diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/data/__init__.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..ee2432f470b406bca849a0d9362b8e396a7e21b2 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/__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. +# 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b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/st_test_cases/mock_compare_resnet_data.vis.config new file mode 100644 index 0000000000000000000000000000000000000000..f0cb92aa411c8f29dfe8f15a67aa3c5872e3f835 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/st_test_cases/mock_compare_resnet_data.vis.config @@ -0,0 +1,3 @@ +{ + "Module.fc.Linear.forward.0": "Module.fc.Linear.forward.0" +} \ No newline at end of file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/data/st_test_cases/test_add_match_nodes.json b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/st_test_cases/test_add_match_nodes.json new file mode 100644 index 0000000000000000000000000000000000000000..2662bf3a43d650630821974cf0797899aa34c496 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/st_test_cases/test_add_match_nodes.json @@ -0,0 +1,318 @@ +[ + { + "case_id": "1", + "description": "测试删除匹配节点", + "input": 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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 +import os + + +class TestCaseFactory: + """管理所有测试用例的统一工厂""" + + UT_CASE_DIR = os.path.join(os.path.dirname(__file__), 'ut_test_cases') + ST_CASE_DIR = os.path.join(os.path.dirname(__file__), 'st_test_cases') + + @classmethod + def get_process_task_add_cases(cls): + return cls.load_ut_cases('test_match_node_controller/process_task_add_case.json') + + @classmethod + def get_process_task_delete_cases(cls): + return cls.load_ut_cases('test_match_node_controller/process_task_delete_case.json') + + @classmethod + def get_process_task_add_child_layer_cases(cls): + return cls.load_ut_cases('test_match_node_controller/process_task_add_child_layer.json') + + @classmethod + def get_process_task_delete_child_layer_cases(cls): + return cls.load_ut_cases('test_match_node_controller/process_task_delete_child_layer.json') + + @classmethod + def get_process_task_add_child_layer_by_config_cases(cls): + return cls.load_ut_cases('test_match_node_controller/process_task_add_child_layer_by_config.json') + + @classmethod + def get_change_expand_state_cases(cls): + return cls.load_ut_cases('test_layout_hierarchy_controller/change_expand_state_case.json') + + @classmethod + def get_update_hierarchy_data_cases(cls): + return cls.load_ut_cases('test_layout_hierarchy_controller/update_hierarchy_data_case.json') + + @classmethod + def load_single_graph_test_data(cls): + return cls.load_ut_cases('test_layout_hierarchy_controller/mock_single_statis_graph.vis') + + @classmethod + def load_compare_graph_test_data(cls): + return cls.load_ut_cases('test_layout_hierarchy_controller/mock_compare_statis_graph.vis') + + @classmethod + def load_ut_cases(cls, file_name): + """从JSON文件加载测试用例""" + path = os.path.join(cls.UT_CASE_DIR, file_name) + with open(path, 'r', encoding='utf-8') as f: + return json.load(f) + + # ST + @classmethod + def get_load_graph_config_info_cases(cls): + return cls.load_st_cases('test_load_graph_config_info.json') + + @classmethod + def get_load_graph_all_node_list_cases(cls): + return cls.load_st_cases('test_load_graph_all_node_list.json') + + @classmethod + def get_change_node_expand_state_cases(cls): + return cls.load_st_cases('test_change_node_expand_state.json') + + @classmethod + def get_test_add_match_nodes_cases(cls): + return cls.load_st_cases('test_add_match_nodes.json') + + @classmethod + def get_test_update_hierarchy_data_cases(cls): + return cls.load_st_cases('test_update_hierarchy_data.json') + + @classmethod + def get_test_delete_match_nodes_cases(cls): + return cls.load_st_cases('test_delete_match_nodes.json') + + @classmethod + def get_test_get_node_info_cases(cls): + return cls.load_st_cases('test_get_node_info.json') + + @classmethod + def get_test_add_match_nodes_by_config_cases(cls): + return cls.load_st_cases('test_add_match_nodes_by_config.json') + + @classmethod + def get_test_update_colors_cases(cls): + return cls.load_st_cases('test_update_colors.json') + + @classmethod + def load_compare_resnet_test_data(cls): + return cls.load_st_cases('mock_compare_resnet_data.vis') + + @classmethod + def load_st_cases(cls, file_name): + """从JSON文件加载测试用例""" + path = os.path.join(cls.ST_CASE_DIR, file_name) + with open(path, 'r', encoding='utf-8') as f: + return json.load(f) diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/data/ut_test_cases/test_layout_hierarchy_controller/change_expand_state_case.json b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/ut_test_cases/test_layout_hierarchy_controller/change_expand_state_case.json new file mode 100644 index 0000000000000000000000000000000000000000..5536e45f29779af07344cec41bc7a11c314ba875 --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/ut_test_cases/test_layout_hierarchy_controller/change_expand_state_case.json @@ -0,0 +1,815 @@ +[ + { + "case_id": "0", + "description": "测试无效graph_type", + "input": { + "node_name": "invalid", + "graph_type": "invalid", + "graph": {}, + "micro_step": -1 + }, + "expected": {} + }, + { + "case_id": "1", + "description": "测试展开NPU根节点", + "input": { + "node_name": "root", + "graph_type": "NPU", + "graph": {}, + "micro_step": -1 + }, + "expected": { + "AddThree_0": { + "x": 0, + "y": 0, + "width": 386, + "height": 125, 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file diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/data/ut_test_cases/test_match_node_controller/process_task_add_child_layer.json b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/ut_test_cases/test_match_node_controller/process_task_add_child_layer.json new file mode 100644 index 0000000000000000000000000000000000000000..d03b9fd26704b4d0688a6f0cfca813c6671dc65e --- /dev/null +++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/ut_test_cases/test_match_node_controller/process_task_add_child_layer.json @@ -0,0 +1,469 @@ +[ + { + "case_id": 1, + "description": "测试参数不全", + "input": { + "graph_data": { + "NPU": { + "node": { + "npu_node": { + "node_type": "Module", + "subnodes": [ + "npu_child1" + ] + } + } + }, + "Bench": { + "node": { + "bench_node": { + "node_type": "Module", + "subnodes": [ + "bench_child1" + ] + } + } + } + }, + "npu_node_name": "", + "bench_node_name": "bench_node", + "task": "md5" + }, + "expected": { + "success": false, + "error": 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"npuMatchNodes": { + "npu_parent": "bench_parent", + "npu_child": "bench_child", + "npu_grandchild": "bench_grandchild" + }, + "benchMatchNodes": { + "bench_parent": "npu_parent", + "bench_child": "npu_child", + "bench_grandchild": "npu_grandchild" + }, + "npuUnMatchNodes": [], + "benchUnMatchNodes": [] + }, + "input": { + "graph_data": { + "NPU": { + "node": { + "npu_parent": { + "node_type": "Module", + "subnodes": [ + "npu_child" + ], + "input_data": { + "parent_input": { + "md5": "parent_in", + "shape": [ + 10 + ] + } + }, + "output_data": { + "parent_output": { + "md5": "parent_out", + "shape": [ + 10 + ] + } + }, + "matched_node_link": [ + "bench_parent" + ], + "data": { + "precision_index": 1 + } + }, + "npu_child": { + "node_type": "Module", + "subnodes": [ + "npu_grandchild" + ], + "input_data": { + "child_input": { + "md5": "child_in", + "shape": [ + 20 + ] + } + }, + "output_data": { + "child_output": { + "md5": "child_out", + "shape": [ + 20 + ] + } + }, + "matched_node_link": [ + "bench_child" + ], + "data": { + "precision_index": 1 + } + }, + "npu_grandchild": { + "node_type": "API", + "subnodes": [], + "input_data": { + "grandchild_input": { + "md5": "grand_in", + "shape": [ + 30 + ] + } + }, + "output_data": { + "grandchild_output": { + "md5": "grand_out", + "shape": [ + 30 + ] + } + }, + "matched_node_link": [ + "bench_grandchild" + ], + "data": { + "precision_index": 1 + } + } + } + }, + "Bench": { + "node": { + "bench_parent": { + "node_type": "Module", + "subnodes": [ + "bench_child" + ], + "input_data": { + "parent_input": { + "md5": "parent_in", + "shape": [ + 10 + ] + } + }, + "output_data": { + "parent_output": { + "md5": "parent_out", + "shape": [ + 10 + ] + } + }, + "matched_node_link": [ + "npu_parent" + ] + }, + "bench_child": { + "node_type": "Module", + "subnodes": [ + "bench_grandchild" + ], + "input_data": { + "child_input": { + "md5": "child_in", + "shape": [ + 20 + ] + } + }, + "output_data": { + "child_output": { + "md5": "child_out", + "shape": [ + 20 + ] + } + }, + "matched_node_link": [ + "npu_child" + ] + }, + "bench_grandchild": { + "node_type": "API", + "subnodes": [], + "input_data": { + "grandchild_input": { + "md5": "grand_in", + "shape": [ + 30 + ] + } + }, + "output_data": { + "grandchild_output": { + "md5": "grand_out", + "shape": [ + 30 + ] + } + }, + "matched_node_link": [ + "npu_grandchild" + ] + } + } + } + }, + "npu_node_name": "npu_parent", + "bench_node_name": "bench_parent", + "task": "md5" + }, + "expected": { + "success": true, + "data": { + "npuMatchNodes": {}, + "benchMatchNodes": {}, + "npuUnMatchNodes": [ + "npu_parent", + "npu_child", + "npu_grandchild" + ], + "benchUnMatchNodes": [ + "bench_parent", + "bench_child", + "bench_grandchild" + ] + } + } + } +] \ No newline at end of file diff --git a/profiler/msprof_analyze/test/st/advisor/test_advisor_cmd_single_ascend_pt_db_compare.py b/profiler/msprof_analyze/test/st/advisor/test_advisor_cmd_single_ascend_pt_db_compare.py index f01e08ee7d33e637c68dbf57b25e146741690e30..85584502c9126873cddddec6b03546be38a277c0 100644 --- a/profiler/msprof_analyze/test/st/advisor/test_advisor_cmd_single_ascend_pt_db_compare.py +++ b/profiler/msprof_analyze/test/st/advisor/test_advisor_cmd_single_ascend_pt_db_compare.py @@ -1,321 +1,321 @@ -# Copyright (c) 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. -import os -import logging -from unittest import TestCase - -import math -import pandas as pd -from bs4 import BeautifulSoup -from msprof_analyze.advisor.interface.interface import Interface - -from msprof_analyze.advisor.analyzer.analyzer_controller import AnalyzerController - -from msprof_analyze.prof_common.path_manager import PathManager -from msprof_analyze.test.st.advisor.utils import get_files, execute_cmd -from msprof_analyze.test.st.utils import ST_DATA_PATH - - -class TestAdvisorCmdSingleAscendPtDBCompare(TestCase): - BASE_PROFILING_PATH = os.path.join(ST_DATA_PATH, "cluster_data_2_db", - "n122-120-121_12321_20240911113658382_ascend_pt") - COMPARISON_PROFILING_PATH = os.path.join(ST_DATA_PATH, "cluster_data_2_db", - "n122-120-121_12322_20240911113658370_ascend_pt") - OUTPUT_PATH = os.path.join(os.path.abspath(os.path.dirname(__file__)), "TestAdvisorCmdSingleAscendPtDBCompare") - ALL_OUTPUT_PATH = os.path.join(OUTPUT_PATH, "all") - result_excel = {} - result_html = {} - COMMAND_SUCCESS = 0 - - def setup_class(self): - PathManager.make_dir_safety(self.ALL_OUTPUT_PATH) - cmd_all = ["msprof-analyze", "advisor", "all", "-d", self.BASE_PROFILING_PATH, "-bp", - self.COMPARISON_PROFILING_PATH, "-o", self.ALL_OUTPUT_PATH, "-l", "en", "--force"] - if execute_cmd(cmd_all) != self.COMMAND_SUCCESS or not os.path.exists(self.ALL_OUTPUT_PATH): - self.assertTrue(False, msg="advisor [all] [bp] task failed.") - self.result_html, self.result_excel = get_files(self.OUTPUT_PATH) - - def teardown_class(self): - PathManager.remove_path_safety(self.OUTPUT_PATH) - - def test_all_problems(self): - category = [ - "Kernel compare of Target and Benchmark", - "Byte Alignment Analysis", - "Bandwidth Contention Analysis", - "Block Dim Issues", - "AICPU Issues", - "Fusible Operator Analysis", - "Operator Dispatch Issues" - ] - - # True presents the attr is nan - description_len = [1, 1, 3, 6, 2, 1, 1] - suggestion_len = [True, 1, 1, True, 2, 2, 1] - problem_count = [True, True, True, 5921, 2, True, True] - total_time = [True, True, True, 87840734.826, 87840734.826, True, True] - time_ratio = [True, True, True, 0.0033, 0, True, True] - income = [True, True, True, True, True, True, True] - income_ratio = [True, True, True, True, True, True, True] - try: - df = pd.read_excel(self.result_excel.get("all", None), sheet_name='problems', header=0) - except FileNotFoundError: - logging.error("File %s not found.", str(self.result_excel.get("all", None))) - return - - for index, row in df.iterrows(): - self.assertEqual(category[index], row["category"]) - self.assertEqual(description_len[index], len(row["description"].split("\n"))) - self.assertEqual(suggestion_len[index], isinstance(row["suggestion"], float) or - len(row["suggestion"].split("\n"))) - self.assertEqual(problem_count[index], (math.isnan(row["problem count"]) or row["problem count"])) - self.assertEqual(total_time[index], (math.isnan(row["total_time(us)"]) or - round(row["total_time(us)"], 3))) - self.assertEqual(time_ratio[index], (math.isnan(row["time ratio"]) or round(row["time ratio"], 4))) - self.assertEqual(income[index], (math.isnan(row["income(us)"]) or round(row["income(us)"], 2))) - self.assertEqual(income_ratio[index], (math.isnan(row["income ratio"]) or - round(row["income ratio"], 2))) - - def test_byte_alignment_analysis(self): - op_name = [ - "hcom_broadcast__568_2_1", - "hcom_reduceScatter__257_1_1", - "hcom_allGather__257_2_1" - ] - - total_size = [ - 24274052, - 670986240, - 335493120 - ] - - duration = [ - 997.164, - 35740.428, - 17278.562 - ] - - abnormal_duration = [ - 997.164, - 35740.428, - 17278.562 - ] - - bandwidth = [ - 24.3431, - 18.7739, - 19.4167 - ] - - test_pattern = ["all"] - for pattern in test_pattern: - try: - df = pd.read_excel(self.result_excel.get(pattern, None), sheet_name='Byte Alignment Analysis', header=0) - except FileNotFoundError: - logging.error("File %s not found.", self.result_excel.get(pattern, None)) - return - - for index, row in df.iterrows(): - self.assertEqual(op_name[index], row["op name"]) - self.assertEqual(total_size[index], row["total size(Byte)"]) - self.assertEqual(duration[index], row["duration(us)"]) - self.assertEqual(abnormal_duration[index], row["abnormal duration(us)"]) - self.assertEqual(bandwidth[index], row["bandwidth(GB/s)"]) - - soup = BeautifulSoup(open(self.result_html.get(pattern, None)), 'html.parser') - for h2 in soup.find_all('h2'): - if h2.contents[0] == "Byte Alignment Analysis": - div_content = h2.next.next.next - table = div_content.find_all('table') - for row_index, row in enumerate(table[1].find_all('tr')): - if row_index == 0: - continue - self.assertEqual(str(op_name[row_index - 1]), row.find_all('td')[0].text) - self.assertEqual(str(total_size[row_index - 1]), row.find_all('td')[1].text) - self.assertEqual(str(round(duration[row_index - 1], 3)), row.find_all('td')[2].text) - self.assertEqual(str(round(abnormal_duration[row_index - 1], 3)), row.find_all('td')[3].text) - self.assertEqual(str(round(bandwidth[row_index - 1], 4)), row.find_all('td')[4].text) - - def test_all_bandwidth_contention_analysis(self): - bandwidth_contention_analysis = [ - "hcom_allGather__114_1_1", "hcom_allGather__114_4_1", "hcom_allGather__114_109_1", - "hcom_allGather__114_113_1", "hcom_allGather__114_117_1", "hcom_allGather__114_121_1", - "hcom_allGather__114_125_1", "hcom_allGather__114_129_1", "hcom_allGather__114_133_1", - "hcom_allGather__114_173_1", "hcom_allGather__114_177_1", "hcom_allGather__114_181_1", - "hcom_allGather__114_185_1", "hcom_allGather__114_189_1", "hcom_allGather__114_193_1", - "hcom_allGather__114_197_1", "hcom_allGather__114_209_1", "hcom_reduceScatter__568_261_1", - "hcom_reduceScatter__114_275_1", "hcom_reduceScatter__114_283_1", "hcom_reduceScatter__114_315_1", - "hcom_allGather__114_316_1", "hcom_reduceScatter__114_331_1", "hcom_reduceScatter__114_347_1", - "hcom_allGather__114_348_1", "hcom_reduceScatter__114_355_1", "hcom_reduceScatter__114_363_1", - "hcom_reduceScatter__114_371_1", "hcom_reduceScatter__114_379_1", "hcom_reduceScatter__114_387_1", - "hcom_allGather__114_388_1", "hcom_reduceScatter__114_411_1", "hcom_allGather__114_412_1", - "hcom_reduceScatter__114_419_1", "hcom_allGather__114_420_1", "hcom_reduceScatter__114_427_1", - "hcom_reduceScatter__114_435_1", "hcom_reduceScatter__114_443_1", "hcom_reduceScatter__114_451_1", - "hcom_reduceScatter__114_467_1", "hcom_allGather__114_468_1", "hcom_reduceScatter__114_475_1", - "hcom_allGather__114_476_1", "hcom_reduceScatter__114_483_1", "hcom_reduceScatter__114_491_1", - "hcom_reduceScatter__114_499_1", "hcom_reduceScatter__114_507_1", "hcom_reduceScatter__114_515_1", - "hcom_reduceScatter__114_531_1", "hcom_reduceScatter__114_539_1", "hcom_reduceScatter__114_547_1", - "hcom_reduceScatter__114_555_1", "hcom_allGather__114_556_1", "hcom_reduceScatter__114_563_1", - "hcom_reduceScatter__114_571_1", "hcom_reduceScatter__114_579_1", "hcom_reduceScatter__114_587_1", - "hcom_reduceScatter__114_595_1", "hcom_reduceScatter__114_603_1", "hcom_reduceScatter__114_611_1", - "hcom_reduceScatter__114_619_1", "hcom_reduceScatter__114_635_1", "hcom_reduceScatter__114_643_1", - "hcom_allGather__114_644_1", "hcom_reduceScatter__114_651_1", "hcom_reduceScatter__114_659_1", - "hcom_reduceScatter__114_667_1", "hcom_allGather__114_668_1", "hcom_reduceScatter__114_675_1", - "hcom_allGather__114_676_1", "hcom_reduceScatter__114_683_1", "hcom_allGather__114_684_1", - "hcom_reduceScatter__114_691_1" - ] - - duration = [ - 8.3508, 15.4094, 9.5789, 8.5513, 8.3012, 9.1346, 8.7032, 9.3836, 8.7531, 11.9869, 9.8575, 9.7712, 9.9296, - 12.6163, 9.6824, 9.1268, 11.0426, 15.7377, 48.7819, 73.1451, 134.33, 14.7282, 127.4724, 127.9985, 12.5301, - 124.9251, 123.348, 122.798, 123.1688, 132.2497, 11.5286, 120.421, 12.1733, 123.3453, 9.9289, 124.3953, - 124.8201, 126.5423, 122.8442, 130.256, 12.7242, 128.1858, 12.174, 123.4281, 123.2906, 122.3294, 123.7423, - 126.1776, 127.7836, 127.616, 123.5298, 120.636, 11.249, 123.3667, 125.7421, 123.9869, 124.2625, 121.3439, - 124.2089, 126.8418, 123.9893, 125.8097, 117.6455, 13.4391, 124.0685, 126.6376, 123.167, 12.0098, 121.3413, - 13.7026, 118.2242, 13.1474, 116.1516 - ] - bandwidth = [ - 6.38, 11.11, 5.2, 6.64, 7.02, 4.97, 7.83, 8.02, 6.44, 8.54, 4.59, 4.17, 6.48, 5.02, 6.13, 4.42, 5.17, - 12.26, 13.98, 3.5, 4.48, 2.95, 3.13, 2.87, 4.96, 2.83, 2.5, 2.58, 3.36, 2.89, 3.99, 3.26, 3.76, 2.98, - 