diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore b/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore
index 75bc12db6361869d36e80447322dde9292c0c761..70f4e767811d0d93c25fbb8ce2d2b29c4ba3b6e6 100644
--- a/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/.gitignore
@@ -5,4 +5,7 @@ dist/
build/
tb_graph_ascend.egg-info/
__pycache__/
-/server/static/index.html
\ No newline at end of file
+/server/static/index.html
+report.html
+assets/
+/htmlcov/
\ No newline at end of file
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts
index a908f6ac61a671a71c83861727da0716dd64aad3..e7b12acc2f07454f9e89296800512186e0a93414 100644
--- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph-scene.ts
@@ -306,6 +306,7 @@ class TfGraphScene2 extends LegacyElementMixin(DarkModeMixin(PolymerElement)) im
},
tb_debug.GraphDebugEventId.RENDER_SCENE_BUILD_SCENE,
);
+ console.log('tf-graph-scene: built scene====', renderHierarchy);
// Update the minimap again when the graph is done animating.
setTimeout((): void => {
this.minimap.update();
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts
index e16376056d37364161451c01e45a80d8effdf472..3eafa25502f9094c4b639989e6e532f897f854e7 100644
--- a/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/fe/src/tf_graph/tf-graph.ts
@@ -28,6 +28,7 @@ import * as tf_graph_render from '../tf_graph_common/render';
import * as tf_graph_util from '../tf_graph_common/util';
import * as tf_graph_layout from '../tf_graph_common/layout';
import './tf-graph-scene';
+import '../main_graph/index'
import './components/legend/index';
import type { MinimapVis, Selection } from '../tf_graph_controls/tf-graph-controls';
import { fetchPbTxt, parseGraphPbTxt } from '../tf_graph_common/parser';
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py
index a61154c3ea813656a84f51ad8044d07025aea004..9517d252ca206722497d27ad10c2a4f9bd3c5222 100644
--- a/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/app/controllers/match_nodes_controller.py
@@ -38,10 +38,12 @@ class MatchNodesController:
# 在原始数据上，添加匹配节点，和匹配节点信息
npu_node_data['matched_node_link'] = [bench_node_name]
bench_node_data['matched_node_link'] = [npu_node_name]
- npu_node_data['data']['precision_index'] = precision_error
+ # 防止 KeyError 或 TypeError
+ npu_node_data.setdefault('data', {})['precision_index'] = precision_error
# 后端维护一个匹配节点列表，前端展示
npu_match_nodes_list[npu_node_name] = bench_node_name
bench_match_nodes_list[bench_node_name] = npu_node_name
+
graph_data['npu_match_nodes'] = npu_match_nodes_list
graph_data['bench_match_nodes'] = bench_match_nodes_list
return {
@@ -81,8 +83,8 @@ class MatchNodesController:
def process_summary_task_add(graph_data, npu_node_name, bench_node_name):
npu_match_nodes_list = graph_data.get('npu_match_nodes', {})
bench_match_nodes_list = graph_data.get('bench_match_nodes', {})
- npu_node_data = graph_data.get('NPU', {}).get('node', {}).get(npu_node_name, {})
- bench_node_data = graph_data.get('Bench', {}).get('node', {}).get(bench_node_name, {})
+ npu_node_data = graph_data.get('NPU', {}).get('node', {}).get(npu_node_name)
+ bench_node_data = graph_data.get('Bench', {}).get('node', {}).get(bench_node_name)
# 计算统计误差
intput_statistical_diff = MatchNodesController.calculate_statistical_diff(
npu_node_data.get('input_data'), bench_node_data.get('input_data'), npu_node_name, bench_node_name
@@ -109,7 +111,8 @@ class MatchNodesController:
bench_node_data['matched_node_link'] = [npu_node_name]
MatchNodesController.update_graph_node_data(npu_node_data.get('input_data'), intput_statistical_diff)
