-
-
-
- {{ $t('profiling.timeLine') }}
-
-
-
-
-
-
-
-
- {{$t('profiling.scopeNameNum')}}
-
-
-
-
-
-
-
- {{$t('profiling.opTotalTime')}}{{timelineInfo.totalTime}}ms
-
-
- {{$t('profiling.streamNum')}}{{timelineInfo.streamNum}}
-
-
- {{$t('profiling.opNum')}}{{timelineInfo.opNum}}
-
-
- {{$t('profiling.opTimes')}}{{timelineInfo.opTimes + $t('profiling.times')}}
-
-
-
-
-
- ![]()
-
- {{$t("public.dataLoading")}}
-{{$t("public.noData")}}
-
+
+
{{ $t('profiling.timeLineMsprof') }}
+ v-if="!timelineInfoMsprof.noData">
{{$t('profiling.rankList')}}
@@ -578,7 +444,7 @@ limitations under the License.
-
+
@@ -710,23 +587,6 @@ export default {
colorList: CommonProperty.pieColorArr[this.$store.state.themeIndex],
initOver: false, // Is initialization complete
},
- timeLine: {
- // Time line data
- data: null,
- waiting: false, // Is it waiting for interface return
- disable: true,
- },
- timelineInfo: {
- // Time line information
- totalTime: 0,
- streamNum: 0,
- opNum: 0, // Number of operators
- opTimes: 0, // Operator time consuming
- noData: true,
- initOver: false, // Is initialization complete
- scopeNameNum: '',
- scopeNameNumArr: [],
- },
timeLineMsprof: {
// Time line data
data: null,
@@ -735,6 +595,8 @@ export default {
},
timelineInfoMsprof: {
// Time line information
+ noData: true,
+ initOver: false,
rankListSelected: [],
rankList: [],
modelListSelected: [],
@@ -755,6 +617,14 @@ export default {
value: false,
label: 'No'
}],
+ scopeNameSelected: false,
+ scopeNameArr: [{
+ value: true,
+ label: 'Yes'
+ }, {
+ value: false,
+ label: 'No'
+ }],
},
processSummary: {
// Data of process summary
@@ -774,7 +644,6 @@ export default {
initOver: false, // Is initialization complete
},
themeIndex: this.$store.state.themeIndex,
- isHeterogeneous: false,
pynativeOpType: {
all: 'pynative_type',
detail: 'pynative_detail',
@@ -855,7 +724,7 @@ export default {
setTimeout(() => {
this.$bus.$on('collapse', this.resizeTrace);
}, 500);
- if (!this.isPynative) this.queryMsprofTimelineOption();
+ this.queryMsprofTimelineOption();
},
watch: {
rankID: {
@@ -863,7 +732,6 @@ export default {
if (isInteger(newValue)) {
this.svg.initOver = false;
this.pieChart.initOver = false;
- this.timelineInfo.initOver = false;
this.processSummary.initOver = false;
this.init();
} else {
@@ -872,9 +740,7 @@ export default {
this.svg.noData = true;
this.svg.initOver = true;
this.pieChart.initOver = true;
- this.timelineInfo.initOver = true;
this.processSummary.initOver = true;
- this.timeLine.waiting = false;
}
}
},
@@ -886,7 +752,6 @@ export default {
* Initialization function
*/
init() {
- this.queryTimelineInfo();
if (this.isDynamic) {
this.$nextTick(() => {
this.initShapeStep();
@@ -1205,7 +1070,6 @@ export default {
RequestService.queryTrainingTrace(params).then(
(res) => {
this.svg.initOver = true;
- this.isHeterogeneous = res.data.is_heterogeneous;
if (res && res.data && res.data.training_trace_graph && res.data.training_trace_graph.length) {
this.svg.noData = false;
this.removeTrace();
@@ -1246,7 +1110,6 @@ export default {
this.totalSteps = '--';
this.totalTime = '--';
this.tailPercent = '--';
- this.isHeterogeneous = false;
},
);
},
@@ -1570,83 +1433,7 @@ export default {
this.svg.resizeTimer = null;
}, 500);
},
- /**
- * Query the data of time line
- */
- queryTimelineInfo() {
- const params = {
- dir: this.trainInfo.path,
- device_id: this.rankID,
- };
- RequestService.queryTimelineInfo(params)
- .then((res) => {
- this.timelineInfo.initOver = true;
- if (res && res.data) {
- this.timelineInfo.noData = false;
- this.timelineInfo.totalTime =
- this.toFixedFun(res.data.total_time, 4) || (res.data.total_time === 0 ? 0 : '--');
- this.timelineInfo.streamNum = res.data.num_of_streams || (res.data.num_of_streams === 0 ? 0 : '--');
- this.timelineInfo.opNum = res.data.num_of_ops || (res.data.num_of_ops === 0 ? 0 : '--');
- this.timelineInfo.opTimes = res.data.op_exe_times || (res.data.op_exe_times === 0 ? 0 : '--');
- if (res.data.max_scope_name_num >= 0) {
- this.timelineInfo.scopeNameNum = res.data.max_scope_name_num;
- this.timelineInfo.scopeNameNumArr = Array(res.data.max_scope_name_num + 1)
- .fill()
- .map((value, key) => {
- return {
- label: key,
- value: key,
- };
- });
- this.queryTimeline();
- } else {
- this.timeLine.disable = true;
- }
- } else {
- this.timelineInfo.noData = true;