5.14, 2.95, 2.74, 2.4, 2.37, 2.94, 3.76, 3.14, 4.12, 2.92, 2.6, 2.35, 2.38, 2.5, 2.9, 3.35, 2.5, 2.92, - 4.23, 2.76, 2.07, 2.48, 2.8, 3.3, 2.4, 2.59, 2.41, 2.94, 5.01, 3.33, 2.53, 2.66, 2.87, 4.51, 3.28, 3.7, - 6.45, 3.85, 9.02 - ] - try: - df = pd.read_excel(self.result_excel.get("all", None), sheet_name='Bandwidth Contention Analysis', header=0) - except FileNotFoundError: - logging.error("File %s not found.", str(self.result_excel.get("all", None))) - return - - for index, row in df.iterrows(): - self.assertEqual(bandwidth_contention_analysis[index], row["op name"]) - self.assertEqual(duration[index], round(row["duration(ms)"], 4)) - self.assertEqual(bandwidth[index], round(row["bandwidth(GB/s)"], 2)) - - - def test_aicpu_operator(self): - op_name = ["aclnnEqScalar_EqualAiCpu_Equal", "aclnnPowTensorScalar_SquareAiCpu_Square"] - op_type = ["Equal", "Square"] - task_duration = [94.422, 87.862] - input_shapes = ["\"41;\"", "\"41\""] - input_data_types = ["DOUBLE;DOUBLE", "INT64"] - input_formats = ["FORMAT_ND;FORMAT_ND", "FORMAT_ND"] - output_shapes = ["\"41\"", "\"41\""] - output_data_types = ["BOOL", "INT64"] - output_formats = ["FORMAT_ND", "FORMAT_ND"] - stack_info = [True, True] - - t0_description = ["Square, Equal"] - t0_suggestion = ["aclnnEqScalar_EqualAiCpu_Equal"] - t0_elapsed_time = ["182.28"] - t0_time_ratio = ["0.0"] - t1_operator_type = ["Equal"] - t1_counts = ["1"] - t1_elapsed_time = ["94.42"] - t2_operator_type = ["Square"] - t2_counts = ["1"] - t2_elapsed_time = ["87.86"] - b_names = ["Equal", "Suggestion 1:", "Square", "Suggestion 1:"] - - try: - df = pd.read_excel(self.result_excel.get("all", None), sheet_name='AICPU Issues', header=0) - except FileNotFoundError: - logging.error("File %s not found.", str(self.result_excel.get("all", None))) - return - - for index, row in df.iterrows(): - self.assertEqual(op_name[index], row["op_name"]) - self.assertEqual(op_type[index], row["op_type"]) - self.assertEqual(task_duration[index], round(row["task_duration"], 3)) - self.assertEqual(input_shapes[index], row["input_shapes"]) - self.assertEqual(input_data_types[index], row["input_data_types"]) - self.assertEqual(input_formats[index], row["input_formats"]) - self.assertEqual(output_shapes[index], row["output_shapes"]) - self.assertEqual(output_data_types[index], row["output_data_types"]) - self.assertEqual(output_formats[index], row["output_formats"]) - self.assertEqual(stack_info[index], math.isnan(row["stack_info"])) - - soup = BeautifulSoup(open(self.result_html.get("all", None)), 'html.parser') - for h2 in soup.find_all('h2'): - if h2.contents[0] == "AICPU Issues": - div_content = h2.next.next.next - table = div_content.find_all('table') - for row_index, row in enumerate(table[0].find_all('tr')): - if row_index == 0: - continue - self.assertEqual(t0_description[row_index - 1], - row.find_all('td')[0].text.split(":")[1].replace("\n", "")) - self.assertEqual(t0_suggestion[row_index - 1], row.find_all('td')[1].text.split(" ")[-1]) - self.assertEqual(t0_elapsed_time[row_index - 1], row.find_all('td')[2].text) - self.assertEqual(t0_time_ratio[row_index - 1], row.find_all('td')[3].text) - for row_index, row in enumerate(table[1].find_all('tr')): - if row_index == 0: - continue - self.assertEqual(t1_operator_type[row_index - 1], row.find_all('td')[0].text) - self.assertEqual(t1_counts[row_index - 1], row.find_all('td')[1].text) - self.assertEqual(t1_elapsed_time[row_index - 1], row.find_all('td')[2].text) - for row_index, row in enumerate(table[2].find_all('tr')): - if row_index == 0: - continue - self.assertEqual(t2_operator_type[row_index - 1], row.find_all('td')[0].text) - self.assertEqual(t2_counts[row_index - 1], row.find_all('td')[1].text) - self.assertEqual(t2_elapsed_time[row_index - 1], row.find_all('td')[2].text) - - b_contents = div_content.find_all('b') - for b_index, b_content in enumerate(b_contents): - self.assertEqual(b_names[b_index], b_content.text) - - def test_operator_dispatch(self): - issues = ["operator dispatch"] - op_name = ["aclopCompileAndExecute"] - counts = [381] - total_time = [64611.056] - - t0_description = ["381"] - t0_suggestion = ["torch_npu.npu.set_compile_mode(jit_compile=False)"] - t1_issue = ["aclopCompileAndExecute"] - t1_counts = ['381'] - t1_elapsed_time = ['64611.05599999996'] - - try: - df = pd.read_excel(self.result_excel.get("all", None), sheet_name='Operator Dispatch Issues', header=0) - except FileNotFoundError: - logging.error("File %s not found.", str(self.result_excel.get("all", None))) - return - for index, row in df.iterrows(): - self.assertEqual(issues[index], row["Issues"]) - self.assertEqual(op_name[index], row["op name"]) - self.assertEqual(counts[index], row["counts"]) - self.assertEqual(total_time[index], round(row["total time"], 3)) - - soup = BeautifulSoup(open(self.result_html.get("all", None)), 'html.parser') - for h2 in soup.find_all('h2'): - if h2.contents[0] == "Operator Dispatch Issues": - div_content = h2.next.next.next - table = div_content.find_all('table') - for row_index, row in enumerate(table[0].find_all('tr')): - if row_index == 0: - continue - self.assertEqual(t0_description[row_index - 1], row.find_all('td')[0].text.split(' ')[1]) - self.assertEqual(t0_suggestion[row_index - 1], - row.find_all('td')[1].text.split('`')[1].split(';')[0]) - for row_index, row in enumerate(table[1].find_all('tr')): - if row_index == 0: - continue - self.assertEqual(t1_issue[row_index - 1], row.find_all('td')[0].text) - self.assertEqual(t1_counts[row_index - 1], row.find_all('td')[1].text) - self.assertEqual(t1_elapsed_time[row_index - 1], row.find_all('td')[2].text) - - +# Copyright (c) 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. +import os +import logging +from unittest import TestCase + +import math +import pandas as pd +from bs4 import BeautifulSoup +from msprof_analyze.advisor.interface.interface import Interface + +from msprof_analyze.advisor.analyzer.analyzer_controller import AnalyzerController + +from msprof_analyze.prof_common.path_manager import PathManager +from msprof_analyze.test.st.advisor.utils import get_files, execute_cmd +from