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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # 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.
- # ============================================================================
- """
- Function:
- Test profiler to watch the performance of training.
- Usage:
- pytest tests/st/func/profiler
- """
- import os
- import pytest
-
- from mindinsight.profiler.analyser.minddata_analyser import MinddataAnalyser
- from mindinsight.profiler.analyser.analyser_factory import AnalyserFactory
-
- from .conftest import BASE_SUMMARY_DIR_RUN_2
-
-
- class TestMinddataAnalyser:
- """Test minddata analyser module."""
-
- @classmethod
- def setup_class(cls):
- """Generate parsed files."""
- cls.summary_dir = os.path.join(BASE_SUMMARY_DIR_RUN_2, 'normal_run')
- cls.profiler = os.path.join(cls.summary_dir, 'profiler')
-
- def setup_method(self):
- """Create analyser."""
- self._analyser = AnalyserFactory.instance().get_analyser(
- 'minddata', self.profiler, '1')
-
- @pytest.mark.level0
- @pytest.mark.env_single
- @pytest.mark.platform_x86_cpu
- @pytest.mark.platform_arm_ascend_training
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.platform_x86_ascend_training
- def test_analyse_queue_summary(self):
- """Test analysing the queue summary info."""
- expect_result = {
- "data_process": {"status": "normal"},
- "device_queue_info": {"summary": {"empty_batch_count": 1, "full_batch_count": 0, "total_batch": 1}},
- "device_queue_op": {"status": "normal"},
- "get_next": {"status": "normal"},
- "get_next_queue_info": {"summary": {"empty_batch_count": 0, "total_batch": 3}},
- "data_transmission": {"status": "normal"}
- }
-
- get_next_queue_info, _ = self._analyser.analyse_get_next_info(info_type="queue")
- device_queue_info, _ = self._analyser.analyse_device_queue_info(info_type="queue")
- result = MinddataAnalyser.analyse_queue_summary(get_next_queue_info, device_queue_info)
- assert expect_result == result
-
- @pytest.mark.level0
- @pytest.mark.env_single
- @pytest.mark.platform_x86_cpu
- @pytest.mark.platform_arm_ascend_training
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.platform_x86_ascend_training
- def test_analyse_get_next_info(self):
- """Test analysing the get_next operation info for info_type="time" """
- expect_result = {
- "info": {"get_next": [0.001, 0, 0.001]},
- "size": 3,
- "summary": {"time_summary": {"avg_cost": "0.0006666666666666666"}}
- }
-
- time_info = {
- "size": 0,
- "info": [],
- "summary": {"time_summary": {}},
- "advise": {}
- }
-
- _, time_info = self._analyser.analyse_get_next_info(info_type="time")
- assert expect_result == time_info
-
- @pytest.mark.level0
- @pytest.mark.env_single
- @pytest.mark.platform_x86_cpu
- @pytest.mark.platform_arm_ascend_training
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.platform_x86_ascend_training
- def test_analyse_device_queue_info(self):
- """Test analysing the device_queue operation info for info_type="time" """
- expect_result = {
- "info": {"total_cost": [4], "push_cost": [4], "get_cost": [0]},
- "size": 1,
- "summary": {"time_summary": {"avg_cost": 4, "get_cost": 0, "push_cost": 4}}
- }
-
- time_info = {
- "size": 0,
- "info": [],
- "summary": {"time_summary": {}},
- "advise": {}
- }
-
- _, time_info = self._analyser.analyse_device_queue_info(info_type="time")
- assert expect_result == time_info
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