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| # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. | |
| # | |
| # 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. | |
| import collections | |
| import numpy as np | |
| import datetime | |
| __all__ = ['TrainingStats', 'Time'] | |
| class SmoothedValue(object): | |
| """Track a series of values and provide access to smoothed values over a | |
| window or the global series average. | |
| """ | |
| def __init__(self, window_size): | |
| self.deque = collections.deque(maxlen=window_size) | |
| def add_value(self, value): | |
| self.deque.append(value) | |
| def get_median_value(self): | |
| return np.median(self.deque) | |
| def Time(): | |
| return datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f') | |
| class TrainingStats(object): | |
| def __init__(self, window_size, stats_keys): | |
| self.window_size = window_size | |
| self.smoothed_losses_and_metrics = { | |
| key: SmoothedValue(window_size) | |
| for key in stats_keys | |
| } | |
| def update(self, stats): | |
| for k, v in stats.items(): | |
| if k not in self.smoothed_losses_and_metrics: | |
| self.smoothed_losses_and_metrics[k] = SmoothedValue( | |
| self.window_size) | |
| self.smoothed_losses_and_metrics[k].add_value(v) | |
| def get(self, extras=None): | |
| stats = collections.OrderedDict() | |
| if extras: | |
| for k, v in extras.items(): | |
| stats[k] = v | |
| for k, v in self.smoothed_losses_and_metrics.items(): | |
| stats[k] = round(v.get_median_value(), 6) | |
| return stats | |
| def log(self, extras=None): | |
| d = self.get(extras) | |
| strs = [] | |
| for k, v in d.items(): | |
| strs.append('{}: {:x<6f}'.format(k, v)) | |
| strs = ', '.join(strs) | |
| return strs | |