28 lines
985 B
Python
28 lines
985 B
Python
import torch
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class EarlyStopping:
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def __init__(self, patience=5, verbose=False):
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self.patience = patience
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self.verbose = verbose
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self.counter = 0
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self.best_score = None
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self.early_stop = False
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def __call__(self, val_loss, model):
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score = -val_loss
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if self.best_score is None:
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self.best_score = score
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self.save_checkpoint(val_loss, model)
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elif score < self.best_score:
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self.counter += 1
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if self.counter >= self.patience:
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self.early_stop = True
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else:
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self.best_score = score
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self.save_checkpoint(val_loss, model)
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self.counter = 0
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def save_checkpoint(self, val_loss, model, filename='checkpoint.pt'):
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if self.verbose:
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print(f'Validation loss decreased ({self.best_score:.6f} --> {val_loss:.6f}). Saving model ...')
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torch.save(model.state_dict(), f'checkpoints/{filename}') |