171 lines
6.9 KiB
Python
171 lines
6.9 KiB
Python
# Copyright 2022 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import os
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import sys
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import shutil
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from tests.security_utils import security_off_wrap
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import pytest
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def cleanup():
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data_path = os.path.join(os.getcwd(), "data")
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kernel_meta_path = os.path.join(os.getcwd(), "kernel_data")
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cache_path = os.path.join(os.getcwd(), "__pycache__")
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if os.path.exists(data_path):
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shutil.rmtree(data_path)
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if os.path.exists(kernel_meta_path):
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shutil.rmtree(kernel_meta_path)
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if os.path.exists(cache_path):
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shutil.rmtree(cache_path)
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class CheckProfilerFiles:
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def __init__(self, device_id, rank_id, profiler_path, device_target):
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"""Arges init."""
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self.device_id = device_id
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self.rank_id = rank_id
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self.profiler_path = profiler_path
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self.device_target = device_target
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if device_target == "Ascend":
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self._check_d_profiling_file()
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elif device_target == "GPU":
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self._check_gpu_profiling_file()
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else:
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self._check_cpu_profiling_file()
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def _check_gpu_profiling_file(self):
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"""Check gpu profiling file."""
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op_detail_file = self.profiler_path + f'gpu_op_detail_info_{self.device_id}.csv'
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op_type_file = self.profiler_path + f'gpu_op_type_info_{self.device_id}.csv'
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activity_file = self.profiler_path + f'gpu_activity_data_{self.device_id}.csv'
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timeline_file = self.profiler_path + f'gpu_timeline_display_{self.device_id}.json'
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getnext_file = self.profiler_path + f'minddata_getnext_profiling_{self.device_id}.txt'
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pipeline_file = self.profiler_path + f'minddata_pipeline_raw_{self.device_id}.csv'
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framework_file = self.profiler_path + f'gpu_framework_{self.device_id}.txt'
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gpu_profiler_files = (op_detail_file, op_type_file, activity_file,
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timeline_file, getnext_file, pipeline_file, framework_file)
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for file in gpu_profiler_files:
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assert os.path.isfile(file)
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def _check_d_profiling_file(self):
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"""Check Ascend profiling file."""
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aicore_file = self.profiler_path + f'aicore_intermediate_{self.rank_id}_detail.csv'
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step_trace_file = self.profiler_path + f'step_trace_raw_{self.rank_id}_detail_time.csv'
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timeline_file = self.profiler_path + f'ascend_timeline_display_{self.rank_id}.json'
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aicpu_file = self.profiler_path + f'aicpu_intermediate_{self.rank_id}.csv'
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minddata_pipeline_file = self.profiler_path + f'minddata_pipeline_raw_{self.rank_id}.csv'
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queue_profiling_file = self.profiler_path + f'device_queue_profiling_{self.rank_id}.txt'
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memory_file = self.profiler_path + f'memory_usage_{self.rank_id}.pb'
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d_profiler_files = (aicore_file, step_trace_file, timeline_file, aicpu_file,
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minddata_pipeline_file, queue_profiling_file, memory_file)
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for file in d_profiler_files:
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assert os.path.isfile(file)
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def _check_cpu_profiling_file(self):
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"""Check cpu profiling file."""
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op_detail_file = self.profiler_path + f'cpu_op_detail_info_{self.device_id}.csv'
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op_type_file = self.profiler_path + f'cpu_op_type_info_{self.device_id}.csv'
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timeline_file = self.profiler_path + f'cpu_op_execute_timestamp_{self.device_id}.txt'
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cpu_profiler_files = (op_detail_file, op_type_file, timeline_file)
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for file in cpu_profiler_files:
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assert os.path.isfile(file)
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class TestEnvEnableProfiler:
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profiler_path = os.path.join(os.getcwd(), f'data/profiler/')
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device_id = int(os.getenv('DEVICE_ID')) if os.getenv('DEVICE_ID') else 0
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rank_id = int(os.getenv('RANK_ID')) if os.getenv('RANK_ID') else 0
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@classmethod
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def setup_class(cls):
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"""Run begin all test case start."""
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cleanup()
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@staticmethod
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def teardown():
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"""Run after each test case end."""
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cleanup()
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@pytest.mark.level2
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@security_off_wrap
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def test_cpu_profiler(self):
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if sys.platform != 'linux':
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return
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status = os.system(
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"""export MS_PROFILER_OPTIONS='{"start":true}';
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python ./run_net.py --target=CPU --mode=0;
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"""
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)
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CheckProfilerFiles(self.device_id, self.rank_id, self.profiler_path, "CPU")
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assert status == 0
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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@security_off_wrap
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def test_gpu_profiler(self):
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root_status = os.system("whoami | grep root")
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cuda_status = os.system("nvcc -V | grep 'release 10'")
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if root_status and not cuda_status:
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return
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status = os.system(
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"""export MS_PROFILER_OPTIONS='{"start":true, "profile_memory":true, "sync_enable":true}';
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python ./run_net.py --target=GPU --mode=0;
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"""
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)
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CheckProfilerFiles(self.device_id, self.rank_id, self.profiler_path, "GPU")
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assert status == 0
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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@security_off_wrap
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def test_gpu_profiler_pynative(self):
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"""
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Feature: profiler support GPU pynative mode.
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Description: profiling l2 GPU pynative mode data, analyze performance issues.
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Expectation: No exception.
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"""
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root_status = os.system("whoami | grep root")
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cuda_status = os.system("nvcc -V | grep 'release 10'")
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if root_status and not cuda_status:
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return
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status = os.system(
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"""export MS_PROFILER_OPTIONS='{"start":true, "sync_enable":true}';
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python ./run_net.py --target=GPU --mode=1;
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"""
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)
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CheckProfilerFiles(self.device_id, self.rank_id, self.profiler_path, "GPU")
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assert status == 0
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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@security_off_wrap
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def test_ascend_profiler(self):
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status = os.system(
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"""export MS_PROFILER_OPTIONS='{"start":true, "profile_memory":true}';
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python ./run_net.py --target=Ascend --mode=0;
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"""
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)
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CheckProfilerFiles(self.device_id, self.rank_id, self.profiler_path, "Ascend")
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assert status == 0
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