20, - radius: 2, - labelOffset: 0, - }, }, shortcutSize: { /** Size of shortcuts for op nodes */ op: { width: 10, height: 4 }, /** Size of shortcuts for meta nodes */ meta: { width: 12, height: 4, radius: 1 }, - /** Size of shortcuts for series nodes */ - series: { width: 14, height: 4 }, + /** Size of shortcuts for multi_collection nodes */ multi_collection: { width: 12, height: 4, radius: 1 }, + /** Size of shortcuts for api_list nodes */ api_list: { width: 12, height: 4, radius: 1 }, }, annotations: { @@ -198,20 +135,6 @@ export const PARAMS = { maxLabelWidth: 40, }, constant: { size: { width: 4, height: 4 } }, - series: { - /** Maximum number of repeated item for unexpanded series node. */ - maxStackCount: 3, - /** - * Positioning offset ratio for collapsed stack - * of parallel series (series without edges between its members). - */ - parallelStackOffsetRatio: 0.2, - /** - * Positioning offset ratio for collapsed stack - * of tower series (series with edges between its members). - */ - towerStackOffsetRatio: 0.5, - }, minimap: { /** The maximum width/height the minimap can have. */ size: 150, @@ -242,8 +165,6 @@ export function layoutScene(renderNodeInfo: render.RenderGroupNodeInfo): void { // Update position of its children nodes and edges if (renderNodeInfo.node.type === NodeType.META) { layoutMetanode(renderNodeInfo, 10); - } else if (renderNodeInfo.node.type === NodeType.SERIES) { - layoutSeriesNode(renderNodeInfo); } else if (renderNodeInfo.node.type === NodeType.MULTI_COLLECTION) { layoutMetanode(renderNodeInfo, 10); } else if (renderNodeInfo.node.type === NodeType.API_LIST) { @@ -292,9 +213,6 @@ function layoutChildren(renderNodeInfo: render.RenderGroupNodeInfo): void { case NodeType.OP: _.extend(childNodeInfo, PARAMS.nodeSize.op); break; - case NodeType.BRIDGE: - _.extend(childNodeInfo, PARAMS.nodeSize.bridge); - break; case NodeType.META: case NodeType.MULTI_COLLECTION: case NodeType.API_LIST: @@ -311,19 +229,6 @@ function layoutChildren(renderNodeInfo: render.RenderGroupNodeInfo): void { layoutScene(childGroupNodeInfo); // Recursively layout its subscene. } break; - case NodeType.SERIES: - if (childNodeInfo.expanded) { - _.extend(childNodeInfo, PARAMS.nodeSize.series.expanded); - let childGroupNodeInfo = childNodeInfo; - layoutScene(childGroupNodeInfo); // Recursively layout its subscene. - } else { - let childGroupNodeInfo = childNodeInfo; - let seriesParams = childGroupNodeInfo.node.hasNonControlEdges - ? PARAMS.nodeSize.series.vertical - : PARAMS.nodeSize.series.horizontal; - _.extend(childNodeInfo, seriesParams); - } - break; default: throw Error(`Unrecognized node type: ${childNodeInfo.node.type}`); } @@ -348,17 +253,11 @@ function dagreLayout(graph: graphlib.Graph, params): { height: number; width: nu ranksep: params.rankSep, edgesep: params.edgeSep, }); - let bridgeNodeNames: any[] = []; let nonBridgeNodeNames: any[] = []; // Split out nodes into bridge and non-bridge nodes, and calculate the total // width we should use for bridge nodes. _.each(graph.nodes(), (nodeName) => { - let nodeInfo = graph.node(nodeName); - if (nodeInfo.node.type === NodeType.BRIDGE) { - bridgeNodeNames.push(nodeName); - } else { - nonBridgeNodeNames.push(nodeName); - } + nonBridgeNodeNames.push(nodeName); }); // If there are no non-bridge nodes, then the graph has zero size. if (!nonBridgeNodeNames.length) { @@ -498,23 +397,7 @@ function layoutMetanode(renderNodeInfo: render.RenderGroupNodeInfo, rankSep: num // Determine the whole metanode's height (from top to bottom). renderNodeInfo.height = renderNodeInfo.paddingTop + renderNodeInfo.coreBox.height + renderNodeInfo.paddingBottom; } -/** - * Calculate layout for series node's core graph. Only called for an expanded - * series. - */ -function layoutSeriesNode(node: render.RenderGroupNodeInfo): void { - let graph = node.coreGraph; - let params = PARAMS.subscene.series; - _.extend(node, params); - // Layout the core. - _.extend(node.coreBox, dagreLayout(node.coreGraph, PARAMS.graph.series)); - _.each(graph.nodes(), (nodeName) => { - graph.node(nodeName).excluded = false; - }); - // Series do not have in/outExtractBox so no need to include them here. - node.width = node.coreBox.width + params.paddingLeft + params.paddingRight; - node.height = node.coreBox.height + params.paddingTop + params.paddingBottom; -} + /** * Calculate layout for annotations of a given node. * This will modify positions of the given node and its annotations. @@ -641,8 +524,6 @@ function sizeAnnotation(a: render.Annotation): void { _.extend(a, PARAMS.shortcutSize.op); } else if (a.node.type === NodeType.META) { _.extend(a, PARAMS.shortcutSize.meta); - } else if (a.node.type === NodeType.SERIES) { - _.extend(a, PARAMS.shortcutSize.series); } else if (a.node.type === NodeType.MULTI_COLLECTION) { _.extend(a, PARAMS.shortcutSize.multi_collection); } else if (a.node.type === NodeType.API_LIST) { diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts index f126183b0..273eab274 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts @@ -435,30 +435,9 @@ export function buildShape(nodeGroup, d, nodeClassName: string): d3.Selectiond; - if (groupNodeInfo.coreGraph) { - stampType = groupNodeInfo.node.hasNonControlEdges ? 'vertical' : 'horizontal'; - } - let classList = [Class.Node.COLOR_TARGET]; - if (groupNodeInfo.isFadedOut) { - classList.push('faded-ellipse'); - } - tf_graph_common - .selectOrCreateChild(shapeGroup, 'use', classList) - .attr('xlink:href', `#op-series-${stampType}-stamp`); - tf_graph_common - .selectOrCreateChild(shapeGroup, 'rect', Class.Node.COLOR_TARGET) - .attr('rx', d.radius) - .attr('ry', d.radius); - break; - } case NodeType.META: case NodeType.MULTI_COLLECTION: case NodeType.API_LIST: @@ -478,12 +457,6 @@ export function nodeClass(d: render.RenderNodeInfo): string { return Class.OPNODE; case NodeType.META: return Class.METANODE; - case NodeType.SERIES: - return Class.SERIESNODE; - case NodeType.BRIDGE: - return Class.BRIDGENODE; - case NodeType.ELLIPSIS: - return Class.ELLIPSISNODE; case NodeType.MULTI_COLLECTION: return Class.MULTI_COLLECTION; case NodeType.API_LIST: @@ -694,13 +667,11 @@ export function stylize( const resolvedNodeClassName = nodeClassName || Class.Node.SHAPE || Class.Node.OUTER; const isHighlighted = sceneElement.isNodeHighlighted(renderInfo.node.name); const isSelected = sceneElement.isNodeSelected(renderInfo.node.name); - const isExtract = renderInfo.isInExtract || renderInfo.isOutExtract || renderInfo.isLibraryFunction; const isExpanded = renderInfo.expanded && resolvedNodeClassName !== Class.Annotation.NODE; const isFadedOut = renderInfo.isFadedOut; const isLinked = sceneElement.isNodeLinked(renderInfo.node.name); nodeGroup.classed('highlighted', isHighlighted); nodeGroup.classed('selected', isSelected); - nodeGroup.classed('extract', isExtract); nodeGroup.classed('expanded', isExpanded); nodeGroup.classed('faded', isFadedOut); nodeGroup.classed('linked', isLinked); diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/parser.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/parser.ts index 1d0918418..ad3047b25 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/parser.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/parser.ts @@ -50,38 +50,7 @@ export function fetchPbTxt(filepath: string): Promise { }); }); } -/** - * Fetches the metadata file, parses it and returns a promise of the result. - */ -export function fetchAndParseMetadata( - path: string, - tracker: ProgressTracker, -): Promise { - return tf_graph_util - .runTask( - 'Reading metadata pbtxt', - 40, - () => { - if (path == null) { - return Promise.resolve(null); - } - return fetchPbTxt(path); - }, - tracker, - tb_debug.GraphDebugEventId.FETCH_METADATA_PBTXT_BYTES, - ) - .then((arrayBuffer: ArrayBuffer | null) => { - return tf_graph_util.runAsyncPromiseTask( - 'Parsing metadata.pbtxt', - 60, - () => { - return arrayBuffer != null ? parseStatsPbTxt(arrayBuffer) : Promise.resolve(null); - }, - tracker, - tb_debug.GraphDebugEventId.PARSE_METADATA_PBTXT_INTO_OBJECT, - ); - }); -} + /** * Fetches the graph file, parses it and returns a promise of the result. The * result will be undefined if the graph is empty. @@ -215,27 +184,12 @@ const GRAPH_REPEATED_FIELDS: { 'node.attr.value.tensor.string_val': true, 'node.attr.value.tensor.tensor_shape.dim': true, }; -const METADATA_REPEATED_FIELDS: { - [attrPath: string]: boolean; -} = { - 'step_stats.dev_stats': true, - 'step_stats.dev_stats.node_stats': true, - 'step_stats.dev_stats.node_stats.output': true, - 'step_stats.dev_stats.node_stats.memory': true, - 'step_stats.dev_stats.node_stats.output.tensor_description.shape.dim': true, -}; /** * Parses an ArrayBuffer of a proto txt file into a raw Graph object. */ export function parseGraphPbTxt(input: ArrayBuffer): Promise { return parsePbtxtFile(input, GRAPH_REPEATED_FIELDS); } -/** - * Parses an ArrayBuffer of a proto txt file into a StepStats object. - */ -export function parseStatsPbTxt(input: ArrayBuffer): Promise { - return parsePbtxtFile(input, METADATA_REPEATED_FIELDS).then((obj) => obj.step_stats); -} /** * Parses a ArrayBuffer of a proto txt file into javascript object. * diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/proto.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/proto.ts index 3e34fe429..b8209271c 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/proto.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/proto.ts @@ -72,34 +72,6 @@ export interface EdgeInfo { value: Record; }[]; } -/** - * Specifies an argument. An argument is either an input or an output of a - * function. There are thus 2 types of arguments: input_args and output_args. - * Nodes outside a function call connect to arguments. The graph explorer - * creates nodes for all arguments within a function. - */ -export interface ArgDef { - name: string; - type: string; -} -/** - * Describes the signature of a function - its name, inputs, and outputs. - */ -export interface OpDef { - name: string; - input_arg: ArgDef[]; - output_arg: ArgDef[]; -} -/** - * Describes a single function within the library. - */ -export interface FunctionDef { - // The definition of the function's name, arguments, return values, - // attrs etc. - signature: OpDef; - // A list of nodes in the function. - node_def: NodeDef[]; -} /** * TensorFlow graph definition as defined in the graph.proto file. */ @@ -109,113 +81,3 @@ export interface GraphDef { // The information of the list of edges. edge?: EdgeInfo[]; } -/** - * Generic graph as defined in the graph_explorer.proto file. - */ -export interface GenericGraph { - /** List of nodes in the graph */ - node: GenericNode[]; - /** List of nodes in the graph */ - edge: GenericEdge[]; - /** List of attributes that describe/modify the operation. */ - attr: Array<{ - [key: string]: any; - }>; -} -/** - * GenericEdge corresponds to the Edge message in graph_explorer.proto. - */ -export interface GenericEdge { - /** Name of the source node. */ - source: string; - /** Name of the target node. */ - target: string; - /** Attributes of the edge. */ - edge_attr: Array<{ - [key: string]: any; - }>; -} -/** - * GenericNode corresponds to the Node message in graph_explorer.proto. - */ -export interface GenericNode { - /** Name of the node */ - name: string; - /** Attributes of a leaf node or leaf nodes within a metanode. */ - node_attr: Array<{ - [key: string]: any; - }>; - /** Attributes of a metanode. */ - metanode_attr: Array<{ - [key: string]: any; - }>; -} -export interface DevStat { - device: string; - node_stats: NodeExecStats[]; -} -/** - * TensorFlow stats file definition as defined in the stats proto file. - */ -export interface StepStats { - dev_stats: DevStat[]; -} -/** - * TensorFlow stats for a node as defined in the step_stats proto file. - */ -export interface NodeExecStats { - node_name: string; - // The next 4 properties are currently stored as string in json - // and must be parsed. - all_start_micros: number; - op_start_rel_micros: number; - op_end_rel_micros: number; - all_end_rel_micros: number; - memory: { - allocator_name: string; - total_bytes: number; // Stored as string in json and should be parsed. - peak_bytes: number; // Stored as string in json and should be parsed. - }[]; - /** Output sizes recorded for a single execution of a graph node */ - output: NodeOutput[]; - timeline_label: string; - scheduled_micros: string; - thread_id: string; -} -/** - * Description for the output tensor(s) of an operation in the graph as - * defined in the step_stats.proto file. - */ -export interface NodeOutput { - slot: number; // Stored as string in json and should be parsed. - tensor_description: { - /** Data type of tensor elements */ - dtype: string; - /** Shape of the tensor */ - shape: { - /** - * Dimensions of the tensor, such as [{name: 'input', size: 30}, - * {name: 'output', size: 40}] for a 30 x 40 2D tensor. The names - * are optional. The order of entries in 'dim' matters: It indicates - * the layout of the values in the tensor in-memory representation. - */ - dim: { - /** Size of the tensor in that dimension */ - size: number; // Stored as string in json and should be parsed. - /** Optional name of the tensor dimension */ - name?: string; - }[]; - }; - /** Information about the size and allocator used for the data */ - allocation_description: { - // The next 2 properties are stored as string in json and - // should be parsed. - /** Total number of bytes requested */ - requested_bytes: number; - /** Total number of bytes allocated, if known */ - allocated_bytes?: number; - /** Name of the allocator used */ - allocator_name: string; - }; - }; -} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/render.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/render.ts index bfeecbcfe..9e4621ed2 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/render.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/render.ts @@ -32,7 +32,6 @@ import { GroupNode, InclusionType, Metaedge, - MetaedgeImpl, Metanode, Node, NodeType, @@ -71,50 +70,8 @@ export const MetanodeColors = { */ DEFAULT_FILL: '#d9d9d9', DEFAULT_STROKE: '#a6a6a6', - SATURATION: 0.6, - LIGHTNESS: 0.85, - /** - * Neutral color to use when the node is expanded (used when coloring by - * compute time, memory and device). - */ - EXPANDED_COLOR: '#f0f0f0', - /** - * Standard hue values for node color palette. - */ - HUES: [220, 100, 180, 40, 20, 340, 260, 300, 140, 60], - STRUCTURE_PALETTE(id: number, lightened?: boolean): string { - // The code below is a flexible way to computationally create a set - // of colors that go well together. - let hues = MetanodeColors.HUES; - let n = hues.length; - let hue = hues[id % n]; - let m = Math.sin((hue * Math.PI) / 360); - let sat = lightened ? 