forked from PulseFocusPlatform/PulseFocusPlatform
95 lines
2.6 KiB
Python
95 lines
2.6 KiB
Python
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# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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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 collections
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import numpy as np
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__all__ = ['SmoothedValue', 'TrainingStats']
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class SmoothedValue(object):
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"""Track a series of values and provide access to smoothed values over a
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window or the global series average.
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"""
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def __init__(self, window_size=20, fmt=None):
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if fmt is None:
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fmt = "{median:.4f} ({avg:.4f})"
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self.deque = collections.deque(maxlen=window_size)
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self.fmt = fmt
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self.total = 0.
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self.count = 0
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def update(self, value, n=1):
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self.deque.append(value)
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self.count += n
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self.total += value * n
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@property
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def median(self):
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return np.median(self.deque)
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@property
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def avg(self):
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return np.mean(self.deque)
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@property
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def max(self):
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return np.max(self.deque)
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@property
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def value(self):
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return self.deque[-1]
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@property
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def global_avg(self):
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return self.total / self.count
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def __str__(self):
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return self.fmt.format(
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median=self.median, avg=self.avg, max=self.max, value=self.value)
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class TrainingStats(object):
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def __init__(self, window_size, delimiter=' '):
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self.meters = None
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self.window_size = window_size
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self.delimiter = delimiter
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def update(self, stats):
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if self.meters is None:
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self.meters = {
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k: SmoothedValue(self.window_size)
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for k in stats.keys()
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}
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for k, v in self.meters.items():
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v.update(stats[k].numpy())
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def get(self, extras=None):
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stats = collections.OrderedDict()
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if extras:
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for k, v in extras.items():
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stats[k] = v
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for k, v in self.meters.items():
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stats[k] = format(v.median, '.6f')
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return stats
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def log(self, extras=None):
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d = self.get(extras)
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strs = []
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for k, v in d.items():
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strs.append("{}: {}".format(k, str(v)))
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return self.delimiter.join(strs)
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