- this.timeLine.disable = true;
- }
- })
- .catch(() => {
- this.timelineInfo.noData = true;
- this.timelineInfo.initOver = true;
- this.timeLine.disable = true;
- });
- },
- queryTimeline() {
- this.timeLine.waiting = true;
- this.timeLine.disable = true;
- const params = {
- dir: this.trainInfo.path,
- device_id: this.rankID,
- scope_name_num: this.timelineInfo.scopeNameNum,
- };
- RequestService.queryTimeline(params)
- .then((res) => {
- this.timeLine.waiting = false;
- if (res && res.data && res.data.length) {
- this.timeLine.data = JSON.stringify(res.data);
- this.timeLine.disable = false;
- }
- })
- .catch(() => {
- this.timeLine.waiting = false;
- });
- },
- /**
- * Download timeline data file
- */
- downloadTimelineFile() {
- const downloadLink = document.createElement('a');
- downloadLink.download = this.getDocName();
- downloadLink.style.display = 'none';
- const blob = new Blob([this.timeLine.data]);
- downloadLink.href = URL.createObjectURL(blob);
- document.body.appendChild(downloadLink);
- downloadLink.click();
- document.body.removeChild(downloadLink);
- },
/**
* Query the data of msprof time line
*/
@@ -1656,7 +1443,7 @@ export default {
};
RequestService.queryMsprofTimelineOption(params)
.then((res) => {
- this.timelineInfo.initOver = true;
+ this.timelineInfoMsprof.initOver = true;
if (res && res.data && res.data.rank_list && res.data.model_list) {
this.timelineInfoMsprof.noData = false;
this.timeLineMsprof.disable = false;
@@ -1681,7 +1468,6 @@ export default {
})
.catch(() => {
this.timelineInfoMsprof.noData = true;
- this.timelineInfoMsprof.initOver = true;
this.timeLineMsprof.disable = true;
});
},
@@ -1694,14 +1480,15 @@ export default {
model_list: this.timelineInfoMsprof.modelListSelected,
kind: this.timelineInfoMsprof.kindSelected,
merge_model: this.timelineInfoMsprof.mergeModelSelected,
+ scope_name: this.timelineInfoMsprof.scopeNameSelected,
};
RequestService.queryMsprofTimeline(params)
.then((res) => {
this.timeLineMsprof.waiting = false;
if (res && res.data && res.data.length) {
this.timeLineMsprof.data = JSON.stringify(res.data);
+ this.downloadTimelineMsprofFile();
this.timeLineMsprof.disable = false;
- this.downloadTimelineMsprofFile()
}
})
.catch(() => {
@@ -1758,30 +1545,7 @@ export default {
this.processSummary.noData = false;
}
},
- /**
- * Generate a download file name
- * @return {String}
- */
- getDocName() {
- const dealNumber = (value) => {
- const prefix = value < 10 ? '0' : '';
- return prefix + value;
- };
- const replacedPrefix = './';
- let dir = this.trainInfo.dir;
- if (dir === replacedPrefix) dir = ' ';
- if (dir.startsWith(replacedPrefix)) dir = dir.replace(replacedPrefix, '');
- const date = new Date();
- const year = date.getFullYear();
- const mouth = dealNumber(date.getMonth() + 1);
- const day = dealNumber(date.getDate());
- const hour = dealNumber(date.getHours());
- const minute = dealNumber(date.getMinutes());
- const second = dealNumber(date.getSeconds());
- const millisecond = date.getMilliseconds();
- const timestamp = `${year}${mouth}${day}${hour}${minute}${second}${millisecond}`;
- return `timeline_${dir}_${this.rankID}_scope-num-${this.timelineInfo.scopeNameNum}_${timestamp}.json`;
- },
+
/**
* Generate a download msprof file name
* @return {String}
diff --git a/requirements.txt b/requirements.txt
index 0a955d1375e5f2c965202af8eaa1cc18caa5300d..034122e2041229db10b831223bad014815074725 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,7 +5,7 @@ itsdangerous >= 1.1.0
Jinja2 >= 2.10.1
MarkupSafe >= 1.1.1
marshmallow >= 3.10.0
-numpy >= 1.17.0
+numpy >= 1.17.0, <= 1.26.4
pillow >= 6.2.0
protobuf >= 3.13.0 , <= 3.20.1
psutil >= 5.7.0
@@ -13,7 +13,7 @@ pyyaml >= 5.3.1
scipy >= 1.5.2
scikit-learn >= 0.23.1
Werkzeug > 2.1.0
-pandas >= 1.0.4 , <= 1.2.5
+pandas >= 1.0.4 , <= 1.3.3
treelib >= 1.6.1
grpcio >= 1.39.0
XlsxWriter >= 1.3.2
\ No newline at end of file
diff --git a/tests/st/func/profiler/test_aicpu_analyser.py b/tests/st/func/profiler/test_aicpu_analyser.py
index 7a33680071182b3463885e5a6c9d1618ad544fa6..3c64f2fc185fb5b6a88f89cb720acb7709c87c8c 100644
--- a/tests/st/func/profiler/test_aicpu_analyser.py
+++ b/tests/st/func/profiler/test_aicpu_analyser.py
@@ -54,7 +54,7 @@ class TestAicpuAnalyser:
def test_query_aicpu_type(self):
"""Test the function of querying AICPU operator type information."""