30 : 90 - (60 * m); - let light = lightened ? 95 : 80; - return d3.hsl(hue, 0.01 * sat, 0.01 * light).toString(); - }, - DEVICE_PALETTE(index: number): string { - return MetanodeColors.STRUCTURE_PALETTE(index); - }, - XLA_CLUSTER_PALETTE(index: number): string { - return MetanodeColors.STRUCTURE_PALETTE(index); - }, - UNKNOWN: '#eee', GRADIENT_OUTLINE: '#888', }; -/** - * Color parameters for op nodes. - */ -export const SeriesNodeColors = { - DEFAULT_FILL: 'white', - DEFAULT_STROKE: '#b2b2b2', -}; -/** - * Function that computes edge thickness in pixels. - */ -export interface EdgeThicknessFunction { - (edgeData: EdgeData, edgeClass: string): number; -} /** * Function that computes edge label strings. This function accepts a Metaedge, * which could actually encapsulate several base edges. For instance, several @@ -130,66 +87,6 @@ export interface EdgeLabelFunction { * Parameters that affect how the graph is rendered on the screen. */ const PARAMS = { - /** - * The minimum number of nodes for a graph to have in order for high in and - * out degree nodes to be extracted in auxiliary. The aim here is to prevent - * nodes from being extracted from small graphs. - */ - minNodeCountForExtraction: 15, - /** - * The minimum in or out degree a node must have in order to be possibly - * extracted. - */ - minDegreeForExtraction: 5, - /** - * Maximum number of control edges a node can have before they aren't - * displayed. - */ - maxControlDegree: 4, - /** - * Maximum in (for outbound bridge paths) or out (for inbound bridge paths) - * degree of a node allowed for a bridge path to be rendered to it from a - * subhierarchy of nodes. Having a max prevents having too many nodes emanate - * from a subhierarchy and crowding up. - */ - maxBridgePathDegree: 4, - /** - * Types patterns for predefined out-extract nodes, which are - * sink-like nodes that will be extracted from the main graph. - */ - outExtractTypes: ['NoOp'], - /** - * Types patterns for predefined in-extract nodes, which are - * source-like nodes that will be extracted from the main graph. - */ - inExtractTypes: [], - /** - * When removing edges from a high degree node, remove all of its edges if - * detachAllEdgesForHighDegree is true. Otherwise remove all in-edges if - * the node has high in-degree, or all out-edges if the node has high - * out-degree. - */ - detachAllEdgesForHighDegree: true, - /** - * After extracting high in/out degree nodes and predefined - * source-like/sink-like, extract isolated nodes to the side - * if this extractIsolatedNodesWithAnnotationsOnOneSide is true. - */ - extractIsolatedNodesWithAnnotationsOnOneSide: true, - /** - * Whether to add bridge nodes and edges to the core when building the - * subhierarchy of an expanded metanode. See buildSubhierarchy(). - */ - enableBridgegraph: true, - /** - * 2 colors, for the minimum and maximum value respectively, whenever we - * have a gradient scale. - */ - minMaxColors: ['#fff5f0', '#fb6a4a'], - /** - * Maximum number of annotations to be displayed on a node before an - * ellipsis is used. - */ maxAnnotations: 5, }; /** @@ -339,10 +236,6 @@ export class RenderGraphInfo { return nodeName; } - setDepth(depth: number): void { - setGroupNodeDepth(this.root, Number(depth)); - } - /** * Returns true if the renderNode is an isolated node within its parent node. */ @@ -360,15 +253,6 @@ export class RenderGraphInfo { return !!found; } - /** - * Returns a list of ops that have been rendered so far for this graph. More - * ops may later be rendered if the user expands nodes for instance. The list - * returned here can only stay the same size or grow on successive calls. - */ - getNamesOfRenderedOps(): string[] { - return this.renderedOpNames; - } - buildSubhierarchy(nodeName: string, subGraph: tf_graph.SlimGraph | undefined = undefined): void { // Terminate if the rendering hierarchy was already constructed // for this node. @@ -432,184 +316,12 @@ export class RenderGraphInfo { }); } }); - // Add render metaedge info for edges in the metagraph. - _.each(metagraph.edges(), (edgeObj) => { - if (edgeObj.v.includes(tf_graph.NAMESPACE_DELIM) || edgeObj.w.includes(tf_graph.NAMESPACE_DELIM)) { - let inbound = edgeObj.w.includes(tf_graph.NAMESPACE_DELIM); - if (inbound) { - let pathNames = edgeObj.w.split(tf_graph.NAMESPACE_DELIM); - this.toRenderEdgeObjs.push({ - v: edgeObj.v, - w: pathNames[pathNames.length - 1], - id: edgeObj.name, - edge: metagraph.edge(edgeObj), - }); - } else { - let pathNames = edgeObj.v.split(tf_graph.NAMESPACE_DELIM); - this.toRenderEdgeObjs.push({ - v: pathNames[pathNames.length - 1], - w: edgeObj.w, - id: edgeObj.name, - edge: metagraph.edge(edgeObj), - }); - } - return; - } - let metaedge = metagraph.edge(edgeObj); - let renderMetaedgeInfo = new RenderMetaedgeInfo(metaedge as any); - renderMetaedgeInfo.isFadedOut = this.index[edgeObj.v].isFadedOut || this.index[edgeObj.w].isFadedOut; - coreGraph.setEdge(edgeObj.v, edgeObj.w, renderMetaedgeInfo, edgeObj.name); - }); // Look up the parent node's render information and short circuit if none. let parentNode = renderGroupNodeInfo.node.parentNode; if (!parentNode) { return; } - // Utility function for computing the name of a bridge node. - let getBridgeNodeName = (inbound, ...rest): string => rest.concat([inbound ? 'IN' : 'OUT']).join('~~'); - if (subGraph) { - const subNodes = Object.keys(subGraph.metaNodes).concat(Object.keys(subGraph.nodes)); - renderNodeInfo.node.cardinality += subNodes.length; - const parentMetagraph = (parentNode as GroupNode).metagraph; - const parentBridgegraph = (parentNode as GroupNode).bridgegraph; - _.each(subNodes, (subName) => { - this.toRenderEdgeObjs - .filter((e) => e.v === subName || e.w === subName) - .forEach((item) => { - const edgeObj = item.edge; - const inbound = item.w === subName; - const edgeIO = inbound - ? [edgeObj.v?.split(tf_graph.NAMESPACE_DELIM)[0], nodeName] - : [nodeName, edgeObj.w?.split(tf_graph.NAMESPACE_DELIM)[0]]; - let bridgeMetaedge = parentMetagraph.edge(...edgeIO, item.id); - if (!bridgeMetaedge) { - bridgeMetaedge = parentBridgegraph.edge(...edgeIO, item.id); - if (!bridgeMetaedge) { - return; - } - } - _.each(edgeObj.baseEdgeList, (baseEdge) => { - let name = inbound ? baseEdge.v : baseEdge.w; - if (baseEdge.attr) { - baseEdge.attr._path = name; - } else { - baseEdge.attr = { _path: name }; - } - if (inbound) { - baseEdge.v = name?.split(tf_graph.NAMESPACE_DELIM).pop(); - baseEdge.w = subName; - } else { - baseEdge.v = subName; - baseEdge.w = name?.split(tf_graph.NAMESPACE_DELIM).pop(); - } - bridgeMetaedge.addBaseEdge(baseEdge, this.hierarchy, true); - }); - }); - }); - } - // Remove rendered edges to save memory. - this.toRenderEdgeObjs = this.toRenderEdgeObjs.filter((e) => !this.index[e.v] || !this.index[e.w]); - // Build out the bridgegraph. - let bridgegraph = this.hierarchy.getBridgegraph(nodeName); - // Look for popular nodes so we can make annotations instead of paths. - let otherCounts = { - // Counts of edges coming INTO other nodes by name (outgoing from self). - in: < - { - [nodeName: string]: number; - } - >{}, - // Counts of edges going OUT from other nodes by name (coming into self). - out: < - { - [nodeName: string]: number; - } - >{}, - // Counts of all control edges involving other nodes by name. - control: < - { - [nodeName: string]: number; - } - >{}, - }; - _.each(bridgegraph.edges(), (e) => { - // An edge is inbound if its destination node is in the metagraph. - let inbound = !!metagraph.node(e.w); - let otherName = inbound ? e.v : e.w; - let metaedge = bridgegraph.edge(e); - if (!metaedge.numRegularEdges) { - otherCounts.control[otherName] = (otherCounts.control[otherName] || 0) + 1; - } else if (inbound) { - otherCounts.out[otherName] = (otherCounts.out[otherName] || 0) + 1; - } else { - otherCounts.in[otherName] = (otherCounts.in[otherName] || 0) + 1; - } - }); - // For each bridge container (IN and/or OUT), add structural edges between - // terminal nodes and that container. A terminal node is one which has no - // non-bridge edges in the direction of the container. - // - // For example, consider a Metanode A which contains two child nodes A/B - // and A/C. Let's say it has one edge in the metagraph from A/B->A/C, and - // one edge in the bridgegraph from Z->A/C. - // - // At this point, we've added a container bridge node IN to house all - // incoming bridge nodes. We've also added a bridge node Z' (with parent IN) - // to A, and a bridge edge from Z'->C. - // - // +----------------------+ - // | A +---+ | - // | +------>| C | | - // | | +---+ | - // | | ^ | - // | | | | - // | | +----|----+ | - // | | | IN | | | - // | +---+ | +---+ | | - // | | B | | | Z'| | | - // | +---+ | +---+ | | - // | +---------+ | - // +----------------------+ - // - // With no other help, dagre would lay out B and Z' on the same level, - // because both of them have no incoming edges. In other words, B is a - // terminal node in the INCOMING direction. - // - // But we want to force dagre to lay out Z' (and everything in IN) lower - // than all non-bridge nodes, so that there's enough room for the bridge - // edges after they've been adjusted to meet up with paths coming in from - // outside. - // - // To force Z' (and all other bridge nodes) to be lowest in the graph, we - // identify terminal nodes like B and give them structural edges to - // a new structural bridge node S which we add to IN. - // - // +----------------------+ - // | A +---+ | - // | +--->| C | | - // | | +---+ | - // | +---+ ^ | - // | | B | | | - // | +---+ | | - // | ^ | | - // | | | | - // | +----|------|----+ | - // | |IN | | | | - // | | +---+ +---+ | | - // | | | S | | Z'| | | - // | | +---+ +---+ | | - // | +----------------+ | - // +----------------------+ - // - // This ensures that dagre will lay out the bridge containers strictly at - // the ends of the graph. The structural edges will never be seen in the - // visualization except as a debugging aid. _.each([true, false], (inbound) => { - let bridgeContainerName = getBridgeNodeName(inbound, nodeName); - let bridgeContainerInfo = coreGraph.node(bridgeContainerName); - if (!bridgeContainerInfo) { - return; - } _.each(coreGraph.nodes(), (childName) => { // Short-circuit if this child is a bridge node or it's not a terminal // node in the direction we're interested in. @@ -623,44 +335,6 @@ export class RenderGraphInfo { if (!isTerminal) { return; } - // Find or create a bridge node in the container for all structural - // metaedges. It would have been nice to skip this step and simply - // set a metaedge between the terminal node and the container node, but - // in that case, something about the graph upsets dagre.layout()'s - // longestPath algorithm (was getting errors due to an undefined). - let structuralNodeName = getBridgeNodeName(inbound, nodeName, 'STRUCTURAL_TARGET'); - let structuralRenderInfo = coreGraph.node(structuralNodeName); - if (!structuralRenderInfo) { - let bridgeNode: BridgeNode = { - // Important Node properties. - name: structuralNodeName, - type: NodeType.BRIDGE, - // Unimportant Node properties. - isGroupNode: false, - cardinality: 1, - parentNode: null, - include: InclusionType.UNSPECIFIED, - // BridgeNode properties. - inbound: inbound, - inputData: {}, - outputData: {}, - suggestions: {}, - nodeAttributes: {}, - }; - structuralRenderInfo = new RenderNodeInfo(bridgeNode); - structuralRenderInfo.structural = true; - this.index[structuralNodeName] = structuralRenderInfo as any; - coreGraph.setNode(structuralNodeName, structuralRenderInfo); - bridgeContainerInfo.node.cardinality++; - coreGraph.setParent(structuralNodeName, bridgeContainerName); - } - // Create the structural Metaedge and insert it. - let structuralMetaedgeInfo = new RenderMetaedgeInfo(null); - structuralMetaedgeInfo.structural = true; - structuralMetaedgeInfo.weight--; // Reduce weight for dagre layout. - inbound - ? coreGraph.setEdge(structuralNodeName, childName, structuralMetaedgeInfo) - : coreGraph.setEdge(childName, structuralNodeName, structuralMetaedgeInfo); }); }); } @@ -943,21 +617,6 @@ export class RenderNodeInfo { paddingLeft: number; paddingRight: number; paddingBottom: number; - /** - * Whether a node is extracted as source-like (having high out-degree or - * matching predefined in-extract pattern.) - */ - isInExtract: boolean; - /** - * Whether a node is extracted as sink-like (having high in-degree or matching - * predefined out-extract pattern.) - */ - isOutExtract: boolean; - /** - * Whether a node represents a function template within the library, in which - * case it should be rendered in a special scene group. - */ - isLibraryFunction: boolean; /** * Whether this node is faded out. Used when displaying stats. */ @@ -990,8 +649,6 @@ export class RenderNodeInfo { this.paddingLeft = 0; this.paddingRight = 0; this.paddingBottom = 0; - this.isInExtract = false; - this.isOutExtract = false; this.coreBox = { width: 0, height: 0 }; // By default, we don't fade nodes out. Default to false for safety. this.isFadedOut = false; @@ -1038,10 +695,6 @@ export class RenderNodeInfo { } } } - - isInCore(): boolean { - return !this.isInExtract && !this.isOutExtract && !this.isLibraryFunction; - } } /** * Contains rendering information about a Metaedge from the underlying @@ -1131,7 +784,6 @@ function setGraphDepth(graph: graphlib.Graph, depth: number): void { case NodeType.META: case NodeType.MULTI_COLLECTION: case NodeType.API_LIST: - case NodeType.SERIES: setGroupNodeDepth(child, depth - 1); break; default: @@ -1188,165 +840,3 @@ function setGroupNodeDepth(renderInfo: RenderGroupNodeInfo, depth: number): void setGraphDepth(renderInfo.coreGraph, depth); } } -/** - * Remove an edge from the graph and add annotations to both ends of the edge. - * - * @param The core graph. - * @param v Source name. - * @param w Sink name. - */ -function createShortcut(graph: graphlib.Graph, v: string, w: string): void { - let src = graph.node(v) as any; - let sink = graph.node(w) as any; - let edge = graph.edge(v, w) as any; - // If