MatchNodesController.update_graph_node_data(npu_node_data.get('output_data'), output_statistical_diff)
- npu_node_data['data']['precision_index'] = precision_error
+ # 防止 KeyError 或 TypeError
+ npu_node_data.setdefault('data', {})['precision_index'] = precision_error
# 后端维护一个匹配节点列表，前端展示
npu_match_nodes_list[npu_node_name] = bench_node_name
bench_match_nodes_list[bench_node_name] = npu_node_name
@@ -138,7 +141,8 @@ class MatchNodesController:
MatchNodesController.delete_matched_node_data(npu_node_data.get('output_data'))
# 后端维护一个匹配节点列表，前端展示
try:
- del npu_node_data['data']['precision_index']
+ # 防止 KeyError 或 TypeError
+ npu_node_data.get('data', {}).pop('precision_index', None)
del npu_match_nodes_list[npu_node_name]
del bench_match_nodes_list[bench_node_name]
except KeyError:
@@ -219,6 +223,8 @@ class MatchNodesController:
@staticmethod
def calculate_md5_diff(npu_data, bench_data):
+ if npu_data == {} or bench_data == {}:
+ return 0
# 对比每个NPU和Bench所有数据md值，如果有一个不一样则返回0,否则返回1
for npu_key, bench_key in zip(npu_data, npu_data):
npu_md5 = npu_data[npu_key].get('md5', '')
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py
index ab9f5d3dacec68bc5c1f22133ab6217a728486b6..aefd06137b23cef484ec86967c1398dabc11aa4a 100644
--- a/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/server/plugin.py
@@ -354,7 +354,6 @@ class GraphsPlugin(base_plugin.TBPlugin):
if json_data.get('StepList', {}) and 'ALL' not in json_data.get('StepList', {}):
json_data['StepList'].insert(0, 'ALL')
all_node_names = self.get_all_node_names(json_data, request)
-
# 读取第一个文件中的Colors和OverflowCheck
first_run_tag = get_global_value("first_run_tag")
first_file_data, _ = GraphUtils.safe_load_data(run, first_run_tag)
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/conftest.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/conftest.py
new file mode 100644
index 0000000000000000000000000000000000000000..894f9ce662475b507aaaf5042c412bc4c8aae8ec
--- /dev/null
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/conftest.py
@@ -0,0 +1,62 @@
+import pytest
+import json
+import os
+from pathlib import Path
+
+
+def load_st_test_cases():
+ meta_path = Path(__file__).parent / "data/metadata_st.json"
+ with open(meta_path) as f:
+ return json.load(f)["test_cases"]
+
+
+def load_ut_test_cases():
+ meta_path = Path(__file__).parent / "data/metadata_ut.json"
+ with open(meta_path) as f:
+ return json.load(f)["test_cases"]
+
+
+# 动态生成测试用例
+def pytest_generate_tests(metafunc):
+ if "meta_data" in metafunc.fixturenames and "operation" in metafunc.fixturenames:
+ ut_test_cases = load_st_test_cases()
+ params = []
+ for case in ut_test_cases:
+ metaData = case["meta_data"]
+ metaData["run"] = Path(__file__).parent / metaData["run"]
+ for op in case["operations"]:
+ params.append(pytest.param(
+ metaData,
+ op,
+ id=f"{metaData['run']}-{op['type']}"
+ ))
+ # 确保参数名称与参数值数量一致
+ metafunc.parametrize("meta_data, operation", params)
+ if "ut_test_case" in metafunc.fixturenames:
+ ut_test_cases = load_ut_test_cases()
+ params = []
+ for case in ut_test_cases:
+ params.append(pytest.param(
+ case,
+ id=f"{case['type']}-{case['name']}"
+ ))
+ # 确保参数名称与参数值数量一致
+ metafunc.parametrize("ut_test_case", params)
+
+
+@pytest.fixture
+def meta_data(meta_data):
+ # 返回当前测试的操作配置
+ return meta_data
+
+
+@pytest.fixture
+def operation_config(operation):
+ # 返回当前测试的操作配置
+ return operation
+
+
+@pytest.fixture
+def ut_test_case(ut_test_case):
+ # 返回当前测试的操作配置
+ return ut_test_case
