# 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. # ============================================================================ """ Fuction: 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}}, "tdt": {"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