33 lines
1.2 KiB
Python
33 lines
1.2 KiB
Python
import torch
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import os
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class EarlyStoppingCallback:
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def __init__(self, model_name, 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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self.model_name = model_name
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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):
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directory = "models/checkpoints"
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if not os.path.exists(directory):
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os.makedirs(directory) # Create the directory if it does not exist
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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(), os.path.join(directory, self.model_name)) |