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/data/compare_statis.vis b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/compare_statis.vis
new file mode 100644
index 0000000000000000000000000000000000000000..5820af6ac01e2a20d36dd6921da9c82b8fd43513
--- /dev/null
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/compare_statis.vis
@@ -0,0 +1,948 @@
+{
+ "ToolTip": "{\"shape\": \"\\u6570\"}",
+ "NPU": {
+ "edge": [],
+ "node": {
+ "AddOne_0": {
+ "matched_node_link": [
+ "AddOne_0"
+ ],
+ "data": {
+ "precision_index": 0.0
+ },
+ "id": "AddOne_0",
+ "inputs": [],
+ "input_data": {
+ "AddOne_0.input_arg.0": {
+ "type": "torch.Tensor",
+ "dtype": "",
+ "shape": [
+ 32,
+ 512,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406",
+ "MaxAbsErr": 0.0,
+ "MinAbsErr": 0.0,
+ "MeanAbsErr": 0.0,
+ "NormAbsErr": 0.0,
+ "MaxRelativeErr": "0.0000%",
+ "MinRelativeErr": "0.0000%",
+ "MeanRelativeErr": "0.0000%",
+ "NormRelativeErr": "0.0000%"
+ },
+ "AddOne_0.input_arg.1": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 64,
+ 256,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406",
+ "MaxAbsErr": 0.0,
+ "MinAbsErr": 0.0,
+ "MeanAbsErr": 0.0,
+ "NormAbsErr": 0.0,
+ "MaxRelativeErr": "0.0000%",
+ "MinRelativeErr": "0.0000%",
+ "MeanRelativeErr": "0.0000%",
+ "NormRelativeErr": "0.0000%"
+ },
+ "AddOne_0.1": {},
+ "AddOne_0.2": {}
+ },
+ "output_data": {
+ "AddOne_0.output_arg.0": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 32,
+ 512,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406",
+ "MaxAbsErr": 0.0,
+ "MinAbsErr": 0.0,
+ "MeanAbsErr": 0.0,
+ "NormAbsErr": 0.0,
+ "MaxRelativeErr": "0.0000%",
+ "MinRelativeErr": "0.0000%",
+ "MeanRelativeErr": "0.0000%",
+ "NormRelativeErr": "0.0000%"
+ },
+ "AddOne_0.output_arg.1": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 64,
+ 256,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406",
+ "MaxAbsErr": 0.0,
+ "MinAbsErr": 0.0,
+ "MeanAbsErr": 0.0,
+ "NormAbsErr": 0.0,
+ "MaxRelativeErr": "0.0000%",
+ "MinRelativeErr": "0.0000%",
+ "MeanRelativeErr": "0.0000%",
+ "NormRelativeErr": "0.0000%"
+ },
+ "AddOne_0.1": {},
+ "AddOne_0.2": {}
+ },
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "pair": "None",
+ "subnodes": [
+ "Test.add_0_withlonglonglonglonglonglonglonglongname.tt.ee",
+ "add_51111"
+ ],
+ "type": "AddOne",
+ "upnode": "Test.maxpoolMaxPool2.maxpoolpo.tt.ee"
+ },
+ "AddOne_1": {
+ "matched_node_link": [],
+ "data": {
+ "precision_index": 0.8
+ },
+ "id": "AddOne_1",
+ "inputs": [],
+ "input_data": {
+ "Test.maxpoolMaxPool2.maxpoolpo.tt.ee.input_arg.0": {
+ "data_name": "-10",
+ "longlonglonglonglonglongName": "hah",
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": "[32, 512, 2, 2]",
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406",
+ "error_key": [
+ "type",
+ "shape"
+ ]
+ },
+ "Test.maxpoolMaxPool2.maxpoolpo.tt.ee.kwrag_arg.1": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 64,
+ 256,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406"
+ }
+ },
+ "is_forward": true,
+ "node_type": 9,
+ "outputs": [],
+ "output_data": {},
+ "pair": "None",
+ "subnodes": [
+ "add_1",
+ "add_4"
+ ],
+ "type": "AddOne",
+ "upnode": "Test.maxpoolMaxPool2.maxpoolpo.tt.ee"
+ },
+ "Test.AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.tt.ee": {
+ "matched_node_link": [],
+ "data": {
+ "precision_index": 0
+ },
+ "id": "Test.AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.tt.ee",
+ "inputs": [],
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "output_data": {},
+ "pair": "None",
