paddlenlp.utils.profiler 源代码

# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
# 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

import sys
import paddle

# A global variable to record the number of calling times for profiler
# functions. It is used to specify the tracing range of training steps.
_profiler_step_id = 0

# A global variable to avoid parsing from string every time.
_profiler_options = None

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