43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
# Copyright (c) 2021 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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from copy import deepcopy
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import paddle
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class ExponentialMovingAverage():
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"""
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Exponential Moving Average
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Code was heavily based on https://github.com/rwightman/pytorch-image-models/blob/master/timm/utils/model_ema.py
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"""
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def __init__(self, model, decay=0.9999):
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super().__init__()
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# make a copy of the model for accumulating moving average of weights
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self.module = deepcopy(model)
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self.module.eval()
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self.decay = decay
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@paddle.no_grad()
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def _update(self, model, update_fn):
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for ema_v, model_v in zip(self.module.state_dict().values(), model.state_dict().values()):
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ema_v.set_value(update_fn(ema_v, model_v))
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def update(self, model):
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self._update(model, update_fn=lambda e, m: self.decay * e + (1. - self.decay) * m)
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def set(self, model):
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self._update(model, update_fn=lambda e, m: m)
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