+ "subnodes": [
+ "add_2"
+ ],
+ "type": "AddOne",
+ "upnode": "AddThree_0",
+ "micro_step_id": "3"
+ },
+ "AddThree_0": {
+ "matched_node_link": [
+ "B___AddThree_0"
+ ],
+ "data": {
+ "precision_index": 0.5
+ },
+ "id": "AddThree_0",
+ "input_data": {},
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "output_data": {},
+ "pair": "None",
+ "subnodes": [
+ "arg0_1_0",
+ "Test.maxpoolMaxPool2.maxpoolpo.tt.ee",
+ "Test.AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.tt.ee",
+ "output_0"
+ ],
+ "type": "AddThree",
+ "upnode": "None"
+ },
+ "Test.maxpoolMaxPool2.maxpoolpo.tt.ee": {
+ "matched_node_link": [
+ "B___Test.maxpoolMaxPool2.maxpoolpo.tt.ee"
+ ],
+ "data": {
+ "precision_status": false,
+ "Host Self Duration(us)": 56.24,
+ "Host Total Duration(us)": 56.24,
+ "Device Self Duration(us)": 0,
+ "Device Total Duration(us)": 0,
+ "overflow_level": "medium"
+ },
+ "id": "Test.maxpoolMaxPool2.maxpoolpo.tt.ee",
+ "inputs": [],
+ "input_data": {
+ "Test.maxpoolMaxPool2.maxpoolpo.tt.ee.input_arg.0": {
+ "data_name": "-10",
+ "longlonglonglonglonglongName": "hah",
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": "[32, 512, 2, 2]",
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406",
+ "error_key": [
+ "type",
+ "shape"
+ ]
+ },
+ "Test.maxpoolMaxPool2.maxpoolpo.tt.ee.kwrag_arg.1": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 64,
+ 256,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406"
+ }
+ },
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "output_data": {
+ "output.0": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 128,
+ 512,
+ 2,
+ 2
+ ],
+ "Max": "538.2343242",
+ "Min": "-234.124124234",
+ "Mean": "-510.23432654",
+ "Norm": "3555.3406"
+ },
+ "output.1": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 16,
+ 256,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406"
+ }
+ },
+ "pair": "None",
+ "subnodes": [
+ "AddOne_0",
+ "AddOne_1"
+ ],
+ "suggestions": {
+ "text": "test ptdbg工具 with longlong tenm tensldjta te alsejtka gaew jtljae tet jsdklfj.",
+ "ptdbg工具": "https://gitee.com/ascend/att/tree/master/debug/accuracy_tools/ptdbg_ascend"
+ },
+ "stack_info": [
+ "File /home/w3000/xxxx/subnodes/sdd/adad/srit-sda/artar/prased, line 136. om het, \n dada = rtens/sda.ddd(asdw)",
+ "File /home/w3000/xxxx/subnodes/sdd/adad/srit-sda/artar/prased, line 136. om het, \n dada = rtens/sda.ddd(asdw)",
+ "File /home/w3000/xxxx/subnodes/sdd/adad/srit-sda/artar/prased, line 136. om het, \n dada = rtens/sda.ddd(asdw)"
+ ],
+ "type": "AddTwo",
+ "upnode": "AddThree_0",
+ "micro_step_id": "0"
+ },
+ "Test.add_0_withlonglonglonglonglonglonglonglongname.tt.ee": {
+ "matched_node_link": [
+ "B___AddThree_0",
+ "B___Test.maxpoolMaxPool2.maxpoolpo.tt.ee",
+ "B___AddOne_0",
+ "B___Test.add_0_withlonglonglonglonglonglonglonglongname.tt.ee"
+ ],
+ "data": {
+ "precision_index": 0.35
+ },
+ "id": "Test.add_0_withlonglonglonglonglonglonglonglongname.tt.ee",
+ "inputs": [],
+ "input_data": {
+ "input_arg.0": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 32,
+ 512,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406"
+ },
+ "input_arg.1": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 64,
+ 256,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406"
+ },
+ "input_arg.2": "None"
+ },
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "output_data": {
+ "output.0": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 128,
+ 512,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406"
+ },
+ "output.1": {
+ "type": "torch.Tensor",