expect_result = {
- 'col_name': ['op_type', 'execution_time', 'execution_frequency', 'percent'],
+ 'col_name': ['kernel_type', 'execution_time', 'execution_frequency', 'percent'],
'object': [
['InitData', 7906.0, 1, 89.84],
['GetNext', 590.5, 2, 6.71],
@@ -74,7 +74,7 @@ class TestAicpuAnalyser:
def test_query_aicpu_detail(self):
"""Test the function of querying AICPU operator type information."""
expect_result = {
- 'col_name': ['op_name', 'op_type', 'total_time',
+ 'col_name': ['kernel_name', 'kernel_type', 'total_time',
'dispatch_time', 'execution_frequency'],
'size': 3
}
diff --git a/tests/st/func/profiler/test_cluster_analyser.py b/tests/st/func/profiler/test_cluster_analyser.py
index f94f4282ea75712d58f666a84b46c57564d1c090..bc43e0666ce66f112794e02cef1db5957fdd8ada 100644
--- a/tests/st/func/profiler/test_cluster_analyser.py
+++ b/tests/st/func/profiler/test_cluster_analyser.py
@@ -59,7 +59,7 @@ class TestClusterAnalyser:
}
expect_result = {
"total_step_num": '1',
- "info": [{"step_trace_info": [0.0, 23.6681, 0.041],
+ "info": [{"step_trace_info": [0.0, 23.6681, 0.041, 23.7091],
"rank_id": 1,
"profiler_dir": "profiler"
}],
diff --git a/tests/st/func/profiler/test_op_analyser.py b/tests/st/func/profiler/test_op_analyser.py
index 3357b914450a81567fbce9dffe16773a5a70e890..e5dc553bcd6c59268222703e51621a690375ea40 100644
--- a/tests/st/func/profiler/test_op_analyser.py
+++ b/tests/st/func/profiler/test_op_analyser.py
@@ -27,19 +27,19 @@ from tests.st.func.profiler.conftest import BASE_SUMMARY_DIR
OP_GATHER_V2_INFO = {
'col_name':
- ['op_name', 'op_type', 'avg_execution_time', 'execution_frequency',
- 'MFLOPs(10^6 cube)', 'GFLOPS(10^9 cube)', 'MFLOPs(10^6 vector)', 'GFLOPS(10^9 vector)', 'full_op_name',
+ ['op_name', 'kernel_name', 'kernel_type', 'avg_execution_time', 'execution_frequency',
+ 'MFLOPs(10^6 cube)', 'GFLOPS(10^9 cube)', 'MFLOPs(10^6 vector)', 'GFLOPS(10^9 vector)',
'op_info'],
'object': [
[
- 'AssignAdd-op203', 'AssignAdd', 1.79, 3, '-', '-', '-', '-', 'Default/AssignAdd-op203',
+ 'Default/AssignAdd-op203', 'AssignAdd-op203', 'AssignAdd', 1.79, 3, '-', '-', '-', '-',
{'input_0': {'format': 'DEFAULT', 'data_type': 'INT32', 'shape': [1]},
'input_1': {'format': 'DEFAULT', 'data_type': 'INT32', 'shape': [1]},
'output_0': {'format': 'DEFAULT', 'data_type': 'INT32', 'shape': [1]}
}
],
[
- 'AssignAdd-op206', 'AssignAdd', 1.283, 3, '-', '-', '-', '-', 'Default/AssignAdd-op206',
+ 'Default/AssignAdd-op206', 'AssignAdd-op206', 'AssignAdd', 1.283, 3, '-', '-', '-', '-',
{'input_0': {'format': 'DEFAULT', 'data_type': 'INT32', 'shape': [1]},
'input_1': {'format': 'DEFAULT', 'data_type': 'INT32', 'shape': [1]},
'output_0': {'format': 'DEFAULT', 'data_type': 'INT32', 'shape': [1]}
@@ -77,7 +77,7 @@ class TestOpAnalyser:
"""Test the function of querying AICORE operator type information."""
expect_result = {
'col_name':
- ['op_type', 'total_time', 'execution_frequency', 'total_percent', 'avg_time'],
+ ['kernel_type', 'total_time', 'execution_frequency', 'total_percent', 'avg_time'],
'object': [['MatMul', 2807.82, 25, 5760.0, 112.313],
['Cast', 104.32, 27, 214.0, 3.864],
['TransData', 86.12, 9, 177.0, 9.569],
@@ -123,7 +123,7 @@ class TestOpAnalyser:
"""Test the function of querying AICORE operator type information."""
expect_result = {
'col_name':
- ['op_type', 'total_time', 'execution_frequency', 'total_percent', 'avg_time'],
+ ['kernel_type', 'total_time', 'execution_frequency', 'total_percent', 'avg_time'],
'object': [
['MatMul', 2807.82, 25, 5760.0, 112.313],
['Mul', 4.29, 3, 9.0, 1.43]
@@ -132,7 +132,7 @@ class TestOpAnalyser:
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'partial_match_str_in': ['Mul']
}
},
@@ -155,7 +155,7 @@ class TestOpAnalyser:
expect_result = OP_GATHER_V2_INFO
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'in': ['AssignAdd']
}
},
diff --git a/tests/ut/profiler/analyser/test_aicpu_analyser.py b/tests/ut/profiler/analyser/test_aicpu_analyser.py
index 8133274f325d0fbb09ff7760e5b964204b4c7246..d3fe6ad61ea4b8f50db32ce9ff8accee3bef2c9f 100644
--- a/tests/ut/profiler/analyser/test_aicpu_analyser.py
+++ b/tests/ut/profiler/analyser/test_aicpu_analyser.py
@@ -47,7 +47,7 @@ class TestAicpuAnalyser:
def test_query_aicpu_type(self):
"""Test the function of querying AICPU operator type information."""