msprof_analyze.test.st.utils import ST_DATA_PATH + + +class TestAdvisorCmdSingleAscendPtDBCompare(TestCase): + BASE_PROFILING_PATH = os.path.join(ST_DATA_PATH, "cluster_data_2_db", + "n122-120-121_12321_20240911113658382_ascend_pt") + COMPARISON_PROFILING_PATH = os.path.join(ST_DATA_PATH, "cluster_data_2_db", + "n122-120-121_12322_20240911113658370_ascend_pt") + OUTPUT_PATH = os.path.join(os.path.abspath(os.path.dirname(__file__)), "TestAdvisorCmdSingleAscendPtDBCompare") + ALL_OUTPUT_PATH = os.path.join(OUTPUT_PATH, "all") + result_excel = {} + result_html = {} + COMMAND_SUCCESS = 0 + + def setup_class(self): + PathManager.make_dir_safety(self.ALL_OUTPUT_PATH) + cmd_all = ["msprof-analyze", "advisor", "all", "-d", self.BASE_PROFILING_PATH, "-bp", + self.COMPARISON_PROFILING_PATH, "-o", self.ALL_OUTPUT_PATH, "-l", "en", "--force"] + if execute_cmd(cmd_all) != self.COMMAND_SUCCESS or not os.path.exists(self.ALL_OUTPUT_PATH): + self.assertTrue(False, msg="advisor [all] [bp] task failed.") + self.result_html, self.result_excel = get_files(self.OUTPUT_PATH) + + def teardown_class(self): + PathManager.remove_path_safety(self.OUTPUT_PATH) + + def test_all_problems(self): + category = [ + "Kernel compare of Target and Benchmark", + "Byte Alignment Analysis", + "Bandwidth Contention Analysis", + "Block Dim Issues", + "AICPU Issues", + "Fusible Operator Analysis", + "Operator Dispatch Issues" + ] + + # True presents the attr is nan + description_len = [1, 1, 3, 6, 2, 1, 1] + suggestion_len = [True, 1, 1, True, 2, 2, 1] + problem_count = [True, True, True, 5921, 2, True, True] + total_time = [True, True, True, 87840734.826, 87840734.826, True, True] + time_ratio = [True, True, True, 0.0033, 0, True, True] + income = [True, True, True, True, True, True, True] + income_ratio = [True, True, True, True, True, True, True] + try: + df = pd.read_excel(self.result_excel.get("all", None), sheet_name='problems', header=0) + except FileNotFoundError: + logging.error("File %s not found.", str(self.result_excel.get("all", None))) + return + + for index, row in df.iterrows(): + self.assertEqual(category[index], row["category"]) + self.assertEqual(description_len[index], len(row["description"].split("\n"))) + self.assertEqual(suggestion_len[index], isinstance(row["suggestion"], float) or + len(row["suggestion"].split("\n"))) + self.assertEqual(problem_count[index], (math.isnan(row["problem count"]) or row["problem count"])) + self.assertEqual(total_time[index], (math.isnan(row["total_time(us)"]) or + round(row["total_time(us)"], 3))) + self.assertEqual(time_ratio[index], (math.isnan(row["time ratio"]) or round(row["time ratio"], 4))) + self.assertEqual(income[index], (math.isnan(row["income(us)"]) or round(row["income(us)"], 2))) + self.assertEqual(income_ratio[index], (math.isnan(row["income ratio"]) or + round(row["income ratio"], 2))) + + def test_byte_alignment_analysis(self): + op_name = [ + "hcom_broadcast__568_2_1", + "hcom_reduceScatter__257_1_1", + "hcom_allGather__257_2_1" + ] + + total_size = [ + 24274052, + 670986240, + 335493120 + ] + + duration = [ + 997.164, + 35740.428, + 17278.562 + ] + + abnormal_duration = [ + 997.164, + 35740.428, + 17278.562 + ] + + bandwidth = [ + 24.3431, + 18.7739, + 19.4167 + ] + + test_pattern = ["all"] + for pattern in test_pattern: + try: + df = pd.read_excel(self.result_excel.get(pattern, None), sheet_name='Byte Alignment Analysis', header=0) + except FileNotFoundError: + logging.error("File %s not found.", self.result_excel.get(pattern, None)) + return + + for index, row in df.iterrows(): + self.assertEqual(op_name[index], row["op name"]) + self.assertEqual(total_size[index], row["total size(Byte)"]) + self.assertEqual(duration[index], row["duration(us)"]) + self.assertEqual(abnormal_duration[index], row["abnormal duration(us)"]) + self.assertEqual(bandwidth[index], row["bandwidth(GB/s)"]) + + soup = BeautifulSoup(open(self.result_html.get(pattern, None)), 'html.parser') + for h2 in soup.find_all('h2'): + if h2.contents[0] == "Byte Alignment Analysis": + div_content = h2.next.next.next + table = div_content.find_all('table') + for row_index, row in enumerate(table[1].find_all('tr')): + if row_index == 0: + continue + self.assertEqual(str(op_name[row_index - 1]), row.find_all('td')[0].text) + self.assertEqual(str(total_size[row_index - 1]), row.find_all('td')[1].text) + self.assertEqual(str(round(duration[row_index - 1], 3)), row.find_all('td')[2].text) + self.assertEqual(str(round(abnormal_duration[row_index - 1], 3)), row.find_all('td')[3].text) + self.assertEqual(str(round(bandwidth[row_index - 1], 4)), row.find_all('td')[4].text) + + def test_all_bandwidth_contention_analysis(self): + bandwidth_contention_analysis = [ + "hcom_allGather__114_1_1", "hcom_allGather__114_4_1", "hcom_allGather__114_109_1", + "hcom_allGather__114_113_1", "hcom_allGather__114_117_1", "hcom_allGather__114_121_1", + "hcom_allGather__114_125_1", "hcom_allGather__114_129_1", "hcom_allGather__114_133_1", + "hcom_allGather__114_173_1", "hcom_allGather__114_177_1", "hcom_allGather__114_181_1", + "hcom_allGather__114_185_1", "hcom_allGather__114_189_1", "hcom_allGather__114_193_1", + "hcom_allGather__114_197_1", "hcom_allGather__114_209_1", "hcom_reduceScatter__568_261_1", + "hcom_reduceScatter__114_275_1", "hcom_reduceScatter__114_283_1", "hcom_reduceScatter__114_315_1", + "hcom_allGather__114_316_1", "hcom_reduceScatter__114_331_1", "hcom_reduceScatter__114_347_1", + "hcom_allGather__114_348_1", "hcom_reduceScatter__114_355_1", "hcom_reduceScatter__114_363_1", + "hcom_reduceScatter__114_371_1", "hcom_reduceScatter__114_379_1", "hcom_reduceScatter__114_387_1", + "hcom_allGather__114_388_1", "hcom_reduceScatter__114_411_1", "hcom_allGather__114_412_1", + "hcom_reduceScatter__114_419_1", "hcom_allGather__114_420_1", "hcom_reduceScatter__114_427_1", + "hcom_reduceScatter__114_435_1", "hcom_reduceScatter__114_443_1", "hcom_reduceScatter__114_451_1", + "hcom_reduceScatter__114_467_1", "hcom_allGather__114_468_1", "hcom_reduceScatter__114_475_1", + "hcom_allGather__114_476_1", "hcom_reduceScatter__114_483_1", "hcom_reduceScatter__114_491