+ "dtype": "torch.float32",
+ "shape": [
+ 16,
+ 256,
+ 2,
+ 2
+ ],
+ "Max": "5348.2343242",
+ "Min": "-2344.124124234",
+ "Mean": "-51.23432654",
+ "Norm": "355555.3406"
+ }
+ },
+ "pair": "None",
+ "subnodes": [],
+ "type": "addlongtingmelasidngkonklajelkjsakljgskadtest",
+ "upnode": "AddOne_0"
+ },
+ "add_51111": {
+ "matched_node_link": [],
+ "data": {
+ "precision_status": true,
+ "precision_index": 1,
+ "md5 Compare Result": "Pass"
+ },
+ "id": "add_51111",
+ "inputs": [],
+ "input_data": {},
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "output_data": {},
+ "pair": "None",
+ "subnodes": [],
+ "type": "add",
+ "upnode": "AddOne_0"
+ },
+ "add_1": {
+ "matched_node_link": [],
+ "data": {
+ "precision_status": false,
+ "precision_index": 0,
+ "md5 Compare Result": "Pass"
+ },
+ "id": "add_1",
+ "inputs": [],
+ "input_data": {},
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "output_data": {},
+ "pair": "None",
+ "subnodes": [],
+ "type": "add",
+ "upnode": "AddOne_1"
+ },
+ "add_4": {
+ "matched_node_link": [],
+ "data": {},
+ "id": "add_4",
+ "inputs": [],
+ "input_data": {},
+ "is_forward": true,
+ "node_type": 0,
+ "outputs": [],
+ "output_data": {},
+ "pair": "None",
+ "subnodes": [],
+ "type": "add",
+ "upnode": "AddOne_1"
+ },
+ "add_2": {
+ "matched_node_link": [],
+ "data": {},
+ "id": "add_2",
+ "inputs": [],
+ "input_data": {
+ "add_2.input_arg.0": {
+ "longlonglonglonglonglongName": "hah",
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+}
\ No newline at end of file
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/data/metadata_st.json b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/metadata_st.json
new file mode 100644
index 0000000000000000000000000000000000000000..820e11cc39b7c4ed4111690970d2714a82bf1899
--- /dev/null
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/metadata_st.json
@@ -0,0 +1,237 @@
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+ "data": {}
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+ },
+ {
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+ "data": {
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+ "data": {
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+ "bench_match_nodes": {
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+ }
+ }
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+ }
+ ]
+}
\ No newline at end of file
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/data/metadata_ut.json b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/metadata_ut.json
new file mode 100644
index 0000000000000000000000000000000000000000..025fbd14c5fdf5307928ffe4bf3ebd0f102c36f9
--- /dev/null
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/data/metadata_ut.json
@@ -0,0 +1,174 @@
+{
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+ {
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+ "node": {
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+ }
+ }
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+ }
+ },
+ "npu_node_name": "npu_conv2d",
+ "bench_node_name": "bench_conv2d"
+ },
+ "expected": {
+ "success": true,
+ "data": {
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+ }
+ }
+ },
+ {
+ "name": "md5_partial_mismatch_failure",
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+ "input": {
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+ "NPU": {
+ "node": {
+ "npu_conv2d": {
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+ "npu_conv2d.data1": {
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+ "npu_conv2d.data2": {