expect_result = {
- 'col_name': ['op_type', 'execution_time', 'execution_frequency', 'percent'],
+ 'col_name': ['kernel_type', 'execution_time', 'execution_frequency', 'percent'],
'object': [
['InitData', 7906.0, 1, 89.84],
],
@@ -55,7 +55,7 @@ class TestAicpuAnalyser:
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'partial_match_str_in': ['init']
}
}
@@ -66,14 +66,14 @@ class TestAicpuAnalyser:
def test_query_aicpu_detail(self):
"""Test the function of querying AICPU operator detail information."""
expect_result = {
- 'col_name': ['op_name', 'op_type', 'total_time',
+ 'col_name': ['kernel_name', 'kernel_type', 'total_time',
'dispatch_time', 'execution_frequency'],
'size': 1
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'partial_match_str_in': ['get']
}
}
diff --git a/tests/ut/profiler/analyser/test_analyser_aicore_detail.py b/tests/ut/profiler/analyser/test_analyser_aicore_detail.py
index 3b325b8c465af07ab02fe7e62eb46d7b34252dfc..d91c4ed4848a4b25d44e553aa27783df9c51413e 100644
--- a/tests/ut/profiler/analyser/test_analyser_aicore_detail.py
+++ b/tests/ut/profiler/analyser/test_analyser_aicore_detail.py
@@ -21,8 +21,8 @@ from unittest import TestCase
from mindinsight.profiler.analyser.analyser_factory import AnalyserFactory
from tests.ut.profiler import PROFILER_DIR
-COL_NAMES = ['op_name', 'op_type', 'avg_execution_time', 'execution_frequency', 'MFLOPs(10^6 cube)',
- 'GFLOPS(10^9 cube)', 'MFLOPs(10^6 vector)', 'GFLOPS(10^9 vector)', 'full_op_name', 'op_info']
+COL_NAMES = ['op_name', 'kernel_name', 'kernel_type', 'avg_execution_time', 'execution_frequency',
+ 'MFLOPs(10^6 cube)', 'GFLOPS(10^9 cube)', 'MFLOPs(10^6 vector)', 'GFLOPS(10^9 vector)', 'op_info']
def get_detail_infos(indexes=None, sort_name=None, sort_type=True):
@@ -52,9 +52,9 @@ def get_detail_infos(indexes=None, sort_name=None, sort_type=True):
for fm_info, detail_info, flops_line in zip(fm_csv_reader, detail_csv_reader, flops_reader):
flops = flops_line.strip().split(',')
cache.append(
- [fm_info[4], fm_info[5], round(float(detail_info[1]) * 1e3, 3), int(detail_info[2]), float(flops[1]),
- float(flops[2]), float(flops[3]), float(flops[4]),
- fm_info[3], json.loads(fm_info[7]) if fm_info[7] else None]
+ [fm_info[4], fm_info[5], fm_info[6], round(float(detail_info[1]) * 1e3, 3), int(detail_info[2]),
+ float(flops[1]), float(flops[2]), float(flops[3]), float(flops[4]),
+ json.loads(fm_info[8]) if fm_info[8] else None]
)
if indexes:
@@ -99,7 +99,7 @@ class TestAicoreDetailAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'in': ['MatMul']
}
}
@@ -109,7 +109,7 @@ class TestAicoreDetailAnalyser(TestCase):
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'not_in': ['AtomicAddrClean', 'Cast', 'TransData', 'Conv2D']
}
}
@@ -119,7 +119,7 @@ class TestAicoreDetailAnalyser(TestCase):
condition = {
'filter_condition': {
- 'op_name': {
+ 'kernel_name': {
'partial_match_str_in': ['op9']
}
}
@@ -145,12 +145,12 @@ class TestAicoreDetailAnalyser(TestCase):
expect_result = {
'col_name': COL_NAMES,
- 'object': get_detail_infos(sort_name='op_name', sort_type=False),
+ 'object': get_detail_infos(sort_name='kernel_name', sort_type=False),
'size': 10
}
condition = {
'sort_condition': {
- 'name': 'op_name',
+ 'name': 'kernel_name',
'type': 'ascending'
}
}
@@ -198,7 +198,7 @@ class TestAicoreDetailAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_name': {
+ 'kernel_name': {
'partial_match_str_in': ['Atomic', 'Conv']
}
},
@@ -222,10 +222,10 @@ class TestAicoreDetailAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'in': ['Conv2D', 'AtomicAddrClean', 'TransData']
},
- 'op_name': {
+ 'kernel_name': {
'partial_match_str_in': ['Atomic', 'Conv']
}
},
@@ -247,7 +247,7 @@ class TestAicoreDetailAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'in': ['MatMul']
},
'is_display_detail': False
@@ -257,13 +257,13 @@ class TestAicoreDetailAnalyser(TestCase):
self.assertDictEqual(expect_result, result)
expect_result = {
- 'col_name': COL_NAMES[0:8],
- 'object': [item[0:8] for item in detail_infos],
+ 'col_name': COL_NAMES[1:9],
+ 'object': [item[1:9] for item in detail_infos],
'size': 1
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'in': ['MatMul']
},
'is_display_detail': False,
@@ -278,12 +278,12 @@ class TestAicoreDetailAnalyser(TestCase):
"""Test the success of the querying and sorting function by operator type."""
