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111 lines
4.3 KiB
111 lines
4.3 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve. |
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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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import sys |
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import paddle |
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# A global variable to record the number of calling times for profiler |
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# functions. It is used to specify the tracing range of training steps. |
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_profiler_step_id = 0 |
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# A global variable to avoid parsing from string every time. |
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_profiler_options = None |
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class ProfilerOptions(object): |
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''' |
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Use a string to initialize a ProfilerOptions. |
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The string should be in the format: "key1=value1;key2=value;key3=value3". |
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For example: |
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"profile_path=model.profile" |
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"batch_range=[50, 60]; profile_path=model.profile" |
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"batch_range=[50, 60]; tracer_option=OpDetail; profile_path=model.profile" |
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ProfilerOptions supports following key-value pair: |
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batch_range - a integer list, e.g. [100, 110]. |
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state - a string, the optional values are 'CPU', 'GPU' or 'All'. |
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sorted_key - a string, the optional values are 'calls', 'total', |
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'max', 'min' or 'ave. |
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tracer_option - a string, the optional values are 'Default', 'OpDetail', |
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'AllOpDetail'. |
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profile_path - a string, the path to save the serialized profile data, |
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which can be used to generate a timeline. |
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exit_on_finished - a boolean. |
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''' |
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def __init__(self, options_str): |
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assert isinstance(options_str, str) |
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self._options = { |
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'batch_range': [10, 20], |
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'state': 'All', |
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'sorted_key': 'total', |
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'tracer_option': 'Default', |
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'profile_path': '/tmp/profile', |
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'exit_on_finished': True |
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} |
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self._parse_from_string(options_str) |
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def _parse_from_string(self, options_str): |
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for kv in options_str.replace(' ', '').split(';'): |
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key, value = kv.split('=') |
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if key == 'batch_range': |
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value_list = value.replace('[', '').replace(']', '').split(',') |
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value_list = list(map(int, value_list)) |
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if len(value_list) >= 2 and value_list[0] >= 0 and value_list[ |
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1] > value_list[0]: |
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self._options[key] = value_list |
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elif key == 'exit_on_finished': |
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self._options[key] = value.lower() in ("yes", "true", "t", "1") |
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elif key in [ |
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'state', 'sorted_key', 'tracer_option', 'profile_path' |
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]: |
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self._options[key] = value |
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def __getitem__(self, name): |
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if self._options.get(name, None) is None: |
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raise ValueError( |
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"ProfilerOptions does not have an option named %s." % name) |
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return self._options[name] |
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def add_profiler_step(options_str=None): |
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''' |
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Enable the operator-level timing using PaddlePaddle's profiler. |
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The profiler uses a independent variable to count the profiler steps. |
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One call of this function is treated as a profiler step. |
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Args: |
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profiler_options - a string to initialize the ProfilerOptions. |
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Default is None, and the profiler is disabled. |
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''' |
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if options_str is None: |
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return |
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global _profiler_step_id |
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global _profiler_options |
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if _profiler_options is None: |
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_profiler_options = ProfilerOptions(options_str) |
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if _profiler_step_id == _profiler_options['batch_range'][0]: |
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paddle.utils.profiler.start_profiler(_profiler_options['state'], |
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_profiler_options['tracer_option']) |
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elif _profiler_step_id == _profiler_options['batch_range'][1]: |
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paddle.utils.profiler.stop_profiler(_profiler_options['sorted_key'], |
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_profiler_options['profile_path']) |
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if _profiler_options['exit_on_finished']: |
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sys.exit(0) |
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_profiler_step_id += 1
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