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+ "md5": "a1b2c3"
+ },
+ "bench_conv2d.data2": {
+ "md5": "d4e5f6"
+ }
+ }
+ }
+ }
+ }
+ },
+ "npu_node_name": "npu_conv2d",
+ "bench_node_name": "bench_conv2d"
+ },
+ "expected": {
+ "success": true,
+ "data": {
+ "precision_error": 0
+ }
+ }
+ },
+ {
+ "name": "delete_existing_node_success",
+ "type": "process_md5_task_delete",
+ "input": {
+ "graph_data": {
+ "npu_match_nodes": {
+ "npu_conv2d": "bench_conv2d"
+ },
+ "bench_match_nodes": {
+ "bench_conv2d": "npu_conv2d"
+ },
+ "NPU": {
+ "node": {
+ "npu_conv2d": {
+ "data": {
+ "precision_index": 1
+ },
+ "matched_node_link": [
+ "bench_conv2d"
+ ]
+ }
+ }
+ }
+ },
+ "npu_node_name": "npu_conv2d",
+ "bench_node_name": "bench_conv2d"
+ },
+ "expected": {
+ "success": true,
+ "data": {}
+ }
+ },
+ {
+ "name": "delete_non_existent_node_failure",
+ "type": "process_md5_task_delete",
+ "input": {
+ "graph_data": {
+ "NPU": {
+ "node": {
+ "npu_conv2d": {}
+ }
+ }
+ },
+ "npu_node_name": "npu_conv2d",
+ "bench_node_name": "bench_conv2d"
+ },
+ "expected": {
+ "success": false,
+ "error": "操作失败：删除节点信息失败"
+ }
+ },
+ {
+ "name": "missing_input_data_handling",
+ "type": "process_md5_task_add",
+ "input": {
+ "graph_data": {
+ "NPU": {
+ "node": {
+ "npu_conv2d": {}
+ }
+ }
+ },
+ "npu_node_name": "npu_conv2d",
+ "bench_node_name": "bench_conv2d"
+ },
+ "expected": {
+ "success": true,
+ "data": {
+ "precision_error": 0
+ }
+ }
+ }
+ ]
+}
\ No newline at end of file
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/integration/service/test_graph_service.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/integration/service/test_graph_service.py
new file mode 100644
index 0000000000000000000000000000000000000000..35e3883ac5c3f33a69cc6c6e57899f4dbce67215
--- /dev/null
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/integration/service/test_graph_service.py
@@ -0,0 +1,42 @@
+import pytest
+from server.app.service.graph_service import GraphService
+
+
+class TestMatchNodesService:
+
+ def test_service(self, meta_data, operation_config):
+ op_type = operation_config["type"]
+ expected = operation_config["expected"]
+ # 执行操作
+ try:
+ if op_type == "get_node_info":
+ result = GraphService.get_node_info(
+ node_info=operation_config["node_info"],
+ meta_data=meta_data
+ )
+ elif op_type == "add_match_nodes":
+ result = GraphService.add_match_nodes(
+ npu_node_name=operation_config["npu_node_name"],
+ bench_node_name=operation_config["bench_node_name"],
+ meta_data=meta_data
+ )
+ elif op_type == "delete_match_nodes":
+ result = GraphService.delete_match_nodes(
+ npu_node_name=operation_config["npu_node_name"],
+ bench_node_name=operation_config["bench_node_name"],
+ meta_data=meta_data
+ )
+ elif op_type == "get_matched_state_list":
+ result = GraphService.get_matched_state_list(
+ meta_data=meta_data
+ )
+ elif op_type == "save_data":
+ result = GraphService.save_data(
+ meta_data=meta_data
+ )
+ except Exception as e:
+ result = {"error": type(e).__name__}
+
+ # 验证结果
+ assert result == expected, \
+ f"Operation {op_type} failed on {operation_config}"
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/pytest.ini b/plugins/tensorboard-plugins/tb_graph_ascend/test/pytest.ini
new file mode 100644
index 0000000000000000000000000000000000000000..ddb991b93410d7fb17d45cfe3d1e74a9a9b92e3a
--- /dev/null
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/pytest.ini
@@ -0,0 +1,9 @@
+[pytest]
+testpaths = tests
+python_files = test_*.py