either of the nodes is explicitly included in the main graph and - // both nodes are in the main graph then do not create the shortcut - // and instead keep the real edge. - const isInclude = src.node.include === InclusionType.INCLUDE || sink.node.include === InclusionType.INCLUDE; - const isExclude = src.node.include === InclusionType.EXCLUDE || sink.node.include === InclusionType.EXCLUDE; - if (isInclude && !isExclude) { - return; - } - - // Add each annotation. - addOutAnnotation(src, sink.node, sink, edge, AnnotationType.SHORTCUT); - addInAnnotation(sink, src.node, src, edge, AnnotationType.SHORTCUT); - // Remove the edge from the core graph. - graph.removeEdge(v, w); -} -/** - * Remove edges from a node, and set its isOutExtract property to true, - * and remove the node and move it to isolatedOutExtract. - * - * If detachAllEdgesForHighDegree or forceDetach is true, extract all of its - * edges. Otherwise, only extract all in-edges. - */ -function makeOutExtract(renderNode: RenderGroupNodeInfo, n: string, forceDetach?: boolean): void { - let graph = renderNode.coreGraph; - let child = graph.node(n) as any; - child.isOutExtract = true; - _.each(graph.predecessors(n), (p, index) => { - createShortcut(graph, p, n); - }); - if (PARAMS.detachAllEdgesForHighDegree || forceDetach) { - _.each(graph.successors(n), (s, index) => { - createShortcut(graph, n, s); - }); - } - // Remove the node from the core graph if it no longer has neighbors. - if (graph.neighbors(n)?.length === 0) { - child.node.include = InclusionType.EXCLUDE; - renderNode.isolatedOutExtract.push(child); - graph.removeNode(n); - } -} -/** - * Remove edges from a node, set its isInExtract property to true, - * and remove the node and move it to isolatedInExtract. - * - * If detachAllEdgesForHighDegree or forceDetach is true, extract all of its - * edges. Otherwise, only remove all out-edges. - */ -export function makeInExtract(renderNode: RenderGroupNodeInfo, n: string, forceDetach?: boolean): void { - let graph = renderNode.coreGraph; - let child = graph.node(n) as any; - child.isInExtract = true; - _.each(graph.successors(n), (s, index) => { - createShortcut(graph, n, s); - }); - if (PARAMS.detachAllEdgesForHighDegree || forceDetach) { - _.each(graph.predecessors(n), (p, index) => { - createShortcut(graph, p, n); - }); - } - // Remove the node from the core graph if it no longer has neighbors. - if (graph.neighbors(n)?.length === 0) { - child.node.include = InclusionType.EXCLUDE; - renderNode.isolatedInExtract.push(child); - graph.removeNode(n); - } -} -/** - * Check whether the node's type is a member of the given list of types. - * - * @param node Node. - * @param types List of type to match. - */ -function hasTypeIn(node: Node, types: string[]): boolean { - if (node.type === NodeType.OP) { - for (let i = 0; i < types.length; i++) { - if ((node).op === types[i]) { - return true; - } - } - } else if (node.type === NodeType.META) { - let rootOpNode = (node).getRootOp(); - if (rootOpNode) { - for (let i = 0; i < types.length; i++) { - if (rootOpNode.op === types[i]) { - return true; - } - } - } - } - return false; -} -/** - * Given an integer, picks a hue that is far apart from other colors. - * The formula for picking color that avoid collision is: - * hue = (color range * golden ratio * index) % color range - */ -export function mapIndexToHue(id: number): number { - let GOLDEN_RATIO = 1.61803398875; - // Hue of 0 is reserved for the gray nodes. - let MIN_HUE = 1; - let MAX_HUE = 359; - let COLOR_RANGE = MAX_HUE - MIN_HUE; - return MIN_HUE + ((COLOR_RANGE * GOLDEN_RATIO * id) % COLOR_RANGE); -} -/** - * Remove edges and add to annotation instead. - * - * For root node, consider predefined types for source and sink. - * We do not extract predefined type from non-root so that Variables and the - * sgd node (op type = 'NoOp') do not get extract from inside own group. - * - * The order of extraction is important here as swapping the order can totally - * screw up the graph layout. - * - * @param {Render.Node} renderNode Node to manipulate. - * nodes from the main graph. If false, only exclude predefined nodes. - */ -/** - * Expands nodes in the graph until the desired node is visible. - * - * @param scene The scene polymer component. - * @param renderHierarchy The render hierarchy. - * @param tensorName The name of a tensor. - * @return A string that is the name of the node representing the given tensor. - * Note that the original tensor name might differ from this returned node - * name. Specifically, for instance, the tensor name usually ends with an - * output slot index (such as :0), while the node name lacks that suffix. - */ -export function expandUntilNodeIsShown(scene, renderHierarchy: RenderGraphInfo, tensorName: string): string { - const splitTensorName = tensorName.split('/'); - // Graph names do not take into account the output slot. Strip it. - const lastNodeNameMatch = splitTensorName[splitTensorName.length - 1].match(/(?.*)\w+/); - if (lastNodeNameMatch?.length === 2) { - splitTensorName[splitTensorName.length - 1] = lastNodeNameMatch?.[1]; - } - let nodeName = splitTensorName[0]; - let renderNode = renderHierarchy.getRenderNodeByName(nodeName); - for (let i = 1; i < splitTensorName.length; i++) { - // Op nodes are not expandable. - if (renderNode.node.type === tf_graph.NodeType.OP) { - break; - } - renderHierarchy.buildSubhierarchy(nodeName); - renderNode.expanded = true; - scene.setNodeExpanded(renderNode); - nodeName += `/${splitTensorName[i]}`; - renderNode = renderHierarchy.getRenderNodeByName(nodeName); - } - return renderNode.node.name; -} diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts index 9ed02cea7..3e13d0700 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts @@ -201,7 +201,7 @@ export function position(sceneGroup, renderNode: render.RenderGroupNodeInfo): vo // expanded metanodes, the graphs are below the labels. Do not shift them // down for series nodes as series nodes don't have labels inside of their // bounding boxes. - let yTranslate = renderNode.node.type === NodeType.SERIES ? 0 : layout.PARAMS.subscene.meta.labelHeight; + let yTranslate = layout.PARAMS.subscene.meta.labelHeight; // core translate(selectChild(sceneGroup, 'g', Class.Scene.CORE), 0, yTranslate); // in-extract diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts index 6d42c6acb..a686c9d04 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts @@ -18,7 +18,7 @@ import { html, PolymerElement } from '@polymer/polymer'; import { DarkModeMixin } from '../polymer/dark_mode_mixin'; import { LegacyElementMixin } from '../polymer/legacy_element_mixin'; import '../tf_dashboard_common/tensorboard-color'; -import { MetanodeColors, OpNodeColors, SeriesNodeColors } from './render'; +import { MetanodeColors, OpNodeColors } from './render'; export enum GraphIconType { CONST = 'CONST', @@ -230,8 +230,6 @@ class TfGraphIcon extends LegacyElementMixin(DarkModeMixin(PolymerElement)) { switch (type) { case GraphIconType.META: return MetanodeColors.DEFAULT_FILL; - case GraphIconType.SERIES: - return SeriesNodeColors.DEFAULT_FILL; default: return OpNodeColors.DEFAULT_FILL; } @@ -247,8 +245,6 @@ class TfGraphIcon extends LegacyElementMixin(DarkModeMixin(PolymerElement)) { switch (type) { case GraphIconType.META: return MetanodeColors.DEFAULT_STROKE; - case GraphIconType.SERIES: - return SeriesNodeColors.DEFAULT_STROKE; default: return OpNodeColors.DEFAULT_STROKE; } diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_loader/tf-graph-dashboard-loader.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_loader/tf-graph-dashboard-loader.ts index 58dc7350d..da3df7898 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_loader/tf-graph-dashboard-loader.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_loader/tf-graph-dashboard-loader.ts @@ -313,20 +313,6 @@ class TfGraphDashboardLoader extends LegacyElementMixin(PolymerElement) { } } - _readAndParseMetadata(path: string): void { - // Reset the progress bar to 0. - this.set('progress', { - value: 0, - msg: '', - }); - let tracker = tf_graph_util.getTracker(this); - tf_graph_parser.fetchAndParseMetadata(path, tracker).then( - (stats) => { - this.set('outStats', stats) - } - ); - } - _fetchAndConstructHierarchicalGraph(path: string | null, pbTxtFile?: Blob): Promise { // Reset the progress bar to 0. this.set('progress', { -- Gitee From 80965263ea613cfb1c80c993656758b70f5af9df Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 24 Mar 2025 17:09:34 +0800 Subject: [PATCH 064/750] fix review --- debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md index 25084af57..6aa16ba49 100644 --- a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md @@ -359,8 +359,8 @@ if __name__ == "__main__": module = ModuleOP() x = torch.randn(10, 8) - out = module(x) # module内部的child modules或API将不会被dump - loss = out.sum() # module_dump_end和stop接口之间的数据正常dump + out = module(x) + loss = out.sum() loss.backward() ``` -- Gitee From 19dbabcfce58d112677a291c4c8f09f3a8998abd Mon Sep 17 00:00:00 2001 From: gitee Date: Mon, 24 Mar 2025 17:20:39 +0800 Subject: [PATCH 065/750] fix review --- debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md index 6aa16ba49..9d87a0f60 100644 --- a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md @@ -339,8 +339,9 @@ if __name__ == "__main__": ``` ### 2.5 跨文件采集数据 +为了确保所有API都被工具封装，PrecisionDebugger的实例化通常放在训练工程的入口位置。但有的时候，需要采集另一个文件中模型的数据。 假设有两个文件，train.py和module.py。train.py为训练工程入口，module.py为模型定义文件。 -本场景目的：为了采集module.py中定义的ModuleOP模块中某些子模块或API的前反向数据。 +本示例介绍了如何采集module.py中定义的ModuleOP模块中某些子模块或API的前反向数据。 train.py文件： -- Gitee From 02694873b9bbb5ce2f6e27d2d7760102b2b7cf34 Mon Sep 17 00:00:00 2001 From: liguanchi Date: Mon, 24 Mar 2025 17:30:13 +0800 Subject: [PATCH 066/750] =?UTF-8?q?=E5=86=97=E4=BD=99?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../fe/src/tf_graph_common/node.ts | 23 +---- .../fe/src/tf_graph_common/scene.ts | 84 +------------------ 2 files changed, 4 insertions(+), 103 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts index 273eab274..76c4a1d0b 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/node.ts @@ -23,7 +23,7 @@ import { Class, FontSizeInPx, selectChild, selectOrCreateChild } from './common' import * as contextmenu from './contextmenu'; import * as edge from './edge'; import * as tf_graph from './graph'; -import { MetanodeImpl, Node, NodeType, OpNode, OpNodeImpl, SeriesNode } from './graph'; +import { MetanodeImpl, Node, NodeType, OpNode, OpNodeImpl } from './graph'; import * as layout from './layout'; import * as render from './render'; import { RenderNodeInfo } from './render'; @@ -509,27 +509,6 @@ function position(nodeGroup, d: render.RenderNodeInfo): void { } break; } - case NodeType.SERIES: { - let shape = tf_graph_scene.selectChild(shapeGroup, 'use'); - if (d.expanded) { - tf_graph_scene.positionRect(shape, d.x, d.y, d.width, d.height); - subscenePosition(nodeGroup, d); - // put label on top - labelPosition(nodeGroup, cx, d.y, (-d.height / 2) + (d.labelHeight / 2)); - } else { - tf_graph_scene.positionRect(shape, cx, d.y, d.coreBox.width, d.coreBox.height); - labelPosition(nodeGroup, cx, d.y, d.labelOffset); - } - break; - } - case NodeType.BRIDGE: { - // position shape - // NOTE: In reality, these will not be visible, but it helps to put them - // in the correct position for debugging purposes. - let shape = tf_graph_scene.selectChild(shapeGroup, 'rect'); - tf_graph_scene.positionRect(shape, d.x, d.y, d.width, d.height); - break; - } case NodeType.MULTI_COLLECTION: case NodeType.API_LIST: { // position shape diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts index 3e13d0700..152c1e1b6 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/scene.ts @@ -16,9 +16,8 @@ Copyright (c) 2025, Huawei Technologies. Adapt to the model hierarchical visualization data collected by the msprobe tool ==============================================================================*/ import * as d3 from 'd3'; -import * as PolymerDom from '../polymer/dom'; -import { Class as _Class, selectChild as _selectChild, SVG_NAMESPACE } from './common'; -import { NodeType, OpNode } from './graph'; +import { Class as _Class, selectChild as _selectChild } from './common'; +import { NodeType } from './graph'; import * as layout from './layout'; import * as render from './render'; @@ -30,66 +29,6 @@ export const Class = _Class; */ const MINIMAP_BOX_WIDTH = 320; const MINIMAP_BOX_HEIGHT = 150; -/** - * A health pill encapsulates an overview of tensor element values. The value - * field is a list of 12 numbers that shed light on the status of the tensor. - * Visualized in health pills are the 3rd through 8th (inclusive) numbers of - * health pill values. Those 6 numbers are counts of tensor elements that fall - * under -Inf, negative, 0, positive, +Inf, NaN (in that order). - * - * Please keep this interface consistent with HealthPillDatum within - * backend.ts. - */ -export interface HealthPill { - device_name: string; - node_name: string; - output_slot: number; - dtype: string; - shape: number[]; - value: number[]; - wall_time: number; - step: number; -} -interface HealthPillNumericStats { - min: number; - max: number; - mean: number; - stddev: number; -} -/** - * Encapsulates how to render a single entry in a health pill. Each entry - * corresponds to a category of tensor element values. - */ -export interface HealthPillEntry { - background_color: string; - label: string; -} -export const healthPillEntries: HealthPillEntry[] = [ - { - background_color: '#CC2F2C', - label: 'NaN', - }, - { - background_color: '#FF8D00', - label: '-∞', - }, - { - background_color: '#EAEAEA', - label: '-', - }, - { - background_color: '#A5A5A5', - label: '0', - }, - { - background_color: '#262626', - label: '+', - }, - { - background_color: '#003ED4', - label: '+∞', - }, -]; /** * Helper method for fitting the graph in the svg view. * @@ -274,24 +213,7 @@ export function positionRect(rect, cx: number, cy: number, width: number, height .attr('width', width) .attr('height', height); } -/** - * Positions a triangle and sizes it. - * @param polygon polygon to set position of. - * @param cx Center x. - * @param cy Center y. - * @param width Width of bounding box for triangle. - * @param height Height of bounding box for triangle. - */ -export function positionTriangle(polygon, cx, cy, width, height): void { - const halfHeight = height / 2; - const halfWidth = width / 2; - const points = [ - [cx, cy - halfHeight], - [cx + halfWidth, cy + halfHeight], - [cx - halfWidth, cy + halfHeight], - ]; - polygon.transition().attr('points', points.map((point) => point.join(',')).join(' ')); -} + /** * Helper for setting position of a svg expand/collapse button * @param button container group -- Gitee From afaf577bd16e4485e6f383487b5b19c47a47dcdf Mon Sep 17 00:00:00 2001 From: jiangchangting1 Date: Mon, 24 Mar 2025 09:35:25 +0000 Subject: [PATCH 067/750] update debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md. Signed-off-by: jiangchangting1 --- debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md index 9d87a0f60..21cd87c01 100644 --- a/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md +++ b/debug/accuracy_tools/msprobe/docs/05.data_dump_PyTorch.md @@ -339,9 +339,7 @@ if __name__ == "__main__": ``` ### 2.5 跨文件采集数据 -为了确保所有API都被工具封装，PrecisionDebugger的实例化通常放在训练工程的入口位置。