detail_infos = get_detail_infos(indexes=[9, 0, 2, 1, 5, 3, 4])
expect_result = {
- 'col_name': COL_NAMES[0:8],
- 'object': [item[0:8] for item in detail_infos]
+ 'col_name': COL_NAMES[1:9],
+ 'object': [item[1:9] for item in detail_infos]
}
filter_condition = {
- 'op_type': {
+ 'kernel_type': {
'in': ['AtomicAddrClean', 'Cast', 'MatMul'],
'not_in': ['TransData']
},
diff --git a/tests/ut/profiler/analyser/test_analyser_aicore_type.py b/tests/ut/profiler/analyser/test_analyser_aicore_type.py
index 676a208b4e7b858be5359f340b2fb9de9ce359f1..6f27e23ac575568288c88625f767ff7be5b6514a 100644
--- a/tests/ut/profiler/analyser/test_analyser_aicore_type.py
+++ b/tests/ut/profiler/analyser/test_analyser_aicore_type.py
@@ -20,7 +20,7 @@ from unittest import TestCase
from mindinsight.profiler.analyser.analyser_factory import AnalyserFactory
from tests.ut.profiler import PROFILER_DIR
-COL_NAMES = ['op_type', 'total_time', 'execution_frequency', 'total_percent', 'avg_time']
+COL_NAMES = ['kernel_type', 'total_time', 'execution_frequency', 'total_percent', 'avg_time']
def get_type_infos(indexes=None, sort_name=None, sort_type=True):
@@ -93,7 +93,7 @@ class TestAicoreTypeAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'in': ['Cast']
}
}
@@ -108,7 +108,7 @@ class TestAicoreTypeAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'not_in': ['Cast']
}
}
@@ -123,7 +123,7 @@ class TestAicoreTypeAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'partial_match_str_in': ['C']
}
}
@@ -140,7 +140,7 @@ class TestAicoreTypeAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'in': ['Cast', 'Conv2D']
}
}
@@ -155,7 +155,7 @@ class TestAicoreTypeAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'not_in': ['Cast', 'Conv2D']
}
}
@@ -170,7 +170,7 @@ class TestAicoreTypeAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'partial_match_str_in': ['Trans', 'Conv']
}
}
@@ -182,11 +182,11 @@ class TestAicoreTypeAnalyser(TestCase):
"""Test the success of the querying function."""
expect_result = {
'col_name': COL_NAMES,
- 'object': get_type_infos(sort_name='op_type', sort_type=True),
+ 'object': get_type_infos(sort_name='kernel_type', sort_type=True),
'size': 5}
condition = {
'sort_condition': {
- 'name': 'op_type',
+ 'name': 'kernel_type',
'type': 'descending'
}
}
@@ -248,7 +248,7 @@ class TestAicoreTypeAnalyser(TestCase):
}
condition = {
'filter_condition': {
- 'op_type': {
+ 'kernel_type': {
'partial_match_str_in': ['C']
}
},
diff --git a/tests/utils/resource/profiler/aicore_intermediate_1_detail.csv b/tests/utils/resource/profiler/aicore_intermediate_1_detail.csv
index 42a64606f33bd11ea1f80d3e0e2ee4422a402cc2..358d41cd677f29e623bb466728ecc4e46f577abb 100755
--- a/tests/utils/resource/profiler/aicore_intermediate_1_detail.csv
+++ b/tests/utils/resource/profiler/aicore_intermediate_1_detail.csv
@@ -1,4 +1,4 @@
-full_op_time,execution_time,execution_frequency
+full_kernel_time,execution_time,execution_frequency
Default/AtomicAddrClean-op104,0.00133,1
Default/AtomicAddrClean-op105,0.000987,1
Default/AtomicAddrClean-op106,0.001129,1
diff --git a/tests/utils/resource/profiler/aicore_intermediate_1_type.csv b/tests/utils/resource/profiler/aicore_intermediate_1_type.csv
index ad7efca9c19c71116701920302cc91f2d37e8c0d..8021b96fb648d7e7dd317bb93980f5856efb94df 100755
--- a/tests/utils/resource/profiler/aicore_intermediate_1_type.csv
+++ b/tests/utils/resource/profiler/aicore_intermediate_1_type.csv
@@ -1,4 +1,4 @@
-op_type,total_time,execution_frequency,percent
+kernel_type,total_time,execution_frequency,percent
AtomicAddrClean,0.007283,6,0.49
Cast,0.053395,13,3.63
TransData,0.121800,5,8.23
diff --git a/tests/utils/resource/profiler/flops_0.txt b/tests/utils/resource/profiler/flops_0.txt
index 56e7d6574ea1fb9bc3ba07157669b32454d98624..73eb07d60314c5b655c42104c3888374e8f571a3 100644
--- a/tests/utils/resource/profiler/flops_0.txt
+++ b/tests/utils/resource/profiler/flops_0.txt
@@ -1,4 +1,4 @@
-op_full_name, FLOPs, FLOPS, FLOPS utilization
+full_kernel_name, FLOPs, FLOPS, FLOPS utilization
Default/Cast-op6, 333, 333, 33
Default/TransData-op7, 333, 333, 33
Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5, 333, 333, 33
diff --git a/tests/utils/resource/profiler/flops_1.txt b/tests/utils/resource/profiler/flops_1.txt
index fa6976759a79ae0cfba33494008b52079ae11902..7604dc55c88fa122130f2353753d2f81121fb159 100644
--- a/tests/utils/resource/profiler/flops_1.txt
+++ b/tests/utils/resource/profiler/flops_1.txt
@@ -1,4 +1,4 @@
-op_full_name, MFLOPs(10^6 cube), GFLOPS(10^9 cube), FLOPS utilization(cube), MFLOPs(10^6 vector), GFLOPS(10^9 vector), FLOPS utilization(vec)
+full_kernel_name, MFLOPs(10^6 cube), GFLOPS(10^9 cube), FLOPS utilization(cube), MFLOPs(10^6 vector), GFLOPS(10^9 vector), FLOPS utilization(vec)
Default/AtomicAddrClean-op104, 333, 333, 33, 333, 333, 33
Default/AtomicAddrClean-op105, 333, 333, 33, 333, 333, 33
Default/AtomicAddrClean-op106, 333, 333, 33, 333, 333, 33
diff --git a/tests/utils/resource/profiler/framework_raw_0.csv b/tests/utils/resource/profiler/framework_raw_0.csv
index 762bc693469eed4dbadca152674aa5498e6d6d0e..e3f87d88cd18f19d59f0bd6a1b8422ecb938f4cf 100755