+norecursedirs = .* venv build dist
+addopts = -v --strict-markers
+log_cli = true
+log_level = DEBUG
+markers =
+ slow: marks tests as slow (deselect with -m 'not slow')
\ No newline at end of file
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/units/controllers/test_match_nodes_controller.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/units/controllers/test_match_nodes_controller.py
new file mode 100644
index 0000000000000000000000000000000000000000..f0ac568d821d436efc27f29a58c9d8131cb4ab44
--- /dev/null
+++ b/plugins/tensorboard-plugins/tb_graph_ascend/test/units/controllers/test_match_nodes_controller.py
@@ -0,0 +1,72 @@
+import pytest
+from server.app.controllers.match_nodes_controller import MatchNodesController
+from server.app.utils.graph_utils import GraphUtils
+
+
+class TestMatchNodesController:
+
+ def test_match_node_controller(self, ut_test_case):
+ op_type = ut_test_case.get("type")
+ input = ut_test_case.get('input')
+ expected = ut_test_case.get("expected")
+ # 执行操作
+ try:
+ if op_type == "process_md5_task_add":
+ result = MatchNodesController.process_md5_task_add(
+ graph_data=input.get("graph_data"),
+ npu_node_name=input.get("npu_node_name"),
+ bench_node_name=input.get("bench_node_name"),
+ )
+ elif op_type == "process_md5_task_delete":
+ result = MatchNodesController.process_md5_task_delete(
+ graph_data=input.get("graph_data"),
+ npu_node_name=input.get("npu_node_name"),
+ bench_node_name=input.get("bench_node_name"),
+ )
+ elif op_type == "process_summary_task_add":
+
+ result = MatchNodesController.process_summary_task_add(
+ graph_data=input.get("graph_data"),
+ npu_node_name=input.get("npu_node_name"),
+ bench_node_name=input.get("bench_node_name"),
+ )
+ elif op_type == "process_summary_task_delete":
+ result = MatchNodesController.process_summary_task_delete(
+ npu_data=input.get("npu_data"),
+ bench_data=input.get("bench_data"),
+ npu_node_name=input.get("npu_node_name"),
+ bench_node_name=input.get("bench_node_name"),
+ )
+ elif op_type == "calculate_statistical_diff":
+ result = MatchNodesController.calculate_statistical_diff(
+ npu_data=input.get("npu_data"),
+ bench_data=input.get("bench_data"),
+ npu_node_name=input.get("npu_node_name"),
+ bench_node_name=input.get("bench_node_name"),
+ )
+ elif op_type == "calculate_max_relative_error":
+ result = MatchNodesController.calculate_max_relative_error(
+ result=input.get("result"),
+ )
+ elif op_type == "calculate_md5_diff":
+ result = MatchNodesController.calculate_md5_diff(
+ npu_data=input.get("npu_data"),
+ bench_data=input.get("bench_data"),
+ )
+ elif op_type == "update_graph_node_data":
+ result = MatchNodesController.update_graph_node_data(
+ graph_npu_node_data=input.get("graph_npu_node_data"),
+ statistical_diff=input.get("statistical_diff"),
+ )
+ elif op_type == "delete_matched_node_data":
+ result = MatchNodesController.delete_matched_node_data(
+ graph_npu_node_data=input.get("graph_npu_node_data"),
+ )
+ else:
+ return
+ except Exception as e:
+ result = {"error": type(e).__name__}
+
+ # 验证结果
+ assert result == expected, \
+ f"Operation {op_type} failed on {ut_test_case}"
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/units/test_plugin.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/units/test_plugin.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/plugins/tensorboard-plugins/tb_graph_ascend/test/units/utils/test_graph_utils.py b/plugins/tensorboard-plugins/tb_graph_ascend/test/units/utils/test_graph_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391