但有的时候，需要采集另一个文件中模型的数据。 -假设有两个文件，train.py和module.py。train.py为训练工程入口，module.py为模型定义文件。 -本示例介绍了如何采集module.py中定义的ModuleOP模块中某些子模块或API的前反向数据。 +为了确保所有API都被工具封装，PrecisionDebugger的实例化通常放在训练工程的入口位置，但有的时候，模型定义会在另一个文件中。 假设有两个文件，train.py（为训练工程入口）module.py（为模型定义文件），为了采集module.py中定义的ModuleOP模块中某些子模块或API的前反向数据，需要在train.py和module.py文件中分别导入PrecisionDebugger并进行如下配置。 train.py文件： -- Gitee From 5fb1ab3db1692d30e00d1473b5fe86cf12d09342 Mon Sep 17 00:00:00 2001 From: liguanchi Date: Mon, 24 Mar 2025 18:38:56 +0800 Subject: [PATCH 068/750] =?UTF-8?q?=E6=A3=80=E8=A7=86=E6=84=8F=E8=A7=81?= =?UTF-8?q?=E4=BF=AE=E6=94=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../tb_graph_ascend/server/plugin.py | 39 +++++++++---------- 1 file changed, 18 insertions(+), 21 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py index bfa84a53e..0159fcc3c 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py @@ -174,38 +174,35 @@ class GraphsPlugin(base_plugin.TBPlugin): root_subnodes_set = [] all_node_names = [] try: - batch = request.args.get("batch") + request_micro_step_id = request.args.get("batch") except ValueError: logger.error('The param "batch" or "step" does not exist or not a valid value') - - root_node = self.json_get(json_data, 'NPU', 'root') or \ + root_name = self.json_get(json_data, 'NPU', 'root') or \ self.json_get(json_data, 'root') - - root_subnodes = self.json_get(json_data, 'NPU', 'node', root_node, 'subnodes') \ + root_subnodes = self.json_get(json_data, 'NPU', 'node', root_name, 'subnodes') \ if 'NPU' in json_data else \ - self.json_get(json_data, 'node', root_node, 'subnodes') - - for node in root_subnodes: - micro_step_id = self.json_get(json_data, 'NPU', 'node', node, 'micro_step_id') \ - if 'NPU' in json_data else \ - self.json_get(json_data, 'node', node, 'micro_step_id') - - if batch == '-1' or str(micro_step_id) == batch: - root_subnodes_set.append(node) + self.json_get(json_data, 'node', root_name, 'subnodes') + if root_subnodes: + for node in root_subnodes: + json_path = ['NPU', 'node', node, 'micro_step_id'] if 'NPU' in json_data \ + else ['node', node, 'micro_step_id'] + micro_step_id = self.json_get(json_data, *json_path) + if request_micro_step_id == '-1' or str(micro_step_id) == request_micro_step_id: + root_subnodes_set.append(node) - def traverse_npu(subnodes_set): + def getLeafNodes(subnodes_set): npu_data = self.json_get(json_data, 'NPU') for node in subnodes_set: node_data = ( self.json_get(npu_data, 'node', node) if npu_data else self.json_get(json_data, 'node', node) ) - if node_data.get('subnodes'): - traverse_npu(node_data.get('subnodes')) - else: - all_node_names.append(node) + if node_data: + if node_data.get('subnodes'): + getLeafNodes(node_data.get('subnodes')) + else: + all_node_names.append(node) - traverse_npu(root_subnodes_set) - + getLeafNodes(root_subnodes_set) return all_node_names # 拿所有precisonNodes的，与controls的精度筛选联动 -- Gitee From fb3a84f1a3213d229dd73681c16316b178476373 Mon Sep 17 00:00:00 2001 From: liguanchi Date: Mon, 24 Mar 2025 18:49:02 +0800 Subject: [PATCH 069/750] =?UTF-8?q?code=5Fcheck=E4=BF=AE=E6=94=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../tensorboard-plugins/tb_graph_ascend/server/plugin.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py index 0159fcc3c..aea5b1091 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py @@ -190,7 +190,7 @@ class GraphsPlugin(base_plugin.TBPlugin): if request_micro_step_id == '-1' or str(micro_step_id) == request_micro_step_id: root_subnodes_set.append(node) - def getLeafNodes(subnodes_set): + def get_leaf_nodes(subnodes_set): npu_data = self.json_get(json_data, 'NPU') for node in subnodes_set: node_data = ( @@ -198,11 +198,12 @@ class GraphsPlugin(base_plugin.TBPlugin): ) if node_data: if node_data.get('subnodes'): - getLeafNodes(node_data.get('subnodes')) + get_leaf_nodes(node_data.get('subnodes')) else: all_node_names.append(node) - getLeafNodes(root_subnodes_set) + get_leaf_nodes(root_subnodes_set) + return all_node_names # 拿所有precisonNodes的，与controls的精度筛选联动 -- Gitee From ba33a4a56b1c4063a574dd2289bef7243e49f7b5 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Mon, 24 Mar 2025 20:05:15 +0800 Subject: [PATCH 070/750] =?UTF-8?q?=F0=9F=90=8E=20ci:=20=E6=90=AD=E5=BB=BA?= =?UTF-8?q?=E6=B5=8B=E8=AF=95=E7=8E=AF=E5=A2=83=E6=A1=86=E6=9E=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../app/controllers/match_nodes_controller.py | 3 + .../server/app/utils/graph_utils.py | 1 + .../tb_graph_ascend/test/test_plugin.py | 488 --------- .../tb_graph_ascend/tests/conftest.py | 39 + .../tb_graph_ascend/tests/pytest.ini | 9 + .../tests/test_data/compare_statis.vis | 948 ++++++++++++++++++ .../tests/test_data/metadata.json | 44 + .../test_match_nodes_controller.py | 11 + .../tests/units/service/test_graph_service.py | 20 + .../tests/units/test_plugin.py | 0 .../tests/units/utils/test_graph_utils.py | 0 11 files changed, 1075 insertions(+), 488 deletions(-) delete mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/pytest.ini create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/compare_statis.vis create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/metadata.json create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/units/controllers/test_match_nodes_controller.py create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/units/service/test_graph_service.py create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/units/test_plugin.py create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/units/utils/test_graph_utils.py diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py index b2c8e64ad..4951f9dde 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py @@ -20,6 +20,9 @@ from ..utils.global_state import ADD_MATCH_KEYS class MatchNodesController: + def add(a, b): + return a + b + @staticmethod def process_md5_task_add(graph_data, npu_node_name, bench_node_name): npu_match_nodes_list = graph_data.get('npu_match_nodes', {}) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py index 1829f2a80..34b5d7455 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py @@ -145,6 +145,7 @@ class GraphUtils: """Load a single .vis file from a given directory based on the tag.""" file_path = os.path.join(run_dir, f"{tag}.vis") file_path = os.path.normpath(file_path) # 标准化路径 + print(os.path.exists(file_path)) if os.path.exists(file_path): # 校验文件的读权限 if not os.access(file_path, os.R_OK): diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py deleted file mode 100644 index 3d958e029..000000000 --- a/plugins/tensorboard-plugins/tb_graph_ascend/test/test_plugin.py +++ /dev/null @@ -1,488 +0,0 @@ -# Copyright (c) 2025, Huawei Technologies. -# All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# ============================================================================== - -import sys -import os -sys.path.append(os.path.pardir) -from unittest.mock import MagicMock, patch -import unittest -from server.plugin import GraphsPlugin - - -class TestGraphsPlugin(unittest.TestCase): - - @property - def plugin(self): - """提供对受保护实例属性 _plugin 的只读访问""" - return self._plugin - - @property - def instance(self): - """提供对受保护实例属性 _instance 的只读访问""" - return self._instance - - def setUp(self): - """在每个测试之前初始化环境""" - fake_context = MagicMock() - - # 创建 GraphsPlugin 实例并传递 context - self.plugin = GraphsPlugin(context=fake_context) - self.plugin._current_file_path = "" # 初始化文件路径 - self.plugin.batch_id = '-1' # 设置为 -1 来触发 _process_subnode 中的判断逻辑 - self.plugin.step_id = '-1' # 设置为 -1 来触发 _process_subnode 中的判断逻辑 - - self.plugin._current_file_data = { - "npu": { - "node": { - "npu_node_1": { - "matched_node_link": [] - } - } - }, - "bench": { - "node": { - "bench_node_1": { - "matched_node_link": [] - } - } - }, - "match": [], - 'task': 'md5' - } - - self.app = Flask(__name__) - self.app.debug = True - self.client = self.app.test_client() - - # 创建模拟的 data_provider - mock_data_provider = MagicMock() - mock_data_provider.some_method.return_value = "some_value" # 根据需要设置模拟的方法 - - # 创建一个模拟的 context，并将 mock_data_provider 赋值给它 - context = MagicMock() - context.data_provider = mock_data_provider - - # 使用 context 创建 GraphsPlugin 实例 - self._instance = GraphsPlugin(context=context) - - def test_get_all_node_name_with_valid_batch_and_step(self): - # 模拟 request.args - mock_request = MagicMock() - mock_request.args.get.return_value = '0' # 模拟 batch=0 和 step=0 - - # 构造 json_data - json_data = { - 'npu': { - 'root': 'root_node', - 'node': { - 'root_node': { - 'micro_step_id': 0, - 'subnodes': ['subnode1', 'subnode2'] - }, - 'subnode1': {'micro_step_id': 0}, - 'subnode2': {'micro_step_id': 0}, - } - }, - 'bench': { - 'node': { - 'bench1': {}, - 'bench2': {} - } - } - } - - # 调用 get_all_nodeName 方法 - npu_ids, bench_ids = self.plugin.get_all_node_names(json_data, mock_request) - - # 验证返回的 npu_ids 和 bench_ids - self.assertEqual(npu_ids, ['subnode1', 'subnode2']) - self.assertEqual(bench_ids, ['bench1', 'bench2']) - - def test_dfs_collect_nodes_with_valid_batch_and_step(self): - # 模拟 request.args - mock_request = MagicMock() - side_effect_dict = { - 'batch': '0', - 'step': '0' - } - - # 设置 mock_request.args.get 的 side_effect - mock_request.args.get.side_effect = side_effect_dict.get - - # 构造 json_data - json_data = { - 'npu': { - 'node': { - 'node1': {'micro_step_id': 0, 'step_id': 0, 'subnodes': []}, - 'node2': {'micro_step_id': 0, 'step_id': 0, 'subnodes': []}, - 'node3': {'micro_step_id': 1, 'step_id': 1, 'subnodes': []}, - 'node4': {'micro_step_id': 0, 'step_id': 1, 'subnodes': ['subnode1']} - } - } - } - - # 调用 dfs_collect_nodes 方法 - all_node_names = self.plugin.dfs_collect_nodes(json_data, mock_request) - - # 验证返回的 all_node_names - self.assertEqual(all_node_names, ['node1', 'node2']) - - def test_group_precision_set_with_even_number_of_elements(self): - # 测试正常的输入（偶数个元素） - precision_set = [1, 2, 3, 4, 5, 6] - expected_result = [[1, 2], [3, 4], [5, 6]] - - # 调用 group_precision_set 方法 - result = self.plugin.group_precision_set(precision_set) - - # 验证结果是否正确 - self.assertEqual(result, expected_result) - - def test_group_precision_set_with_odd_number_of_elements(self): - # 测试输入长度为奇数的情况 - precision_set = [1, 2, 3] - - # 验证是否抛出 ValueError 异常 - with self.assertRaises(ValueError) as context: - self.plugin.group_precision_set(precision_set) - - self.assertEqual(str(context.exception), 'The number of elements in precision_set is not even') - - def test_process_data_with_md5_mismatch(self): - # 测试 md5 不匹配的情况 - data = [] - data_set = { - 'npu_keys': ['npu_key_1'], - 'bench_keys': ['bench_key_1'], - 'input_data': {'npu_key_1': [1, 2, 3], 'md5': 'abcd'}, - 'output_data': {'bench_key_1': [1, 2, 3], 'md5': 'efgh'}, - 'precision_index': 0, - 'file_path': 'test_path', - 'data_type': 'test_type', - } - npu_node = 'test_node' - - # 调用方法 - result = self.plugin.process_data(data, data_set, npu_node) - - # 验证结果 - self.assertEqual(result, 0) - self.assertEqual(data_set['precision_index'], 0) - - def test_should_update_node_with_valid_batch_and_step(self): - # 模拟 json_data 和 subnode_id_data - subnode_id_data = {'micro_step_id': '-1', 'step_id': '-1', 'matched_node_link': ['N___subnode_1']} - subgraph = {'node': {}} - json_data = { - 'StepList': ['0', '1', '2'] # 测试 StepList 数据 - } - - prefix = 'N___' - subnode_id = 'subnode_1' - - # 调用 _process_subnode 方法 - self.plugin._process_subnode(subgraph, prefix, subnode_id, subnode_id_data, json_data) - - # 验证 subnode_id 是否更新 - self.assertIn(prefix + subnode_id, subgraph['node']) - self.assertEqual(subgraph['node'][prefix + subnode_id], subnode_id_data) - - def mock_json_get(self, *args): - """ 模拟 json_get 方法，返回不同层级的数据 """ - if len(args) == 4 and args[1] == "node": - # 返回节点的 matched_node_link 数据 - return self.plugin._current_file_data[args[0]][args[1]].get(args[2], {}).get('matched_node_link', []) - return None - - def test_should_update_node_with_invalid_batch_or_step(self): - # 测试 batch_id 和 step_id 为无效值时不会更新 - self.plugin.batch_id = '-1' - self.plugin.step_id = '-1' - - subnode_id_data = {'micro_step_id': '1', 'step_id': '1', 'matched_node_link': []} - subgraph = {'node': {}} - json_data = { - 'StepList': ['0', '1', '2'] - } - - prefix = 'B___' - subnode_id = 'subnode_1' - - # 调用 _process_subnode 方法 - self.plugin._process_subnode(subgraph, prefix, subnode_id, subnode_id_data, json_data) - - # 验证 subnode_id 是否被更新 - self.assertIn(prefix + subnode_id, subgraph['node']) - self.assertEqual(subgraph['node'][prefix + subnode_id], subnode_id_data) - - def test_update_matched_node_links(self): - subnode_id_data = { - 'matched_node_link': ['link_1', 'link_2'] - } - prefix = 'B___' - - # 调用 _update_matched_node_links 方法 - self.plugin._update_matched_node_links(subnode_id_data, prefix) - - # 验证 matched_node_link 是否被正确更新 - self.assertEqual(subnode_id_data['matched_node_link'], ['N___link_1', 'N___link_2']) - - def test_no_update_matched_node_links(self): - subnode_id_data = { - 'matched_node_link': ['link_1', 'link_2'] - } - prefix = 'N___' - - # 模拟常量 SETS - constants = MagicMock() - constants.SETS = { - 'bench': ('bench', 'B___', 'N___'), - 'npu': ('npu', 'N___', 'B___'), - 'B___': ('bench', 'N___'), - 'N___': ('npu', 'B___') - } - - # 不更新第一个 matched_node_link - subnode_id_data['matched_node_link'][0] = 'prefixlink_1' - - # 调用 _update_matched_node_links 方法 - self.plugin._update_matched_node_links(subnode_id_data, prefix) - - # 验证 linked node 是否正确更新 - self.assertEqual(subnode_id_data['matched_node_link'], ['B___prefixlink_1', 