--- a/tests/utils/resource/profiler/framework_raw_0.csv
+++ b/tests/utils/resource/profiler/framework_raw_0.csv
@@ -1,5 +1,5 @@
-task_id,stream_id,block_dim,full_op_name,op_name,op_type,subgraph,op_info
-51517,0,32,Default/Cast-op6,Cast-op6,Cast,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,3,224,224""}}"
-51518,0,32,Default/TransData-op7,TransData-op7,TransData,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,224,224,16""}}"
-51519,0,32,Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5,Cast-op5,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""49,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""49,4,16,16""}}"
-51522,0,4,Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28,Cast-op28,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""4,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""4,4,16,16""}}"
+task_id,stream_id,block_dim,full_kernel_name,op_name,kernel_name,kernel_type,subgraph,op_info
+51517,0,32,Default/Cast-op6,Default/Cast-op6,Cast-op6,Cast,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,3,224,224""}}"
+51518,0,32,Default/TransData-op7,Default/TransData-op7,TransData-op7,TransData,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,224,224,16""}}"
+51519,0,32,Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5,Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5,Cast-op5,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""49,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""49,4,16,16""}}"
+51522,0,4,Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28,Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28,Cast-op28,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""4,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""4,4,16,16""}}"
diff --git a/tests/utils/resource/profiler/framework_raw_1.csv b/tests/utils/resource/profiler/framework_raw_1.csv
index 5b60ecef49dc854a140531fa64c67a3df0521e34..f45ab9592b01aafe2a031564394bda3a1fc69118 100755
--- a/tests/utils/resource/profiler/framework_raw_1.csv
+++ b/tests/utils/resource/profiler/framework_raw_1.csv
@@ -1,11 +1,11 @@
-task_id,stream_id,block_dim,full_op_name,op_name,op_type,subgraph,op_info
-30290,0,1,Default/AtomicAddrClean-op104,AtomicAddrClean-op104,AtomicAddrClean,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": """"}}"
-30295,0,1,Default/AtomicAddrClean-op105,AtomicAddrClean-op105,AtomicAddrClean,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""10""}}"
-30300,0,1,Default/AtomicAddrClean-op106,AtomicAddrClean-op106,AtomicAddrClean,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""84""}}"
-30268,0,32,Default/Cast-op10,Cast-op10,Cast,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,1,32,32""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32""}}"
-30271,0,9,Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op12,Cast-op12,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""25,1,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""25,1,16,16""}}"
-30320,0,32,Gradients/Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/gradConv2D/Cast-op53,Cast-op53,Cast,Gradients,"{""input_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,1,28,28,16""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,28,28,16""}}"
-30269,0,32,Default/TransData-op11,TransData-op11,TransData,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32""}}"
-30308,0,32,Gradients/Default/network-WithLossCell/_backbone-LeNet5/gradReshape/TransData-op44,TransData-op44,TransData,Gradients,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,16,5,5""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,5,5,16""}}"
-30272,0,32,Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Conv2D-op13,Conv2D-op13,Conv2D,Default,"{""input_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32,16""}, ""input_1"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""25,1,16,16""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,28,28,16""}}"
-30286,0,1,Default/network-WithLossCell/_backbone-LeNet5/fc3-Dense/MatMul-op9,MatMul-op9,MatMul,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,120""}, ""input_1"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""84,120""}, ""input_2"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""84""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,84""}}"
+task_id,stream_id,block_dim,full_kernel_name,op_name,kernel_name,kernel_type,subgraph,op_info
+30290,0,1,Default/AtomicAddrClean-op104,Default/AtomicAddrClean-op104,AtomicAddrClean-op104,AtomicAddrClean,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": """"}}"
+30295,0,1,Default/AtomicAddrClean-op105,Default/AtomicAddrClean-op105,AtomicAddrClean-op105,AtomicAddrClean,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""10""}}"
+30300,0,1,Default/AtomicAddrClean-op106,Default/AtomicAddrClean-op106,AtomicAddrClean-op106,AtomicAddrClean,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""84""}}"
+30268,0,32,Default/Cast-op10,Default/Cast-op10,Cast-op10,Cast,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,1,32,32""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32""}}"