_1", + "hcom_reduceScatter__114_499_1", "hcom_reduceScatter__114_507_1", "hcom_reduceScatter__114_515_1", + "hcom_reduceScatter__114_531_1", "hcom_reduceScatter__114_539_1", "hcom_reduceScatter__114_547_1", + "hcom_reduceScatter__114_555_1", "hcom_allGather__114_556_1", "hcom_reduceScatter__114_563_1", + "hcom_reduceScatter__114_571_1", "hcom_reduceScatter__114_579_1", "hcom_reduceScatter__114_587_1", + "hcom_reduceScatter__114_595_1", "hcom_reduceScatter__114_603_1", "hcom_reduceScatter__114_611_1", + "hcom_reduceScatter__114_619_1", "hcom_reduceScatter__114_635_1", "hcom_reduceScatter__114_643_1", + "hcom_allGather__114_644_1", "hcom_reduceScatter__114_651_1", "hcom_reduceScatter__114_659_1", + "hcom_reduceScatter__114_667_1", "hcom_allGather__114_668_1", "hcom_reduceScatter__114_675_1", + "hcom_allGather__114_676_1", "hcom_reduceScatter__114_683_1", "hcom_allGather__114_684_1", + "hcom_reduceScatter__114_691_1" + ] + + duration = [ + 8.3508, 15.4094, 9.5789, 8.5513, 8.3012, 9.1346, 8.7032, 9.3836, 8.7531, 11.9869, 9.8575, 9.7712, 9.9296, + 12.6163, 9.6824, 9.1268, 11.0426, 15.7377, 48.7819, 73.1451, 134.33, 14.7282, 127.4724, 127.9985, 12.5301, + 124.9251, 123.348, 122.798, 123.1688, 132.2497, 11.5286, 120.421, 12.1733, 123.3453, 9.9289, 124.3953, + 124.8201, 126.5423, 122.8442, 130.256, 12.7242, 128.1858, 12.174, 123.4281, 123.2906, 122.3294, 123.7423, + 126.1776, 127.7836, 127.616, 123.5298, 120.636, 11.249, 123.3667, 125.7421, 123.9869, 124.2625, 121.3439, + 124.2089, 126.8418, 123.9893, 125.8097, 117.6455, 13.4391, 124.0685, 126.6376, 123.167, 12.0098, 121.3413, + 13.7026, 118.2242, 13.1474, 116.1516 + ] + bandwidth = [ + 6.38, 11.11, 5.2, 6.64, 7.02, 4.97, 7.83, 8.02, 6.44, 8.54, 4.59, 4.17, 6.48, 5.02, 6.13, 4.42, 5.17, + 12.26, 13.98, 3.5, 4.48, 2.95, 3.13, 2.87, 4.96, 2.83, 2.5, 2.58, 3.36, 2.89, 3.99, 3.26, 3.76, 2.98, + 5.14, 2.95, 2.74, 2.4, 2.37, 2.94, 3.76, 3.14, 4.12, 2.92, 2.6, 2.35, 2.38, 2.5, 2.9, 3.35, 2.5, 2.92, + 4.23, 2.76, 2.07, 2.48, 2.8, 3.3, 2.4, 2.59, 2.41, 2.94, 5.01, 3.33, 2.53, 2.66, 2.87, 4.51, 3.28, 3.7, + 6.45, 3.85, 9.02 + ] + try: + df = pd.read_excel(self.result_excel.get("all", None), sheet_name='Bandwidth Contention Analysis', header=0) + except FileNotFoundError: + logging.error("File %s not found.", str(self.result_excel.get("all", None))) + return + + for index, row in df.iterrows(): + self.assertEqual(bandwidth_contention_analysis[index], row["op name"]) + self.assertEqual(duration[index], round(row["duration(ms)"], 4)) + self.assertEqual(bandwidth[index], round(row["bandwidth(GB/s)"], 2)) + + + def test_aicpu_operator(self): + op_name = ["aclnnEqScalar_EqualAiCpu_Equal", "aclnnPowTensorScalar_SquareAiCpu_Square"] + op_type = ["Equal", "Square"] + task_duration = [94.422, 87.862] + input_shapes = ["\"41;\"", "\"41\""] + input_data_types = ["DOUBLE;DOUBLE", "INT64"] + input_formats = ["FORMAT_ND;FORMAT_ND", "FORMAT_ND"] + output_shapes = ["\"41\"", "\"41\""] + output_data_types = ["BOOL", "INT64"] + output_formats = ["FORMAT_ND", "FORMAT_ND"] + stack_info = [True, True] + + t0_description = ["Square, Equal"] + t0_suggestion = ["aclnnEqScalar_EqualAiCpu_Equal"] + t0_elapsed_time = ["182.28"] + t0_time_ratio = ["0.0"] + t1_operator_type = ["Equal"] + t1_counts = ["1"] + t1_elapsed_time = ["94.42"] + t2_operator_type = ["Square"] + t2_counts = ["1"] + t2_elapsed_time = ["87.86"] + b_names = ["Equal", "Suggestion 1:", "Square", "Suggestion 1:"] + + try: + df = pd.read_excel(self.result_excel.get("all", None), sheet_name='AICPU Issues', header=0) + except FileNotFoundError: + logging.error("File %s not found.", str(self.result_excel.get("all", None))) + return + + for index, row in df.iterrows(): + self.assertEqual(op_name[index], row["op_name"]) + self.assertEqual(op_type[index], row["op_type"]) + self.assertEqual(task_duration[index], round(row["task_duration"], 3)) + self.assertEqual(input_shapes[index], row["input_shapes"]) + self.assertEqual(input_data_types[index], row["input_data_types"]) + self.assertEqual(input_formats[index], row["input_formats"]) + self.assertEqual(output_shapes[index], row["output_shapes"]) + self.assertEqual(output_data_types[index], row["output_data_types"]) + self.assertEqual(output_formats[index], row["output_formats"]) + self.assertEqual(stack_info[index], math.isnan(row["stack_info"])) + + soup = BeautifulSoup(open(self.result_html.get("all", None)), 'html.parser') + for h2 in soup.find_all('h2'): + if h2.contents[0] == "AICPU Issues": + div_content = h2.next.next.next + table = div_content.find_all('table') + for row_index, row in enumerate(table[0].find_all('tr')): + if row_index == 0: + continue + self.assertEqual(t0_description[row_index - 1], + row.find_all('td')[0].text.split(":")[1].replace("\n", "")) + self.assertEqual(t0_suggestion[row_index - 1], row.find_all('td')[1].text.split(" ")[-1]) + self.assertEqual(t0_elapsed_time[row_index - 1], row.find_all('td')[2].text) + self.assertEqual(t0_time_ratio[row_index - 1], row.find_all('td')[3].text) + for row_index, row in enumerate(table[1].find_all('tr')): + if row_index == 0: + continue + self.assertEqual(t1_operator_type[row_index - 1], row.find_all('td')[0].text) + self.assertEqual(t1_counts[row_index - 1], row.find_all('td')[1].text) + self.assertEqual(t1_elapsed_time[row_index - 1], row.find_all('td')[2].text) + for row_index, row in enumerate(table[2].find_all('tr')): + if row_index == 0: + continue + self.assertEqual(t2_operator_type[row_index - 1], row.find_all('td')[0].text) + self.assertEqual(t2_counts[row_index - 1], row.find_all('td')[1].text) + self.assertEqual(t2_elapsed_time[row_index - 1], row.find_all('td')[2].text) + + b_contents = div_content.find_all('b') + for b_index, b_content in enumerate(b_contents): + self.assertEqual(b_names[b_index], b_content.text) + + def test_operator_dispatch(self): + issues = ["operator dispatch"] + op_name = ["aclopCompileAndExecute"] + counts = [381] + total_time = [64611.056] + + t0_description = ["381"] + t0_suggestion = ["torch_npu.npu.set_compile_mode(jit_compile=False)"] + t1_issue = ["aclopCompileAndExecute"] + t1_counts = ['381'] + t1_elapsed_time = ['64611.05599999996'] + + try: + df = pd.read_excel(self.result_excel.get("all", None), sheet_name='Operator Dispatch Issues', header=0) + except FileNotFoundError: + logging.error("File %s not found.", str(self.result_excel.get("all", None))) + return + for index, row in df.iterrows(): + self.assertEqual(issues[index], row["Issues"]) + self.assertEqual(op_name[index], row["op name"]) + self.assertEqual(counts[index], row["counts"]) + self.assertEqual(total_time[index], round(row["total time"], 3)) + + soup = BeautifulSoup(open(self.result_html.get("all", None)), 'html.parser') + for h2 in soup.find_all('h2'): + if h2.contents[0] == "Operator Dispatch Issues": + div_content = h2.next.next.next + table = div_content.find_all('table') + for row_index, row in enumerate(table[0].find_all('tr')): + if row_index == 0: + continue + self.assertEqual(t0_description[row_index - 1], row.find_all('td')[0].text.split(' ')[1]) + self.assertEqual(t0_suggestion[row_index - 1], + row.find_all('td')[1].text.split('`')[1].split(';')[0]) + for row_index, row in enumerate(table[1].find_all('tr')): + if row_index == 0: + continue + self.assertEqual(t1_issue[row_index - 1], row.find_all('td')[0].text) + self.assertEqual(t1_counts[row_index - 1], row.find_all('td')[1].text) + self.assertEqual(t1_elapsed_time[row_index - 1], row.find_all('td')[2].text) + + diff --git "a/security_statement/\345\205\254\347\275\221\345\234\260\345\235\200.md" "b/security_statement/\345\205\254\347\275\221\345\234\260\345\235\200.md" index f605b4883e2ded36af6e526981fb3aee80c4c863..dfe3b5e5915e73bfa3de72fa2a07d486764a9616 100644 --- "a/security_statement/\345\205\254\347\275\221\345\234\260\345\235\200.md" +++ "b/security_statement/\345\205\254\347\275\221\345\234\260\345\235\200.md" @@ -1,33 +1,33 @@ -| 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地址 | 用途说明 | -| -------- | ------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------ | -| 开源软件 | - | 所有文件 | http://www.apache.org/licenses/LICENSE-2.0 | 文件头中的license信息说明 | -| 开源软件 | - | debug/accuracy_tools/setup.py | pmail_mindstudio@huawei.com | 用于软件包的author-email信息 | -| 开源软件 | - | debug/accuracy_tools/setup.py | https://gitee.com/ascend/mstt/tree/master/debug/accuracy_tools/msprobe | 用于软件包的home-page信息 | -| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/googletest/repository/archive/release-1.12.1.tar.gz | 开源软件下载 | -| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/sinojelly/mockcpp/repository/archive/v2.7.zip | 开源软件下载 | -| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/JSON-for-Modern-CPP/repository/archive/v3.10.1.zip | 开源软件下载 | -| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/openssl/repository/archive/OpenSSL_1_1_1k.tar.gz | 开源软件下载 | -| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/protobuf_source/repository/archive/v3.15.0.tar.gz | 开源软件下载 | -| 开源软件 | - | /.gitmodules | [https://github.com/facebookincubator/dynolog.git](https://gitee.com/link?target=https%3A%2F%2Fgithub.com%2Ffacebookincubator%2Fdynolog.git) | 在线监控底座 | -| 开源软件 | - | /msmonitor/dynolog_npu/cmake/config.ini | https://gitee.com/mirrors/openssl.git | 开源软件下载 | -| 开源软件 | - | /msmonitor/scripts/build.sh | [https://github.com/RustingSword/tensorboard_logger.git](https://gitee.com/link?target=https%3A%2F%2Fgithub.com%2FRustingSword%2Ftensorboard_logger.git) | 开源软件下载 | -| 开源软件 | - | /msmonitor/README.md | [https://github.com/tensorflow/tensorboard](https://gitee.com/link?target=https%3A%2F%2Fgithub.com%2Ftensorflow%2Ftensorboard) | tensorboard官网教程 | -| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.hiascend.com/document/detail/zh/canncommercial/80RC2/devaids/auxiliarydevtool/atlasprofiling_16_0038.html](https://gitee.com/link?target=https%3A%2F%2Fwww.hiascend.com%2Fdocument%2Fdetail%2Fzh%2Fcanncommercial%2F80RC2%2Fdevaids%2Fauxiliarydevtool%2Fatlasprofiling_16_0038.html) | MindStudio Ascend PyTorch Profiler参考示例 | -| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | https://gitee.com/ascend/mstt/blob/master/profiler/msprof_analyze/advisor/doc/Samples of Fused Operator API Replacement.md" | Advisor优化手段参考示例 | -| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.hiascend.com/document/detail/zh/canncommercial/80RC2/devaids/auxiliarydevtool/aoe_16_043.html](https://gitee.com/link?target=https%3A%2F%2Fwww.hiascend.com%2Fdocument%2Fdetail%2Fzh%2Fcanncommercial%2F80RC2%2Fdevaids%2Fauxiliarydevtool%2Faoe_16_043.html) | Advisor优化手段参考示例 | -| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.mindspore.cn/lite/docs/en/master/use/cloud_infer/converter_tool_ascend.html#aoe-auto-tuning](https://gitee.com/link?target=https%3A%2F%2Fwww.mindspore.cn%2Flite%2Fdocs%2Fen%2Fmaster%2Fuse%2Fcloud_infer%2Fconverter_tool_ascend.html%23aoe-auto-tuning) | Advisor优化手段参考示例 | -| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.hiascend.com/document/detail/zh/canncommercial/700/modeldevpt/ptmigr/AImpug_000060.html](https://gitee.com/link?target=https%3A%2F%2Fwww.hiascend.com%2Fdocument%2Fdetail%2Fzh%2Fcanncommercial%2F700%2Fmodeldevpt%2Fptmigr%2FAImpug_000060.html) | Advisor优化手段参考示例 | -| 开源软件 | - | /profiler/msprof_analyze/config/config.ini | https://gitee.com/ascend/mstt/tree/master/profiler/msprof_analyze | msprof-analyze工具地址 | -| 开源软件 | - | /profiler/msprof_analyze/LICENSE | [http://www.apache.org/licenses/LICENSE-2.0](https://gitee.com/link?target=http%3A%2F%2Fwww.apache.org%2Flicenses%2FLICENSE-2.0) | 开源软件协议地址 | -| 开源软件 | - | /profiler/msprof_analyze/advisor/rules/aicpu_rules.yaml | https://gitee.com/ascend/mstt/blob/master/profiler/msprof_analyze/advisor/doc/Samples of AI CPU Operator Replacement.md | AI CPU 算子替换样例 | -| 开源软件 | - | /profiler/msprof_analyze/advisor/rules/environment_variable_info.yaml | [https://support.huawei.com/enterprise/zh/doc/EDOC1100371278/5eeeed85?idPath=23710424](https://gitee.com/link?target=https%3A%2F%2Fsupport.huawei.com%2Fenterprise%2Fzh%2Fdoc%2FEDOC1100371278%2F5eeeed85%3FidPath%3D23710424) | 组网指南 | -| 开源软件 | - | /profiler/msprof_analyze/config/config.ini | [pmail_mindstudio@huawei.com](https://gitee.com/link?target=mailto%3Apmail_mindstudio%40huawei.com) | 公网邮箱 | -| 开源软件 | - | plugins/tensorboard-plugins/tb_graph_ascend/setup.py | pmail_mindstudio@huawei.com | MindStudio官方邮箱 | -| 开源软件 | - | plugins/tensorboard-plugins/tb_graph_ascend/setup.py | https://gitee.com/ascend/mstt/tree/master/plugins/tensorboard-plugins/tb_graph_ascend | 代码仓地址 | -| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://npms.io | 构建引入，注释 | -| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://github.com/webcomponents/shadycss/issues/193 | 构建引入，注释 | -| 开源软件 | - | 非源码引入，只是在构建产物中包含 | http://jsbin.com/temexa/4 | 构建引入，注释 | -| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://fonts.googleapis.com/ | 构建引入，组件样式文件 | -| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://developer.mozilla.org/ | 构建引入，注释 | -| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://github.com/vaadin/vaadin-time-picker/issues/145 | 构建引入，注释 | +| 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地址 | 用途说明 | +| -------- | ------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------ | +| 开源软件 | - | 所有文件 | http://www.apache.org/licenses/LICENSE-2.0 | 文件头中的license信息说明 | +| 开源软件 | - | debug/accuracy_tools/setup.py | pmail_mindstudio@huawei.com | 用于软件包的author-email信息 | +| 开源软件 | - | debug/accuracy_tools/setup.py | https://gitee.com/ascend/mstt/tree/master/debug/accuracy_tools/msprobe | 用于软件包的home-page信息 | +| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/googletest/repository/archive/release-1.12.1.tar.gz | 开源软件下载 | +| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/sinojelly/mockcpp/repository/archive/v2.7.zip | 开源软件下载 | +| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/JSON-for-Modern-CPP/repository/archive/v3.10.1.zip | 开源软件下载 | +| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/openssl/repository/archive/OpenSSL_1_1_1k.tar.gz | 开源软件下载 | +| 开源软件 | - | debug/accuracy_tools/cmake/config.ini | https://gitee.com/mirrors/protobuf_source/repository/archive/v3.15.0.tar.gz | 开源软件下载 | +| 开源软件 | - | /.gitmodules | [https://github.com/facebookincubator/dynolog.git](https://gitee.com/link?target=https%3A%2F%2Fgithub.com%2Ffacebookincubator%2Fdynolog.git) | 在线监控底座 | +| 开源软件 | - | /msmonitor/dynolog_npu/cmake/config.ini | https://gitee.com/mirrors/openssl.git | 开源软件下载 | +| 开源软件 | - | /msmonitor/scripts/build.sh | [https://github.com/RustingSword/tensorboard_logger.git](https://gitee.com/link?target=https%3A%2F%2Fgithub.com%2FRustingSword%2Ftensorboard_logger.git) | 开源软件下载 | +| 开源软件 | - | /msmonitor/README.md | [https://github.com/tensorflow/tensorboard](https://gitee.com/link?target=https%3A%2F%2Fgithub.com%2Ftensorflow%2Ftensorboard) | tensorboard官网教程 | +| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.hiascend.com/document/detail/zh/canncommercial/80RC2/devaids/auxiliarydevtool/atlasprofiling_16_0038.html](https://gitee.com/link?target=https%3A%2F%2Fwww.hiascend.com%2Fdocument%2Fdetail%2Fzh%2Fcanncommercial%2F80RC2%2Fdevaids%2Fauxiliarydevtool%2Fatlasprofiling_16_0038.html) | MindStudio Ascend PyTorch Profiler参考示例 | +| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | https://gitee.com/ascend/mstt/blob/master/profiler/msprof_analyze/advisor/doc/Samples of Fused Operator API Replacement.md" | Advisor优化手段参考示例 | +| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.hiascend.com/document/detail/zh/canncommercial/80RC2/devaids/auxiliarydevtool/aoe_16_043.html](https://gitee.com/link?target=https%3A%2F%2Fwww.hiascend.com%2Fdocument%2Fdetail%2Fzh%2Fcanncommercial%2F80RC2%2Fdevaids%2Fauxiliarydevtool%2Faoe_16_043.html) | Advisor优化手段参考示例 | +| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.mindspore.cn/lite/docs/en/master/use/cloud_infer/converter_tool_ascend.html#aoe-auto-tuning](https://gitee.com/link?target=https%3A%2F%2Fwww.mindspore.cn%2Flite%2Fdocs%2Fen%2Fmaster%2Fuse%2Fcloud_infer%2Fconverter_tool_ascend.html%23aoe-auto-tuning) | Advisor优化手段参考示例 | +| 开源软件 | - | /profiler/msprof_analyze/advisor/config/config.ini | [https://www.hiascend.com/document/detail/zh/canncommercial/700/modeldevpt/ptmigr/AImpug_000060.html](https://gitee.com/link?target=https%3A%2F%2Fwww.hiascend.com%2Fdocument%2Fdetail%2Fzh%2Fcanncommercial%2F700%2Fmodeldevpt%2Fptmigr%2FAImpug_000060.html) | Advisor优化手段参考示例 | +| 开源软件 | - | /profiler/msprof_analyze/config/config.ini | https://gitee.com/ascend/mstt/tree/master/profiler/msprof_analyze | msprof-analyze工具地址 | +| 开源软件 | - | /profiler/msprof_analyze/LICENSE | [http://www.apache.org/licenses/LICENSE-2.0](https://gitee.com/link?target=http%3A%2F%2Fwww.apache.org%2Flicenses%2FLICENSE-2.0) | 开源软件协议地址 | +| 开源软件 | - | /profiler/msprof_analyze/advisor/rules/aicpu_rules.yaml | https://gitee.com/ascend/mstt/blob/master/profiler/msprof_analyze/advisor/doc/Samples of AI CPU Operator Replacement.md | AI CPU 算子替换样例 | +| 开源软件 | - | /profiler/msprof_analyze/advisor/rules/environment_variable_info.yaml | [https://support.huawei.com/enterprise/zh/doc/EDOC1100371278/5eeeed85?idPath=23710424](https://gitee.com/link?target=https%3A%2F%2Fsupport.huawei.com%2Fenterprise%2Fzh%2Fdoc%2FEDOC1100371278%2F5eeeed85%3FidPath%3D23710424) | 组网指南 | +| 开源软件 | - | /profiler/msprof_analyze/config/config.ini | [pmail_mindstudio@huawei.com](https://gitee.com/link?target=mailto%3Apmail_mindstudio%40huawei.com) | 公网邮箱 | +| 开源软件 | - | plugins/tensorboard-plugins/tb_graph_ascend/setup.py | pmail_mindstudio@huawei.com | MindStudio官方邮箱 | +| 开源软件 | - | plugins/tensorboard-plugins/tb_graph_ascend/setup.py | https://gitee.com/ascend/mstt/tree/master/plugins/tensorboard-plugins/tb_graph_ascend | 代码仓地址 | +| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://npms.io | 构建引入，注释 | +| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://github.com/webcomponents/shadycss/issues/193 | 构建引入，注释 | +| 开源软件 | - | 非源码引入，只是在构建产物中包含 | http://jsbin.com/temexa/4 | 构建引入，注释 | +| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://fonts.googleapis.com/ | 构建引入，组件样式文件 | +| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://developer.mozilla.org/ | 构建引入，注释 | +| 开源软件 | - | 非源码引入，只是在构建产物中包含 | https://github.com/vaadin/vaadin-time-picker/issues/145 | 构建引入，注释 | | 开源软件 | - | 非源码引入，只是在构建产物中包含 | http://codepen.io/shyndman/pen/ | 构建引入，注释 | \ No newline at end of file