'B___link_2']) - - @patch('os.walk') # 模拟 os.walk - def test_get_run_dirs(self, mock_os_walk): - """测试 _get_run_dirs 方法""" - - # 设置模拟返回的文件夹和文件 - fake_logdir = os.path.join(os.getcwd(), "fake", "logdir") # 使用绝对路径 - mock_os_walk.return_value = [(fake_logdir, [], ["run1_tag1.vis", "run2_tag2.vis"])] - - # 设置文件大小返回值 - with patch('os.path.getsize', return_value=500): # 模拟文件小于限制 - run_tag_pairs = self.plugin._get_run_dirs() - - # 验证返回的 run_tag_pairs - # 使用 os.path.normpath 来确保路径在不同操作系统上被标准化 - expected_run_tag_pairs = [ - (os.path.normpath(os.path.join(fake_logdir)), 'run1_tag1'), - (os.path.normpath(os.path.join(fake_logdir)), 'run2_tag2') - ] - - self.assertEqual(run_tag_pairs, expected_run_tag_pairs) - - @patch('os.path.getsize') # 模拟 os.path.getsize - def test_get_run_dirs_with_large_file(self, mock_getsize): - """测试 _get_run_dirs 方法，当文件超过大小限制时""" - - # 模拟一个文件大于最大限制 - mock_getsize.return_value = 2000 * 1024 * 1024 # 文件超过 1GB - - # 使用 os.path.join 来构建路径，确保兼容 Windows 和 Linux - fake_logdir = os.path.join("fake", "logdir") - large_file = "large_file.vis" - - with patch('os.walk', return_value=[(fake_logdir, [], [large_file])]): - run_tag_pairs = self.plugin._get_run_dirs() - - # 验证文件被跳过，不会返回任何文件 - self.assertEqual(run_tag_pairs, []) # 文件被跳过，不会返回任何文件 - - def test_convert_to_protobuf_format(self): - """测试 _convert_to_protobuf_format 方法""" - # 模拟节点数据 - subgraph = { - 'node': { - 'npu_node_1': { - 'id': 'op_1', - 'node_type': 1, - 'matched_node_link': ['bench_node_1'], - 'data': { - 'precision_index': 10, - 'other_data': 'value' - }, - 'input_data': {}, - 'output_data': {}, - 'suggestions': {}, - 'subnodes': [], - 'stack_info': 'stack_1' - } - } - } - - # 调用方法 - protobuf_format = self.plugin._convert_to_protobuf_format(subgraph) - - # 验证 protobuf 格式是否正确 - self.assertIn('node {', protobuf_format) - self.assertIn('name: "npu_node_1"', protobuf_format) - self.assertIn('op: "op_1"', protobuf_format) - self.assertIn('precision_index: 10', protobuf_format) - self.assertIn('isLeaf: true', protobuf_format) - - @patch('json.load') # 模拟 json.load - def test_read_json_file_invalid(self, mock_json_load): - """测试 _read_json_file 方法，当文件无效时""" - # 设置模拟的文件路径 - mock_file_path = os.path.join("fake", "file.vis") # 使用 os.path.join 来构造路径 - - # 模拟 json.load 抛出异常 - mock_json_load.side_effect = Exception("Invalid JSON") - - # 使用模拟的路径读取文件 - result = self.plugin._read_json_file(mock_file_path) - - # 验证返回值是 None，并且日志中有错误消息 - self.assertIsNone(result) - - @patch('os.path.exists', return_value=False) - def test_load_json_file_not_found(self, mock_exists): - """测试 _load_json_file 方法，当文件不存在时""" - - # 使用 os.path.join 来确保路径的兼容性 - mock_file_path = os.path.join("fake", "file.vis") - mock_tag = "tag1" - - # 调用方法 - result = self.plugin._load_json_file(mock_file_path, mock_tag) - - # 验证返回值是否为 None - self.assertIsNone(result) - - # 验证 _current_file_path 是否为空 - self.assertEqual(self.plugin._current_file_path, "") - - def test_get_input_output_data(self): - npu_node_data = { - 'input_data': {'input_1': 'data1', 'input_2': 'data2'}, - 'output_data': {'output_1': 'data3'} - } - bench_node_data = { - 'input_data': {'input_1': 'dataA', 'input_2': 'dataB'}, - 'output_data': {'output_1': 'dataC', 'output_2': 'dataD'} - } - - # 调用方法 - ( - npu_input_data, - bench_input_data, - npu_output_data, - bench_output_data - ) = self.instance.get_input_output_data(npu_node_data, bench_node_data) - - # 验证返回结果 - self.assertEqual(npu_input_data, {'input_1': 'data1', 'input_2': 'data2'}) - self.assertEqual(bench_input_data, {'input_1': 'dataA', 'input_2': 'dataB'}) - self.assertEqual(npu_output_data, {'output_1': 'data3'}) - self.assertEqual(bench_output_data, {'output_1': 'dataC', 'output_2': 'dataD'}) - - def test_calculate_min_length(self): - # 模拟输入输出数据 - npu_input_data = {'input_1': 'data1', 'input_2': 'data2'} - bench_input_data = {'input_1': 'dataA', 'input_2': 'dataB', 'input_3': 'dataC'} - npu_output_data = {'output_1': 'data3'} - bench_output_data = {'output_1': 'dataC', 'output_2': 'dataD'} - - # 调用方法 - input_min_length, output_min_length = self.instance.calculate_min_length( - npu_input_data, - bench_input_data, - npu_output_data, - bench_output_data - ) - - # 验证返回值 - self.assertEqual(input_min_length, 2) # 最小输入数据长度 - self.assertEqual(output_min_length, 1) # 最小输出数据长度 - - def test_get_keys(self): - # 模拟 npu 和 bench 数据 - npu_data = { - 'input_data': {'input_1': 'data1', 'input_2': 'data2'}, - 'output_data': {'output_1': 'data3'} - } - bench_data = { - 'input_data': {'input_1': 'dataA', 'input_2': 'dataB'}, - 'output_data': {'output_1': 'dataC', 'output_2': 'dataD'} - } - - # 调用方法 - npu_keys, bench_keys = self.instance.get_keys(npu_data, bench_data) - - # 验证返回值 - self.assertEqual(npu_keys, ['input_data', 'output_data']) - self.assertEqual(bench_keys, ['input_data', 'output_data']) - - def test_calculate_diff_and_relative_error(self): - # 模拟 npu_data 和 bench_data - npu_data = { - 'Max': 10.0, - 'Min': 1.0, - 'Mean': 5.5, - 'Norm': 8.0 - } - bench_data = { - 'Max': 12.0, - 'Min': 2.0, - 'Mean': 5.0, - 'Norm': 7.0 - } - - # 调用方法 - results = self.instance.calculate_diff_and_relative_error(npu_data, bench_data) - - # 验证返回结果 - self.assertEqual(results['npu_Max'], 10.0) - self.assertEqual(results['bench_Max'], 12.0) - self.assertEqual(results['Max_relative_err'], "16.666667%") - - self.assertEqual(results['npu_Min'], 1.0) - self.assertEqual(results['bench_Min'], 2.0) - self.assertEqual(results['Min_relative_err'], "50.000000%") - - self.assertEqual(results['npu_Mean'], 5.5) - self.assertEqual(results['bench_Mean'], 5.0) - self.assertEqual(results['Mean_relative_err'], "10.000000%") - - self.assertEqual(results['npu_Norm'], 8.0) - self.assertEqual(results['bench_Norm'], 7.0) - self.assertEqual(results['Norm_relative_err'], "14.285714%") - - def test_calculate_diff_and_relative_error_with_zero_bench_value(self): - # 模拟 npu_data 和 bench_data，其中 bench_data 有零值 - npu_data = { - 'Max': 10.0, - 'Min': 1.0, - 'Mean': 5.5, - 'Norm': 8.0 - } - bench_data = { - 'Max': 12.0, - 'Min': 0.0, # bench Min 为 0，应该触发 "N/A" 处理 - 'Mean': 5.0, - 'Norm': 0.0 # bench Norm 为 0，应该触发 "N/A" 处理 - } - - # 调用方法 - results = self.instance.calculate_diff_and_relative_error(npu_data, bench_data) - - # 验证返回结果 - self.assertEqual(results['Min_relative_err'], "N/A") - self.assertEqual(results['Norm_relative_err'], "N/A") - -if __name__ == '__main__': - unittest.main() \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py new file mode 100644 index 000000000..b3cbc2b1e --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py @@ -0,0 +1,39 @@ +import pytest +import json +import os +from pathlib import Path + + +def load_test_cases(): + meta_path = Path(__file__).parent / "test_data/metadata.json" # 修改文件扩展名为 .json + with open(meta_path) as f: + return json.load(f)["test_cases"] # 使用 json.load 代替 yaml.safe_load + + +# 动态生成测试用例 +def pytest_generate_tests(metafunc): + if "meta_data" in metafunc.fixturenames and "operation" in metafunc.fixturenames: + test_cases = load_test_cases() + params = [] + for case in test_cases: + metaData = case["metaData"] + for op in case["operations"]: + params.append(pytest.param( + metaData, + op, + id=f"{metaData['run']}-{op['type']}" + )) + # 确保参数名称与参数值数量一致 + metafunc.parametrize("meta_data, operation", params) + + +@pytest.fixture +def graph_data(meta_data): + # 返回当前测试的操作配置 + return meta_data + + +@pytest.fixture +def operation_config(operation): + # 返回当前测试的操作配置 + return operation diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/pytest.ini b/plugins/tensorboard-plugins/tb_graph_ascend/tests/pytest.ini new file mode 100644 index 000000000..ddb991b93 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/pytest.ini @@ -0,0 +1,9 @@ +[pytest] +testpaths = tests +python_files = test_*.py +norecursedirs = .* venv build dist +addopts = -v --strict-markers +log_cli = true +log_level = DEBUG +markers = + slow: marks tests as slow (deselect with -m 'not slow') \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/compare_statis.vis b/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/compare_statis.vis new file mode 100644 index 000000000..d37e9f96a --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/compare_statis.vis @@ -0,0 +1,948 @@ +{ + "ToolTip": "{\"shape\": \"\\u6570\"}", + "NPU": { + "edge": [], + "node": { + "AddOne_0": { + "matched_node_link": [ + "B___AddOne_0" + ], + "data": { + "precision_index": 0.0 + }, + "id": "AddOne_0", + "inputs": [], + "input_data": { + "AddOne_0.input_arg.0": { + "type": "torch.Tensor", + "dtype": "", + "shape": [ + 32, + 512, + 2, + 2 + ], + "Max": "5348.2343242", + "Min": "-2344.124124234", + "Mean": "-51.23432654", + "Norm": "355555.3406", + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + }, + "AddOne_0.input_arg.1": { + "type": "torch.Tensor", + "dtype": "torch.float32", + "shape": [ + 64, + 256, + 2, + 2 + ], + "Max": "5348.2343242", + "Min": "-2344.124124234", + "Mean": "-51.23432654", + "Norm": "355555.3406", + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + }, + "AddOne_0.1": {}, + "AddOne_0.2": {} + }, + "output_data": { + "AddOne_0.output_arg.0": { + "type": "torch.Tensor", + "dtype": "torch.float32", + "shape": [ + 32, + 512, + 2, + 2 + ], + "Max": "5348.2343242", + "Min": "-2344.124124234", + "Mean": "-51.23432654", + "Norm": "355555.3406", + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, 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at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/controllers/test_match_nodes_controller.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/controllers/test_match_nodes_controller.py new file mode 100644 index 000000000..1a5393e08 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/controllers/test_match_nodes_controller.py @@ -0,0 +1,11 @@ +import pytest +from server.app.controllers.match_nodes_controller import MatchNodesController +from server.app.utils.graph_utils import GraphUtils + + +class TestMatchNodesController: + + @pytest.fixture(autouse=True) + def setup_manager(self, graph_data): + self.graph_data = GraphUtils.get_graph_data(graph_data) + diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/service/test_graph_service.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/service/test_graph_service.py new file mode 100644 index 000000000..dcdabf195 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/service/test_graph_service.py @@ -0,0 +1,20 @@ +import pytest +from server.app.controllers.match_nodes_controller import MatchNodesController +from server.app.utils.graph_utils import GraphUtils + + +class TestMatchNodesService: + + @pytest.fixture(autouse=True) + def setup_manager(self, meta_data): + print('meta_data', meta_data) + self.graph_data = GraphUtils.get_graph_data(meta_data) + + def test_operation(self, operation_config): + print("operation_config: ", operation_config) + op_type = operation_config["type"] + expected = operation_config["expected"] + print("op_type: ", op_type) + print("expected: ", expected) + assert True + print('---------------') diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/test_plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/test_plugin.py new file mode 100644 index 000000000..e69de29bb diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/utils/test_graph_utils.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/utils/test_graph_utils.py new file mode 100644 index 000000000..e69de29bb -- Gitee From caf884fae78aedcb313736113fede2ddbebe06a1 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Mon, 24 Mar 2025 20:10:50 +0800 Subject: [PATCH 071/750] =?UTF-8?q?=F0=9F=A6=84=20refactor:=20=E7=BB=93?= =?UTF-8?q?=E6=9E=84=E6=9B=B4=E6=94=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../tb_graph_ascend/server/app/utils/graph_utils.py | 1 - plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py | 2 +- .../tests/{test_data => data}/compare_statis.vis | 0 .../tb_graph_ascend/tests/{test_data => data}/metadata.json | 4 ++-- .../{units => integration}/service/test_graph_service.py | 0 5 files changed, 3 insertions(+), 4 deletions(-) rename plugins/tensorboard-plugins/tb_graph_ascend/tests/{test_data => data}/compare_statis.vis (100%) rename plugins/tensorboard-plugins/tb_graph_ascend/tests/{test_data => data}/metadata.json (94%) rename plugins/tensorboard-plugins/tb_graph_ascend/tests/{units => integration}/service/test_graph_service.py (100%) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py index 34b5d7455..1829f2a80 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/utils/graph_utils.py @@ -145,7 +145,6 @@ class GraphUtils: """Load a single .vis file from a given directory based on the tag.""" file_path = os.path.join(run_dir, f"{tag}.vis") file_path = os.path.normpath(file_path) # 标准化路径 - print(os.path.exists(file_path)) if os.path.exists(file_path): # 校验文件的读权限 if not os.access(file_path, os.R_OK): diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py index b3cbc2b1e..daf242d2d 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py @@ -5,7 +5,7 @@ from pathlib import Path def load_test_cases(): - meta_path = Path(__file__).parent / "test_data/metadata.json" # 修改文件扩展名为 .json + meta_path = Path(__file__).parent / "data/metadata.json" # 修改文件扩展名为 .json with open(meta_path) as f: return json.load(f)["test_cases"] # 使用 json.load 代替 yaml.safe_load diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/compare_statis.vis b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/compare_statis.vis similarity index 100% rename from plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/compare_statis.vis rename to plugins/tensorboard-plugins/tb_graph_ascend/tests/data/compare_statis.vis diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/metadata.json b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata.json similarity index 94% rename from plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/metadata.json rename to plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata.json index 50b3ddf6f..172ad821f 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data/metadata.json +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata.json @@ -2,7 +2,7 @@ "test_cases": [ { "metaData": { - "run": "C:/code/mstt/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data", + "run": "C:/code/mstt/plugins/tensorboard-plugins/tb_graph_ascend/tests/data", "tag": "compare_statis" }, "operations": [ @@ -22,7 +22,7 @@ }, { "metaData": { - "run": "C:/code/mstt/plugins/tensorboard-plugins/tb_graph_ascend/tests/test_data", + "run": "C:/code/mstt/plugins/tensorboard-plugins/tb_graph_ascend/tests/data", "tag": "compare_statis" }, "operations": [ diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/units/service/test_graph_service.