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Early Stopping PyTorch
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# MIT License | |
# | |
# Copyright (c) 2018 Stefano Nardo https://gist.github.com/stefanonardo | |
# | |
# Permission is hereby granted, free of charge, to any person obtaining a copy | |
# of this software and associated documentation files (the "Software"), to deal | |
# in the Software without restriction, including without limitation the rights | |
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
# copies of the Software, and to permit persons to whom the Software is | |
# furnished to do so, subject to the following conditions: | |
# | |
# The above copyright notice and this permission notice shall be included in all | |
# copies or substantial portions of the Software. | |
# | |
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | |
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | |
# SOFTWARE. | |
class EarlyStopping(object): | |
def __init__(self, mode='min', min_delta=0, patience=10, percentage=False): | |
self.mode = mode | |
self.min_delta = min_delta | |
self.patience = patience | |
self.best = None | |
self.num_bad_epochs = 0 | |
self.is_better = None | |
self._init_is_better(mode, min_delta, percentage) | |
if patience == 0: | |
self.is_better = lambda a, b: True | |
self.step = lambda a: False | |
def step(self, metrics): | |
if self.best is None: | |
self.best = metrics | |
return False | |
if torch.isnan(metrics): | |
return True | |
if self.is_better(metrics, self.best): | |
self.num_bad_epochs = 0 | |
self.best = metrics | |
else: | |
self.num_bad_epochs += 1 | |
if self.num_bad_epochs >= self.patience: | |
return True | |
return False | |
def _init_is_better(self, mode, min_delta, percentage): | |
if mode not in {'min', 'max'}: | |
raise ValueError('mode ' + mode + ' is unknown!') | |
if not percentage: | |
if mode == 'min': | |
self.is_better = lambda a, best: a < best - min_delta | |
if mode == 'max': | |
self.is_better = lambda a, best: a > best + min_delta | |
else: | |
if mode == 'min': | |
self.is_better = lambda a, best: a < best - ( | |
best * min_delta / 100) | |
if mode == 'max': | |
self.is_better = lambda a, best: a > best + ( | |
best * min_delta / 100) |
Hi @stefanonardo , how should I credit you and what is the license of the script?
Hi @jakobamb, thank you for asking. I added a license.
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Hi @stefanonardo , how should I credit you and what is the license of the script?