+30271,0,9,Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op12,Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op12,Cast-op12,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""25,1,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""25,1,16,16""}}"
+30320,0,32,Gradients/Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/gradConv2D/Cast-op53,Gradients/Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/gradConv2D/Cast-op53,Cast-op53,Cast,Gradients,"{""input_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,1,28,28,16""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,28,28,16""}}"
+30269,0,32,Default/TransData-op11,Default/TransData-op11,TransData-op11,TransData,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32""}}"
+30308,0,32,Gradients/Default/network-WithLossCell/_backbone-LeNet5/gradReshape/TransData-op44,Gradients/Default/network-WithLossCell/_backbone-LeNet5/gradReshape/TransData-op44,TransData-op44,TransData,Gradients,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,16,5,5""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,5,5,16""}}"
+30272,0,32,Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Conv2D-op13,Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Conv2D-op13,Conv2D-op13,Conv2D,Default,"{""input_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,32,32,16""}, ""input_1"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""25,1,16,16""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,28,28,16""}}"
+30286,0,1,Default/network-WithLossCell/_backbone-LeNet5/fc3-Dense/MatMul-op9,Default/network-WithLossCell/_backbone-LeNet5/fc3-Dense/MatMul-op9,MatMul-op9,MatMul,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,120""}, ""input_1"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""84,120""}, ""input_2"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""84""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,84""}}"
diff --git a/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_detail.csv b/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_detail.csv
index b122d096c8db046bfc1c3d5c9e852758d48041c5..5887db135bb56614c78743cc16e2f30e4d54dc2c 100644
--- a/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_detail.csv
+++ b/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_detail.csv
@@ -1,4 +1,4 @@
-full_op_name,execution_time,execution_frequency
+full_kernel_name,execution_time,execution_frequency
Default/GetNext-op6,5e-05,3
Default/StreamSend-op199,1e-05,3
Default/StreamRecv-op202,5e-05,3
diff --git a/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_type.csv b/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_type.csv
index ee6c55870bbf86619fb3c122a7939c142daf262d..9b462c12ee9db37fb093fb692826140eb5ecbbd7 100644
--- a/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_type.csv
+++ b/tests/utils/resource/run_1/normal_run/profiler/aicore_intermediate_1_type.csv
@@ -1,4 +1,4 @@
-op_type,total_time,execution_frequency,percent
+kernel_type,total_time,execution_frequency,percent
GetNext,0.00015,3,0.00
StreamSend,0.00003,3,0.00
StreamRecv,0.00015,3,0.00
diff --git a/tests/utils/resource/run_1/normal_run/profiler/flops_1.txt b/tests/utils/resource/run_1/normal_run/profiler/flops_1.txt
index b821434850800c6729e89be0edce3ef8671ba464..4e7c744f0fa7a3a617cd8e6e9d27c2898f0f2028 100644
--- a/tests/utils/resource/run_1/normal_run/profiler/flops_1.txt
+++ b/tests/utils/resource/run_1/normal_run/profiler/flops_1.txt
@@ -1,4 +1,4 @@
-op_full_name, FLOPs, FLOPS, FLOPS utilization
+full_kernel_name, FLOPs, FLOPS, FLOPS utilization
Default/AssignAdd-op414, 333, 333, 33
Default/network-TrainStepWrap/optimizer_d-Adam/Mul-op29, 333, 333, 33
Default/network-TrainStepWrap/optimizer_d-Adam/Assign-op30, 333, 333, 33
diff --git a/tests/utils/resource/run_1/normal_run/profiler/framework_raw_1.csv b/tests/utils/resource/run_1/normal_run/profiler/framework_raw_1.csv
index 92bbdd0b73ad8f8b5336958a4d915d58639cf1fa..fff14ef235bf31c8a4f00c4f53871badcc3bccc1 100644
--- a/tests/utils/resource/run_1/normal_run/profiler/framework_raw_1.csv
+++ b/tests/utils/resource/run_1/normal_run/profiler/framework_raw_1.csv
@@ -1,82 +1,82 @@
-task_id,stream_id,block_dim,full_op_name,op_name,op_type,subgraph,op_info,graph_id
-2,8,1,Default/InitDataSetQueue-op0,InitDataSetQueue-op0,InitDataSetQueue,Default,"{""input_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}, ""input_1"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}}",11
-2,8,1,Default/StreamSwitch-op198,StreamSwitch-op198,StreamSwitch,Default,"{""input_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}, ""input_1"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}}",11
-2,88,1,Default/GetNext-op6,GetNext-op6,GetNext,Default,"{""output_0"": {""format"": ""DEFAULT"", ""data_type"": ""FLOAT32"", ""shape"": [32, 1, 32, 32]}, ""output_1"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [32]}}",11
-4,88,1,Default/GetNext-op6,GetNext-op6,GetNext,Default,"{""output_0"": {""format"": ""DEFAULT"", ""data_type"": ""FLOAT32"", ""shape"": [32, 1, 32, 32]}, ""output_1"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [32]}}",11
-5,88,1,Default/StreamSend-op199,StreamSend-op199,StreamSend,Default,{},11
