# 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.analyser_factory import AnalyserFactory from tests.st.func.profiler.conftest import BASE_SUMMARY_DIR class TestMinddataPipelineAnalyser: """Test minddata pipeline analyser module.""" JOB_ID = 'JOB3' @classmethod def setup_class(cls): """Generate parsed files.""" cls.summary_dir = os.path.join(BASE_SUMMARY_DIR, 'normal_run') cls.profiler = os.path.join(cls.summary_dir, 'profiler') def setup_method(self): """Create analyser.""" self._analyser = AnalyserFactory.instance().get_analyser( 'minddata_pipeline', 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_query(self): """Test the function of querying minddata pipeline infomation.""" expect_result = { 'col_name': [ 'op_id', 'op_type', 'output_queue_average_size', 'output_queue_length', 'output_queue_usage_rate', 'sample_interval', 'parent_id', 'children_id' ], 'object': [ [1, 'Shuffle', 20.0, 64, 0.3125, 10, 0, [2, 3]], [2, 'TFReader', 20.0, 64, 0.3125, 10, 1, None], [3, 'TFReader', 20.0, 64, 0.3125, 10, 1, None], [0, 'Batch', None, None, None, 10, None, [1]] ], 'size': 4 } condition = { 'sort_condition': { 'name': 'output_queue_average_size', 'type': 'descending' } } result = self._analyser.query(condition) 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_get_op_and_parent_op_info(self): """Test the function of the target operator and queue infomation.""" expect_result = { 'current_op': { 'op_id': 1, 'op_type': 'Shuffle', 'num_workers': 1 }, 'parent_op': { 'op_id': 0, 'op_type': 'Batch', 'num_workers': 4 }, 'queue_info': { 'output_queue_size': [10, 20, 30], 'output_queue_average_size': 20.0, 'output_queue_length': 64, 'output_queue_usage_rate': 0.3125, 'sample_interval': 10 } } result = self._analyser.get_op_and_parent_op_info(1) assert expect_result == result