David310/Detect_AI-generated_Image

1import numpy as np2import torch3 4 5class EarlyStopping:6    """Early stops the training if validation loss doesn't improve after a given patience."""7    def __init__(self, patience=1, verbose=False, delta=0):8        """9        Args:10            patience (int): How long to wait after last time validation loss improved.11                            Default: 712            verbose (bool): If True, prints a message for each validation loss improvement. 13                            Default: False14            delta (float): Minimum change in the monitored quantity to qualify as an improvement.15                            Default: 016        """17        self.patience = patience18        self.verbose = verbose19        self.counter = 020        self.best_score = None21        self.early_stop = False22        self.score_max = -np.Inf23        self.delta = delta24 25    def __call__(self, score, model):26        if self.best_score is None:27            self.best_score = score28            self.save_checkpoint(score, model)29        elif score < self.best_score - self.delta:30            self.counter += 131            print(f'EarlyStopping counter: {self.counter} out of {self.patience}')32            if self.counter >= self.patience:33                self.early_stop = True34        else:35            self.best_score = score36            self.save_checkpoint(score, model)37            self.counter = 038 39    def save_checkpoint(self, score, model):40        '''Saves model when validation loss decrease.'''41        if self.verbose:42            print(f'Validation accuracy increased ({self.score_max:.6f} --> {score:.6f}).  Saving model ...')43        model.save_networks('best')44        self.score_max = score