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/integration/service/test_graph_service.py similarity index 100% rename from plugins/tensorboard-plugins/tb_graph_ascend/tests/units/service/test_graph_service.py rename to plugins/tensorboard-plugins/tb_graph_ascend/tests/integration/service/test_graph_service.py -- Gitee From 49fe16c41e077b25e7d8b32862a91c0dd2c5660a Mon Sep 17 00:00:00 2001 From: wangqingcai Date: Mon, 24 Mar 2025 15:29:11 +0800 Subject: [PATCH 072/750] bugfix: fix spelling errors in log message. --- debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py | 2 +- .../msprobe/pytorch/monitor/distributed/wrap_distributed.py | 4 ++-- .../msprobe/pytorch/monitor/unittest/test_monitor.py | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py b/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py index 6ffd1ffab..588b1f97d 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py @@ -119,7 +119,7 @@ def check_process_num(process_num): def check_data_type_list(data_type_list): if data_type_list is None: - logger.info(f"data_type_list is None, use defualt all_data_type_list: {all_data_type_list}") + logger.info(f"data_type_list is None, use default all_data_type_list: {all_data_type_list}") return if not isinstance(data_type_list, list): raise ValueError(f"data_type_list({data_type_list}) is not a list") diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/distributed/wrap_distributed.py b/debug/accuracy_tools/msprobe/pytorch/monitor/distributed/wrap_distributed.py index 20ef3757d..c209fdba9 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/distributed/wrap_distributed.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/distributed/wrap_distributed.py @@ -142,7 +142,7 @@ def get_process_group(process_group): def stack_filter(stack): if len(stack) > MAX_STRING_LENGTH: - logger.warning(f'The character strin contains more than {MAX_STRING_LENGTH}. re match is skipped.') + logger.warning(f'The character string contains more than {MAX_STRING_LENGTH}. re match is skipped.') for pattern in StackBlackList: if re.search(pattern, stack): return False @@ -197,7 +197,7 @@ def is_target_line(codeline): stack = get_callstack() whole_stack = ';'.join(stack) if len(whole_stack) > MAX_STRING_LENGTH: - logger.warning(f'The character strin contains more than {MAX_STRING_LENGTH}. re match is skipped.') + logger.warning(f'The character string contains more than {MAX_STRING_LENGTH}. re match is skipped.') for pattern in codeline: if re.search(pattern, whole_stack): return True diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/unittest/test_monitor.py b/debug/accuracy_tools/msprobe/pytorch/monitor/unittest/test_monitor.py index 4d5c1a717..acdb34ff5 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/unittest/test_monitor.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/unittest/test_monitor.py @@ -92,7 +92,7 @@ def valid_reduce(reduced, unreduced, tp_size, dp_size, sequence_parallel): if errors: logger.info(errors) else: - logger.info(f'grad mean is in consist between unreduced grad and reduced grad monitord.') + logger.info(f'grad mean is in consist between unreduced grad and reduced grad monitored.') def assert_equal(a, b): -- Gitee From bb09a4b4678fd8d4771ecf5718a75020575161af Mon Sep 17 00:00:00 2001 From: wangqingcai Date: Mon, 24 Mar 2025 15:30:20 +0800 Subject: [PATCH 073/750] bugfix: fix log level --- debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py b/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py index 700d56738..1a0c393ca 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py @@ -339,11 +339,11 @@ class TrainerMon: # 初始化writer, 创建输出目录 if self.format not in FORMAT_MAPPING: - logger.error(f"Unsupported format: {self.format}, use default format: {MonitorConst.CSV}") + logger.warning(f"Unsupported format: {self.format}, use default format: {MonitorConst.CSV}") self.format = MonitorConst.CSV if self.ur_distribution and self.format != 'tensorboard': - logger.error("can only set ur_distribution when format is 'tensorboard', cancel ur_distribution") + logger.warning("can only set ur_distribution when format is 'tensorboard', cancel ur_distribution") self.ur_distribution = False writer = FORMAT_MAPPING[self.format] -- Gitee From 59da543b8015b5deabe67aa7c5b1fd34a3897f4e Mon Sep 17 00:00:00 2001 From: liguanchi Date: Tue, 25 Mar 2025 14:27:33 +0800 Subject: [PATCH 074/750] =?UTF-8?q?=E5=86=97=E4=BD=99=E6=B8=85=E7=90=86?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../fe/src/tf_graph_board/tf-graph-board.ts | 54 ++++++++++++++- .../fe/src/tf_graph_common/tf-graph-icon.ts | 66 ------------------- .../fe/src/tf_graph_common/tf-node-icon.ts | 2 - 3 files changed, 52 insertions(+), 70 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts index 81b79b708..cdfd6667b 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_board/tf-graph-board.ts @@ -203,8 +203,22 @@ class TfGraphBoard extends LegacyElementMixin(PolymerElement) { @property({ type: Object }) hierarchyParams: tf_graph_hierarchy.HierarchyParams = tf_graph_hierarchy.DefaultHierarchyParams; - @property({ type: Boolean, notify: true }) - allStepsModeEnabled: boolean = false; + /** + * A number between 0 and 100 denoting the % of progress + * for the progress bar and the displayed message. + * @type {{value: number, msg: string}} + */ + @property({ type: Object }) + progress: object; + + @property({ type: Boolean }) + traceInputs: boolean; + + @property({ type: Boolean }) + autoExtractNodes: boolean; + + @property({ type: Object, notify: true }) + renderHierarchy: tf_graph_render.MergedRenderGraphInfo; @property({ type: Object }) menu: any; @@ -212,6 +226,42 @@ class TfGraphBoard extends LegacyElementMixin(PolymerElement) { @property({ type: Object }) colorset: any; + @property({ type: String, notify: true }) + selectedNode: string; + + @property({ type: Object, notify: true }) + selectedEdge: tf_graph_render.EdgeData; + + // A function with signature EdgeThicknessFunction that computes the + // thickness of a given edge. + @property({ type: Object }) + edgeWidthFunction: object; + + @property({ type: String }) + _highlightedNode: string; + + // An optional function that takes a node selected event (whose `detail` + // property is the selected node ... which could be null if a node is + // deselected). Called whenever a node is selected or deselected. + @property({ type: Object }) + handleNodeSelected: object; + + // An optional function that computes the label for an edge. Should + // implement the EdgeLabelFunction signature. + @property({ type: Object }) + edgeLabelFunction: object; + + // An optional callback that implements the tf.graph.edge.EdgeSelectionCallback signature. If + // provided, edges are selectable, and this callback is run when an edge is selected. + @property({ type: Object }) + handleEdgeSelected: object; + + @property({ type: Object }) + selection: object; + + @property({ type: Object }) + tooltips: object; + @property({ type: Object }) selectNodeCopy: string = ''; diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts index a686c9d04..6d173b8bd 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-graph-icon.ts @@ -64,47 +64,9 @@ class TfGraphIcon extends LegacyElementMixin(DarkModeMixin(PolymerElement)) { - - - - - - - - - - - - - - - - - - - - - - - - - - - `; @property({ type: String }) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-node-icon.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-node-icon.ts index 6da65e0b1..f1c4fb5bb 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-node-icon.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_common/tf-node-icon.ts @@ -148,8 +148,6 @@ class TfNodeIcon extends LegacyElementMixin(PolymerElement) { } case tf_graph.NodeType.META: return GraphIconType.META; - case tf_graph.NodeType.SERIES: - return GraphIconType.SERIES; default: } } -- Gitee From 9513d0e030e04e0cddc6da2f09f012d1dd4a412c Mon Sep 17 00:00:00 2001 From: wangqingcai Date: Mon, 24 Mar 2025 16:02:14 +0800 Subject: [PATCH 075/750] bugfix: add upper limit of parameter --- debug/accuracy_tools/msprobe/core/common/const.py | 2 ++ .../accuracy_tools/msprobe/pytorch/monitor/csv2tb.py | 3 +++ .../accuracy_tools/msprobe/pytorch/monitor/utils.py | 12 ++++++++++++ 3 files changed, 17 insertions(+) diff --git a/debug/accuracy_tools/msprobe/core/common/const.py b/debug/accuracy_tools/msprobe/core/common/const.py index da8e190f9..00028a186 100644 --- a/debug/accuracy_tools/msprobe/core/common/const.py +++ b/debug/accuracy_tools/msprobe/core/common/const.py @@ -706,3 +706,5 @@ class MonitorConst: CSV = "csv" API = "api" HEADER_NAME = 'name' + + MAX_NDIGITS = 20 diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py b/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py index 588b1f97d..77a93eb23 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py @@ -29,6 +29,7 @@ from msprobe.pytorch.monitor.utils import get_target_output_dir all_data_type_list = ["actv", "actv_grad", "exp_avg", "exp_avg_sq", "grad_unreduced", "grad_reduced", "param"] CSV_FILE_SUFFIX = r"_\d+-\d+\.csv" +MAX_PROCESS_NUM = 128 def parse_step_line(line, ops): @@ -115,6 +116,8 @@ def csv2tb_by_step_work(target_output_dirs, output_dirpath, data_type_list): def check_process_num(process_num): if not is_int(process_num) or process_num <= 0: raise ValueError(f"process_num({process_num}) is not a positive integer") + if process_num > MAX_PROCESS_NUM: + raise ValueError(f"The maximum supported process_num is {MAX_PROCESS_NUM}, current value: {process_num}.") def check_data_type_list(data_type_list): diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py b/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py index 94afe56ff..379eaa718 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py @@ -105,6 +105,15 @@ def validate_ops(ops): return valid_ops +def validate_ndigits(ndigits): + if not ndigits: + return + if not is_int(ndigits) or ndigits <= 0: + raise ValueError(f"ndigits({ndigits}) is not a positive integer, current is: {ndigits}.") + if ndigits > MonitorConst.MAX_NDIGITS: + raise ValueError(f"The maximum supported ndigits is {MonitorConst.MAX_NDIGITS}, current value: {ndigits}.") + + def validate_ranks(ranks): if not isinstance(ranks, list): raise TypeError("module_ranks should be a list") @@ -209,6 +218,9 @@ def validate_step_count_per_record(step_count_per_record): def validate_config(config): config['ops'] = validate_ops(config.get('ops', [])) + ndigits = config.get('ndigits') + validate_ndigits(ndigits) + eps = config.get('eps', 1e-8) if not isinstance(eps, float): raise TypeError("eps should be a float") -- Gitee From a83b7a7dda99a51f9a96d4eb9ffc79c751984008 Mon Sep 17 00:00:00 2001 From: wangqingcai Date: Mon, 24 Mar 2025 16:47:27 +0800 Subject: [PATCH 076/750] bugfix: fix tensorboard dir and file mode --- .../msprobe/core/common/file_utils.py | 18 ++++++++++++++++++ .../msprobe/pytorch/monitor/csv2tb.py | 3 ++- .../msprobe/pytorch/monitor/module_hook.py | 5 ++++- .../msprobe/pytorch/monitor/utils.py | 12 +++++++++++- 4 files changed, 35 insertions(+), 3 deletions(-) diff --git a/debug/accuracy_tools/msprobe/core/common/file_utils.py b/debug/accuracy_tools/msprobe/core/common/file_utils.py index fdc626ca6..a4ffa3aa8 100644 --- a/debug/accuracy_tools/msprobe/core/common/file_utils.py +++ b/debug/accuracy_tools/msprobe/core/common/file_utils.py @@ -26,6 +26,7 @@ import yaml import numpy as np import pandas as pd +from msprobe.core.common.utils import recursion_depth_decorator from msprobe.core.common.log import logger from msprobe.core.common.exceptions import FileCheckException from msprobe.core.common.const import FileCheckConst @@ -332,6 +333,23 @@ def change_mode(path, mode): 'Failed to change {} authority. {}'.format(path, str(ex))) from ex +@recursion_depth_decorator('msprobe.core.common.file_utils.recursive_chmod') +def recursive_chmod(path): + """ + 递归地修改目录及其子目录和文件的权限，文件修改为640，路径修改为750 + + :param path: 要修改权限的目录路径 + """ + for _, dirs, files in os.walk(path): + for file_name in files: + file_path = os.path.join(path, file_name) + change_mode(file_path, FileCheckConst.DATA_FILE_AUTHORITY) + for dir_name in dirs: + dir_path = os.path.join(path, dir_name) + change_mode(dir_path, FileCheckConst.DATA_DIR_AUTHORITY) + recursive_chmod(dir_path) + + def path_len_exceeds_limit(file_path): return len(os.path.realpath(file_path)) > FileCheckConst.DIRECTORY_LENGTH or \ len(os.path.basename(file_path)) > FileCheckConst.FILE_NAME_LENGTH diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py b/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py index 77a93eb23..9b85070a0 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/csv2tb.py @@ -22,7 +22,7 @@ from torch.utils.tensorboard import SummaryWriter from tqdm import tqdm from msprobe.core.common.const import MonitorConst -from msprobe.core.common.file_utils import read_csv, create_directory, remove_path +from msprobe.core.common.file_utils import read_csv, create_directory, remove_path, recursive_chmod from msprobe.core.common.utils import is_int from msprobe.pytorch.common.log import logger from msprobe.pytorch.monitor.utils import get_target_output_dir @@ -164,4 +164,5 @@ def csv2tensorboard_by_step( p.start() for p in processes: p.join() + recursive_chmod(output_dirpath) logger.info(f"output has been saved to: {output_dirpath}") diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py b/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py index 1a0c393ca..1b61b8540 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py @@ -40,7 +40,7 @@ from msprobe.pytorch.monitor.module_metric import get_metrics, get_summary_write from msprobe.pytorch.monitor.module_spec_verifier import validate_config_spec from msprobe.pytorch.monitor.optimizer_collect import OptimizerMonFactory from msprobe.pytorch.monitor.utils import get_param_struct, validate_config, validate_ops, \ - get_output_base_dir, get_target_output_dir + get_output_base_dir, get_target_output_dir, chmod_tensorboard_dir from msprobe.pytorch.monitor.visualizer import HeatmapVisualizer torch_version_above_or_equal_2 = torch.