-2,90,1,Default/StreamSwitch-op200,StreamSwitch-op200,StreamSwitch,Default,"{""input_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}, ""input_1"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}}",11
-3,90,1,Default/EndGraph-op201,EndGraph-op201,EndGraph,Default,{},11
-3,78,1,Default/StreamRecv-op202,StreamRecv-op202,StreamRecv,Default,{},11
-4,78,1,Default/AssignAdd-op203,AssignAdd-op203,AssignAdd,Default,"{""input_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}, ""input_1"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}, ""output_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}}",11
-5,78,1,Default/StreamActive-op204,StreamActive-op204,StreamActive,Default,{},11
-2,72,1,Default/Profiling-op208,Profiling-op208,Profiling,Default,{},11
-3,72,1,Default/Profiling-op209,Profiling-op209,Profiling,Default,{},11
-4,72,32,Default/TransData-op114,TransData-op114,TransData,Default,"{""input_0"": {""format"": ""DEFAULT"", ""data_type"": ""FLOAT32"", ""shape"": [32, 1, 32, 32]}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT32"", ""shape"": [32, 1, 32, 32, 16]}}",11
-5,72,4,Default/TensorMove-op89,TensorMove-op89,TensorMove,Default,"{""input_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [32]}, ""output_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [32]}}",11
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+58,72,32,Gradients/Default/network-TrainOneStepCell/network-WithLossCell/_backbone-LeNet5/conv2-Conv2d/gradConv2D/Conv2DBackpropInputD-op83,Gradients/Default/network-TrainOneStepCell/network-WithLossCell/_backbone-LeNet5/conv2-Conv2d/gradConv2D/Conv2DBackpropInputD-op83,Conv2DBackpropInputD-op83,Conv2DBackpropInputD,Gradients,"{""input_0"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT16"", ""shape"": [32, 1, 10, 10, 16]}, ""input_1"": {""format"": ""FRAC_Z"", ""data_type"": ""FLOAT16"", ""shape"": [25, 1, 16, 16]}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT16"", ""shape"": [32, 1, 14, 14, 16]}}",11
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+60,72,32,Gradients/Default/network-TrainOneStepCell/network-WithLossCell/_backbone-LeNet5/conv2-Conv2d/gradConv2D/Conv2DBackpropFilterD-op86,Gradients/Default/network-TrainOneStepCell/network-WithLossCell/_backbone-LeNet5/conv2-Conv2d/gradConv2D/Conv2DBackpropFilterD-op86,Conv2DBackpropFilterD-op86,Conv2DBackpropFilterD,Gradients,"{""input_0"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT16"", ""shape"": [32, 1, 10, 10, 16]}, ""input_1"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT16"", ""shape"": [32, 1, 14, 14, 16]}, ""output_0"": {""format"": ""FRAC_Z"", ""data_type"": ""FLOAT32"", ""shape"": [25, 1, 16, 16]}}",11
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+63,72,32,Gradients/Default/network-TrainOneStepCell/network-WithLossCell/_backbone-LeNet5/max_pool2d-MaxPool2d/gradMaxPool/MaxPoolGradWithArgmax-op111,Gradients/Default/network-TrainOneStepCell/network-WithLossCell/_backbone-LeNet5/max_pool2d-MaxPool2d/gradMaxPool/MaxPoolGradWithArgmax-op111,MaxPoolGradWithArgmax-op111,MaxPoolGradWithArgmax,Gradients,"{""input_0"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT16"", ""shape"": [32, 1, 28, 28, 16]}, ""input_1"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT16"", ""shape"": [32, 1, 14, 14, 16]}, ""input_2"": {""format"": ""NC1HWC0"", ""data_type"": ""UINT16"", ""shape"": [32, 1, 4, 14, 16]}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""FLOAT16"", ""shape"": [32, 1, 28, 28, 16]}}",11
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+69,72,1,Default/Profiling-op210,Default/Profiling-op210,Profiling-op210,Profiling,Default,{},11
+70,72,1,Default/Profiling-op211,Default/Profiling-op211,Profiling-op211,Profiling,Default,{},11
+71,72,1,Default/AssignAdd-op206,Default/AssignAdd-op206,AssignAdd-op206,AssignAdd,Default,"{""input_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}, ""input_1"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}, ""output_0"": {""format"": ""DEFAULT"", ""data_type"": ""INT32"", ""shape"": [1]}}",11
+72,72,1,Default/StreamActive-op207,Default/StreamActive-op207,StreamActive-op207,StreamActive,Default,{},11
diff --git a/tests/utils/resource/run_2/normal_run/profiler/aicpu_intermediate_1.csv b/tests/utils/resource/run_2/normal_run/profiler/aicpu_intermediate_1.csv
index 490235810bfe9cda58d87cd269284bc514c18056..062d15837adeb6a205ca5bf420578a4fb70d9bb4 100644
--- a/tests/utils/resource/run_2/normal_run/profiler/aicpu_intermediate_1.csv
+++ b/tests/utils/resource/run_2/normal_run/profiler/aicpu_intermediate_1.csv
@@ -1,4 +1,4 @@
-serial_number,op_type,total_time,dispatch_time,execution_time,run_start,run_end
+serial_number,kernel_type,total_time,dispatch_time,execution_time,run_start,run_end
1,InitData,7.906,0.15,0.22,154901853050,154901853210
2,GetNext,0.888,0.132,0.22,154907895189,154907895707
3,EndOfSequence,0.282,0.078,0.22,154907896287,154907896335
{{$t('profiling.modelList')}}
-
+
{{$t('profiling.mergeModel')}}
+
+ {{$t('profiling.scopeName')}}
+
+
+
+
+
+
+
+ v-if="timelineInfoMsprof.noData">
![]()
@@ -632,8 +511,6 @@ limitations under the License.
-
-
{{$t("public.dataLoading")}}
{{$t("public.noData")}}