__version__.split('+')[0] >= '2.0' @@ -697,6 +697,9 @@ class TrainerMon: if self.anomaly_data_factory: self.anomaly_data_writer.write_detected_json(self.summary_writer.get_anomalies()) self.summary_writer.clear_anomalies() + + if self.format == MonitorConst.TENSORBOARD: + chmod_tensorboard_dir(self.tensorboard_dir) self.call_id = 0 self.param_name_call_id.clear() diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py b/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py index 379eaa718..b6f9c8748 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/utils.py @@ -25,7 +25,7 @@ import torch from msprobe.core.common.const import MonitorConst, Const from msprobe.pytorch.common.log import logger from msprobe.core.common.utils import is_int -from msprobe.core.common.file_utils import check_file_or_directory_path +from msprobe.core.common.file_utils import check_file_or_directory_path, recursive_chmod device = "cpu" @@ -296,3 +296,13 @@ def get_target_output_dir(monitor_path, time_start, time_end): if start_ok and end_ok: result[rank] = os.path.join(monitor_path, dirname) return result + + +def chmod_tensorboard_dir(path): + """ + format配置为tensorboard时，需要补充文件权限设置 + """ + try: + recursive_chmod(path) + except Exception as e: + logger.warning(f"chmod tensorboard dir wrong because {e}, not updated, please check!!!") -- Gitee From b044d3a795a3eff26aee482e4e22e82693e2632a Mon Sep 17 00:00:00 2001 From: wangqingcai Date: Mon, 24 Mar 2025 20:33:41 +0800 Subject: [PATCH 077/750] bugfix: mv recursion_depth_decorator into decorator.py --- .../msprobe/core/common/decorator.py | 50 +++++++++++++++++++ .../msprobe/core/common/file_utils.py | 2 +- .../msprobe/core/common/utils.py | 32 ------------ .../data_processor/pytorch_processor.py | 3 +- .../msprobe/core/data_dump/json_writer.py | 2 +- .../generate_op_script/op_generator.py | 2 +- .../tensor_transport_layer/attl.py | 3 +- .../dump/module_dump/module_processer.py | 2 +- .../pytorch/free_benchmark/common/utils.py | 2 +- .../compare/single_benchmark.py | 2 +- .../perturbed_layers/npu/add_noise.py | 2 +- .../perturbed_layers/npu/bit_noise.py | 2 +- .../perturbed_layers/npu/change_value.py | 2 +- .../perturbed_layers/npu/improve_precision.py | 2 +- .../msprobe/pytorch/monitor/module_hook.py | 2 +- .../pytorch/online_dispatch/dump_compare.py | 2 +- .../msprobe/pytorch/online_dispatch/utils.py | 2 +- .../msprobe/test/core_ut/common/test_utils.py | 2 +- .../visualization/compare/graph_comparator.py | 2 +- 19 files changed, 68 insertions(+), 50 deletions(-) create mode 100644 debug/accuracy_tools/msprobe/core/common/decorator.py diff --git a/debug/accuracy_tools/msprobe/core/common/decorator.py b/debug/accuracy_tools/msprobe/core/common/decorator.py new file mode 100644 index 000000000..d3710002b --- /dev/null +++ b/debug/accuracy_tools/msprobe/core/common/decorator.py @@ -0,0 +1,50 @@ +# Copyright (c) 2024-2025, Huawei Technologies Co., Ltd. +# All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from collections import defaultdict +from functools import wraps + +from msprobe.core.common.const import Const +from msprobe.core.common.exceptions import MsprobeException +from msprobe.core.common.log import logger + +# 记录工具函数递归的深度 +recursion_depth = defaultdict(int) + + +def recursion_depth_decorator(func_info, max_depth=Const.MAX_DEPTH): + """装饰一个函数，当函数递归调用超过限制时，抛出异常并打印函数信息。""" + def decorator(func): + @wraps(func) + def wrapper(*args, **kwargs): + func_id = id(func) + recursion_depth[func_id] += 1 + if recursion_depth[func_id] > max_depth: + msg = f"call {func_info} exceeds the recursion limit." + logger.error_log_with_exp( + msg, + MsprobeException( + MsprobeException.RECURSION_LIMIT_ERROR, msg + ), + ) + try: + result = func(*args, **kwargs) + finally: + recursion_depth[func_id] -= 1 + return result + + return wrapper + + return decorator diff --git a/debug/accuracy_tools/msprobe/core/common/file_utils.py b/debug/accuracy_tools/msprobe/core/common/file_utils.py index a4ffa3aa8..e4d004ee5 100644 --- a/debug/accuracy_tools/msprobe/core/common/file_utils.py +++ b/debug/accuracy_tools/msprobe/core/common/file_utils.py @@ -26,7 +26,7 @@ import yaml import numpy as np import pandas as pd -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.core.common.log import logger from msprobe.core.common.exceptions import FileCheckException from msprobe.core.common.const import FileCheckConst diff --git a/debug/accuracy_tools/msprobe/core/common/utils.py b/debug/accuracy_tools/msprobe/core/common/utils.py index e08e40f1e..8d55dd4c1 100644 --- a/debug/accuracy_tools/msprobe/core/common/utils.py +++ b/debug/accuracy_tools/msprobe/core/common/utils.py @@ -18,9 +18,7 @@ import os import re import subprocess import time -from collections import defaultdict from datetime import datetime, timezone -from functools import wraps import numpy as np @@ -481,36 +479,6 @@ def safe_get_value(container, index, container_name, key=None): raise MsprobeBaseException(MsprobeBaseException.INVALID_OBJECT_TYPE_ERROR) from e -# 记录工具函数递归的深度 -recursion_depth = defaultdict(int) - - -# 装饰一个函数，当函数递归调用超过限制时，抛出异常并打印函数信息。 -def recursion_depth_decorator(func_info, max_depth=Const.MAX_DEPTH): - def decorator(func): - @wraps(func) - def wrapper(*args, **kwargs): - func_id = id(func) - recursion_depth[func_id] += 1 - if recursion_depth[func_id] > max_depth: - msg = f"call {func_info} exceeds the recursion limit." - logger.error_log_with_exp( - msg, - MsprobeException( - MsprobeException.RECURSION_LIMIT_ERROR, msg - ), - ) - try: - result = func(*args, **kwargs) - finally: - recursion_depth[func_id] -= 1 - return result - - return wrapper - - return decorator - - def check_str_param(param): if not re.match(Const.REGEX_PREFIX_PATTERN, param): logger.error('The parameter {} contains special characters.'.format(param)) diff --git a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py index 04e090510..973bfd981 100644 --- a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py +++ b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py @@ -27,7 +27,8 @@ from msprobe.core.common.const import Const from msprobe.core.common.exceptions import MsprobeException from msprobe.core.common.file_utils import path_len_exceeds_limit from msprobe.core.common.log import logger -from msprobe.core.common.utils import convert_tuple, recursion_depth_decorator +from msprobe.core.common.utils import convert_tuple +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.core.data_dump.data_processor.base import BaseDataProcessor, ModuleBackwardInputsOutputs, \ ModuleForwardInputsOutputs, TensorStatInfo from msprobe.pytorch.common.utils import Const as PtConst, save_pt, is_hifloat8_tensor, is_float8_tensor diff --git a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py index f1221d812..e1f57f53b 100644 --- a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py +++ b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py @@ -21,7 +21,7 @@ import threading from msprobe.core.common.const import Const, FileCheckConst from msprobe.core.common.file_utils import change_mode, FileOpen, save_json, load_json from msprobe.core.common.log import logger -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator lock = threading.Lock() diff --git a/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/generate_op_script/op_generator.py b/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/generate_op_script/op_generator.py index 641eada03..e9ea4553b 100644 --- a/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/generate_op_script/op_generator.py +++ b/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/generate_op_script/op_generator.py @@ -31,7 +31,7 @@ from msprobe.core.common.utils import check_file_or_directory_path, check_op_str from msprobe.core.common.const import Const, MonitorConst, MsgConst from msprobe.core.common.log import logger from msprobe.core.common.file_utils import make_dir -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator TENSOR_DATA_LIST = ["torch.Tensor", "torch.nn.parameter.Parameter"] TORCH_BOOL_TYPE = ["torch.bool"] diff --git a/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/tensor_transport_layer/attl.py b/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/tensor_transport_layer/attl.py index f858067b6..2cfc355ec 100644 --- a/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/tensor_transport_layer/attl.py +++ b/debug/accuracy_tools/msprobe/pytorch/api_accuracy_checker/tensor_transport_layer/attl.py @@ -27,8 +27,7 @@ from msprobe.pytorch.api_accuracy_checker.tensor_transport_layer.client import T from msprobe.pytorch.api_accuracy_checker.tensor_transport_layer.server import TCPServer from msprobe.core.common.file_utils import remove_path from msprobe.pytorch.common.utils import logger, save_api_data, load_api_data, save_pkl, load_pkl -from msprobe.core.common.utils import recursion_depth_decorator - +from msprobe.core.common.decorator import recursion_depth_decorator BufferType = Union[ApiData, Dict[str, Any], str] # Union[Tensor, Tuple[Optional[Tensor]]] diff --git a/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py b/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py index ae75d3c65..d9b67c931 100644 --- a/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py +++ b/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py @@ -19,7 +19,7 @@ import torch from torch.utils.hooks import BackwardHook from msprobe.core.common.const import Const -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.core.data_dump.scope import BaseScope, ModuleRangeScope, MixRangeScope from msprobe.pytorch.common.log import logger from msprobe.pytorch.common.utils import replace_last_occurrence, is_float8_tensor diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/common/utils.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/common/utils.py index e3fd2b69f..6baa684cb 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/common/utils.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/common/utils.py @@ -16,7 +16,7 @@ import torch from msprobe.core.common.exceptions import FreeBenchmarkException -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.free_benchmark.common.enums import DeviceType diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/compare/single_benchmark.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/compare/single_benchmark.py index 49e845da4..a5f18946c 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/compare/single_benchmark.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/compare/single_benchmark.py @@ -16,7 +16,7 @@ import math import torch -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.free_benchmark import logger from msprobe.pytorch.free_benchmark.common.constant import ThresholdConfig from msprobe.pytorch.free_benchmark.common.utils import TorchC diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py index 986b833ab..754e3b06e 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/add_noise.py @@ -14,7 +14,7 @@ # limitations under the License. import torch -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.free_benchmark import logger from msprobe.pytorch.free_benchmark.common.constant import ThresholdConfig from msprobe.pytorch.free_benchmark.common.enums import PerturbationMode diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py index 7d5cda6be..aec0c3ca9 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/bit_noise.py @@ -14,7 +14,7 @@ # limitations under the License. import torch -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.free_benchmark import logger from msprobe.pytorch.free_benchmark.common.constant import ThresholdConfig from msprobe.pytorch.free_benchmark.common.enums import PerturbationMode diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/change_value.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/change_value.py index c4fbeaf82..521637a1d 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/change_value.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/change_value.py @@ -14,7 +14,7 @@ # limitations under the License. import torch -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.free_benchmark import logger from msprobe.pytorch.free_benchmark.common.enums import PerturbationMode from msprobe.pytorch.free_benchmark.common.params import DataParams diff --git a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/improve_precision.py b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/improve_precision.py index 095e77ffa..daa271976 100644 --- a/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/improve_precision.py +++ b/debug/accuracy_tools/msprobe/pytorch/free_benchmark/perturbed_layers/npu/improve_precision.py @@ -15,7 +15,7 @@ import torch from msprobe.core.common.const import Const -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.free_benchmark import logger from msprobe.pytorch.free_benchmark.common.constant import CommonField from msprobe.pytorch.free_benchmark.common.enums import PerturbationMode diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py b/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py index 1b61b8540..2861718f0 100644 --- a/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py +++ b/debug/accuracy_tools/msprobe/pytorch/monitor/module_hook.py @@ -26,7 +26,7 @@ from torch.utils.hooks import BackwardHook from msprobe.core.common.const import MonitorConst, Const from msprobe.core.common.file_utils import load_json, save_json -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.common.log import logger from msprobe.pytorch.common.utils import is_recomputation, is_float8_tensor from msprobe.pytorch.monitor.anomaly_analyse import AnomalyDataWriter diff --git a/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dump_compare.py b/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dump_compare.py index a15406475..915db3be7 100644 --- a/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dump_compare.py +++ b/debug/accuracy_tools/msprobe/pytorch/online_dispatch/dump_compare.py @@ -20,7 +20,7 @@ from datetime import datetime, timezone import torch from msprobe.core.common.const import Const -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.core.common.file_utils import FileOpen, save_npy, save_json from msprobe.pytorch.common.log import logger diff --git a/debug/accuracy_tools/msprobe/pytorch/online_dispatch/utils.py b/debug/accuracy_tools/msprobe/pytorch/online_dispatch/utils.py index 2116186cc..37105551a 100644 --- a/debug/accuracy_tools/msprobe/pytorch/online_dispatch/utils.py +++ b/debug/accuracy_tools/msprobe/pytorch/online_dispatch/utils.py @@ -27,7 +27,7 @@ else: pta_cpu_device = torch.device("cpu") from msprobe.core.common.const import CompareConst -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator from msprobe.pytorch.common.log import logger diff --git a/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py b/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py index 69abbf12b..df5d6c785 100644 --- a/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py +++ b/debug/accuracy_tools/msprobe/test/core_ut/common/test_utils.py @@ -52,11 +52,11 @@ from msprobe.core.common.utils import (CompareException, get_stack_construct_by_dump_json_path, check_seed_all, safe_get_value, - recursion_depth_decorator, MsprobeBaseException, check_str_param, is_json_file, detect_framework_by_dump_json) +from msprobe.core.common.decorator import recursion_depth_decorator class TestUtils(TestCase): diff --git a/debug/accuracy_tools/msprobe/visualization/compare/graph_comparator.py b/debug/accuracy_tools/msprobe/visualization/compare/graph_comparator.py index 3f695d234..f2ba394bc 100644 --- a/debug/accuracy_tools/msprobe/visualization/compare/graph_comparator.py +++ b/debug/accuracy_tools/msprobe/visualization/compare/graph_comparator.py @@ -19,7 +19,7 @@ from msprobe.visualization.utils import GraphConst, load_json_file, load_data_js from msprobe.visualization.graph.graph import Graph, NodeOp from msprobe.visualization.compare.mode_adapter import ModeAdapter from msprobe.core.common.const import Const -from msprobe.core.common.utils import recursion_depth_decorator +from msprobe.core.common.decorator import recursion_depth_decorator class GraphComparator: -- Gitee From 2f7112d3a6712b21fd03d098e0eb37ddc4c02756 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Tue, 25 Mar 2025 15:15:03 +0800 Subject: [PATCH 078/750] =?UTF-8?q?=F0=9F=A7=AA=20test:=20=E5=A2=9E?= =?UTF-8?q?=E5=8A=A0service=E5=B1=82=E6=B5=8B=E8=AF=95=E7=94=A8=E4=BE=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../tb_graph_ascend/.gitignore | 5 +- .../tb_graph_ascend/server/plugin.py | 2 +- .../tb_graph_ascend/tests/conftest.py | 9 +- .../tests/data/compare_statis.vis | 2 +- .../tb_graph_ascend/tests/data/metadata.json | 44 ---- .../tests/data/metadata_st.json | 237 ++++++++++++++++++ .../tests/data/metadata_ut.json | 0 .../integration/service/test_graph_service.py | 43 +++- 8 files changed, 283 insertions(+), 59 deletions(-) delete mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata.json create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata_st.json create mode 100644 plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata_ut.json diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore b/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore index 75bc12db6..15cd1b851 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore +++ b/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore @@ -5,4 +5,7 @@ dist/ build/ tb_graph_ascend.egg-info/ __pycache__/ -/server/static/index.html \ No newline at end of file +/server/static/index.html +/report.html +/assets/ +/htmlcov/ \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py index aea5b1091..02cf7e751 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py @@ -170,7 +170,7 @@ class GraphsPlugin(base_plugin.TBPlugin): # 返回格式为 [[NPU节点ID列表], [Bench节点ID列表]] return [npu_ids, bench_ids] - def dfs_collect_nodes(self, json_data, request): + def dfs_collect_nodes(self, json_data, request): root_subnodes_set = [] all_node_names = [] try: diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py index daf242d2d..a45b29625 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/conftest.py @@ -4,8 +4,8 @@ import os from pathlib import Path -def load_test_cases(): - meta_path = Path(__file__).parent / "data/metadata.json" # 修改文件扩展名为 .json +def load_st_test_cases(): + meta_path = Path(__file__).parent / "data/metadata_st.json" # 修改文件扩展名为 .json with open(meta_path) as f: return json.load(f)["test_cases"] # 使用 json.load 代替 yaml.safe_load @@ -13,10 +13,11 @@ def load_test_cases(): # 动态生成测试用例 def pytest_generate_tests(metafunc): if "meta_data" in metafunc.fixturenames and "operation" in metafunc.fixturenames: - test_cases = load_test_cases() + test_cases = load_st_test_cases() params = [] for case in test_cases: - metaData = case["metaData"] + metaData = case["meta_data"] + metaData["run"] = Path(__file__).parent / metaData["run"] for op in case["operations"]: params.append(pytest.param( metaData, diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/compare_statis.vis b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/compare_statis.vis index d37e9f96a..5820af6ac 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/compare_statis.vis +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/compare_statis.vis @@ -5,7 +5,7 @@ "node": { "AddOne_0": { "matched_node_link": [ - "B___AddOne_0" + "AddOne_0" ], "data": { "precision_index": 0.0 diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata.json b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata.json deleted file mode 100644 index 172ad821f..000000000 --- a/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata.json +++ /dev/null @@ -1,44 +0,0 @@ -{ - "test_cases": [ - { - "metaData": { - "run": "C:/code/mstt/plugins/tensorboard-plugins/tb_graph_ascend/tests/data", - "tag": "compare_statis" - }, - "operations": [ - { - "type": "add_relation", - "source": "NodeA", - "target": "NodeB", - "expected": "success" - }, - { - "type": "remove_node", - "node": "NodeC", - "expected": null, - "error": "NodeNotFound" - } - ] - }, - { - "metaData": { - "run": "C:/code/mstt/plugins/tensorboard-plugins/tb_graph_ascend/tests/data", - "tag": "compare_statis" - }, - "operations": [ - { - "type": "add_relation", - "source": "NodeA", - "target": "NodeB", - "expected": "success" - }, - { - "type": "remove_node", - "node": "NodeC", - "expected": null, - "error": "NodeNotFound" - } - ] - } - ] -} \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata_st.json b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata_st.json new file mode 100644 index 000000000..820e11cc3 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata_st.json @@ -0,0 +1,237 @@ +{ + "test_cases": [ + { + "meta_data": { + "run": "data", + "tag": "compare_statis" + }, + "operations": [ + { + "type": "get_node_info", + "node_info": { + "nodeName": "Test.maxpoolMaxPool2.maxpoolpo.tt.ee", + "nodeType": "Bench" + }, + "expected": { + "success": true, + "data": { + "matched_node_link": [], + "data": {}, + "id": "Test.maxpoolMaxPool2.maxpoolpo.tt.ee", + "inputs": [], + "input_data": { + "Test.maxpoolMaxPool2.maxpoolpo.tt.ee.input_arg.0": { + "longlonglonglonglonglongName": "hah", + "type": "torch.Tensor", + "dtype": "torch.float32", + "shape": "[32, 512, 2, 2]", + "Max": "548.2343242", + "Min": "-234.124124234", + "Mean": "-5.23432654", + "Norm": "35555.3406", + "error_key": [ + "type", + "shape" + ] + }, + "Test.maxpoolMaxPool2.maxpoolpo.tt.ee.kwrag_arg.1": { + "type": "torch.Tensor", + "dtype": "torch.float32", + "shape": [ + 64, + 256, + 2, + 2 + ], + "Max": "5348.2343242", + "Min": "-2344.124124234", + "Mean": "-51.23432654", + "Norm": "355555.3406" + } + }, + "is_forward": true, + "node_type": 0, + "outputs": [], + "output_data": { + "output.0": { + "type": "torch.Tensor", + "dtype": "torch.float32", + "shape": [ + 128, + 512, + 2, + 2 + ], + "Max": "5038.2343242", + "Min": "-1234.124124234", + "Mean": "-410.23432654", + "Norm": "3255.3406" + }, + "output.1": { + "type": "torch.Tensor", + "dtype": "torch.float32", + "shape": [ + 16, + 256, + 2, + 2 + ], + "Max": "538.2343242", + "Min": "-234.124124234", + "Mean": "-51.23432654", + "Norm": "35555.3406" + } + }, + "pair": "None", + "subnodes": [ + "AddOne_0", + "AddOne_1" + ], + "type": "AddTwo", + "upnode": "AddThree_0" + } + } + }, + { + "type": "add_match_nodes", + "npu_node_name": "AddOne_0", + "bench_node_name": "AddOne_0", + "expected": { + "success": true, + "data": { + "precision_error": 0.0, + "intput_statistical_diff": { + "AddOne_0.input_arg.0": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + }, + "AddOne_0.input_arg.1": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + } + }, + "output_statistical_diff": { + "AddOne_0.output_arg.0": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + }, + "AddOne_0.output_arg.1": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + } + } + } + } + }, + { + "type": "delete_match_nodes", + "npu_node_name": "AddOne_0", + "bench_node_name": "AddOne_0", + "expected": { + "success": true, + "data": {} + } + }, + { + "type": "add_match_nodes", + "npu_node_name": "AddOne_0", + "bench_node_name": "AddOne_0", + "expected": { + "success": true, + "data": { + "precision_error": 0.0, + "intput_statistical_diff": { + "AddOne_0.input_arg.0": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + }, + "AddOne_0.input_arg.1": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + } + }, + "output_statistical_diff": { + "AddOne_0.output_arg.0": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + }, + "AddOne_0.output_arg.1": { + "MaxAbsErr": 0.0, + "MinAbsErr": 0.0, + "MeanAbsErr": 0.0, + "NormAbsErr": 0.0, + "MaxRelativeErr": "0.0000%", + "MinRelativeErr": "0.0000%", + "MeanRelativeErr": "0.0000%", + "NormRelativeErr": "0.0000%" + } + } + } + } + }, + { + "type": "get_matched_state_list", + "expected": { + "success": true, + "data": { + "npu_match_nodes": { + "AddOne_0": "AddOne_0" + }, + "bench_match_nodes": { + "AddOne_0": "AddOne_0" + } + } + } + }, + { + "type": "save_data", + "expected": { + "success": true + } + } + ] + } + ] +} \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata_ut.json b/plugins/tensorboard-plugins/tb_graph_ascend/tests/data/metadata_ut.json new file mode 100644 index 000000000..e69de29bb diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/tests/integration/service/test_graph_service.py b/plugins/tensorboard-plugins/tb_graph_ascend/tests/integration/service/test_graph_service.py index dcdabf195..6a649e2fd 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/tests/integration/service/test_graph_service.py +++ b/plugins/tensorboard-plugins/tb_graph_ascend/tests/integration/service/test_graph_service.py @@ -1,5 +1,5 @@ import pytest -from server.app.controllers.match_nodes_controller import MatchNodesController +from server.app.service.graph_service import GraphService from server.app.utils.graph_utils import GraphUtils @@ -7,14 +7,41 @@ class TestMatchNodesService: @pytest.fixture(autouse=True) def setup_manager(self, meta_data): - print('meta_data', meta_data) self.graph_data = GraphUtils.get_graph_data(meta_data) - def test_operation(self, operation_config): - print("operation_config: ", operation_config) + def test_service(self, meta_data, operation_config): op_type = operation_config["type"] expected = operation_config["expected"] - print("op_type: ", op_type) - print("expected: ", expected) - assert True - print('---------------') + # 执行操作 + try: + if op_type == "get_node_info": + result = GraphService.get_node_info( + node_info=operation_config["node_info"], + meta_data=meta_data + ) + elif op_type == "add_match_nodes": + result = GraphService.add_match_nodes( + npu_node_name=operation_config["npu_node_name"], + bench_node_name=operation_config["bench_node_name"], + meta_data=meta_data + ) + elif op_type == "delete_match_nodes": + result = GraphService.delete_match_nodes( + npu_node_name=operation_config["npu_node_name"], + bench_node_name=operation_config["bench_node_name"], + meta_data=meta_data + ) + elif op_type == "get_matched_state_list": + result = GraphService.get_matched_state_list( + meta_data=meta_data + ) + elif op_type == "save_data": + result = GraphService.save_data( + meta_data=meta_data + ) + except Exception as e: + result = {"error": type(e).__name__} + + # 验证结果 + assert result == expected, \ + f"Operation {op_type} failed on {operation_config}" -- Gitee From fcf586ff37b4157b65d75da2e54c032611372285 Mon Sep 17 00:00:00 2001 From: sunchao <1299792067@qq.com> Date: Tue, 25 Mar 2025 15:54:09 +0800 Subject: [PATCH 079/750] =?UTF-8?q?=F0=9F=90=9E=20fix:=20=E8=A7=A3?= =?UTF-8?q?=E5=86=B3=E6=96=87=E5=AD=97=E9=87=8D=E5=8F=A0=E9=97=AE=E9=A2=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../components/tf_resize_height/index.ts | 12 ++++++------ .../fe/src/tf_graph_node_info/index.ts | 8 +++++++- 2 files changed, 13 insertions(+), 7 deletions(-) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_resize_height/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_resize_height/index.ts index 6c8dddba9..2e7f8e5e6 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_resize_height/index.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/components/tf_resize_height/index.ts @@ -35,18 +35,18 @@ class ResizableTabsheet extends PolymerElement { } .resize-handle { - height: 6px; + height: 2px; width: 100%; - background-color: #ddd; cursor: ns-resize; + bottom: 2px; z-index: 999; position: relative; - bottom: 10px; - background-color: transparent; + background-color:rgb(141, 141, 141); } .resize-handle:hover { background-color: hsl(214, 100%, 43%); + height: 4px; } @@ -63,8 +63,8 @@ class ResizableTabsheet extends PolymerElement { }) height: number = 300; - _resize: (event: MouseEvent) => void = () => {}; - _stopResize: (this: Document, ev: MouseEvent) => any = () => {}; + _resize: (event: MouseEvent) => void = () => { }; + _stopResize: (this: Document, ev: MouseEvent) => any = () => { }; @observe('height') _updateHeight(newHeight): void { diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/index.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/index.ts index d3b38e9da..cb394caf5 100644 --- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/index.ts +++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph_node_info/index.ts @@ -46,6 +46,12 @@ class TfGraphNodeInfo extends PolymerElement { width: 100%; height: 100%; } + vaadin-tabsheet::part(content){ + background-color: white; + } + .vaadin-tabs{ + background-color:white; + } .vaadin-tab{ font-size: 14px; } @@ -113,7 +119,7 @@ class TfGraphNodeInfo extends PolymerElement { } - +

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