Args: patience (int): How long to wait after last time validation loss improved. Default: 50 verbose (bool): If True, prints a message for each validation loss improvement. Default: False delta (flo
(self, args, patience=50, verbose=False, delta=0)
| 21 | """Early stops the training if validation loss doesn't improve after a given patience.""" |
| 22 | # source https://blog.csdn.net/qq_37430422/article/details/103638681 |
| 23 | def __init__(self, args, patience=50, verbose=False, delta=0): |
| 24 | """ |
| 25 | Args: |
| 26 | patience (int): How long to wait after last time validation loss improved. |
| 27 | Default: 50 |
| 28 | verbose (bool): If True, prints a message for each validation loss improvement. |
| 29 | Default: False |
| 30 | delta (float): Minimum change in the monitored quantity to qualify as an improvement. |
| 31 | Default: 0 |
| 32 | """ |
| 33 | self.val_on_psnr = args.val_on_psnr |
| 34 | self.patience = patience |
| 35 | self.verbose = verbose |
| 36 | self.counter = 0 |
| 37 | self.best_score = None |
| 38 | self.early_stop = False |
| 39 | self.val_loss_min = np.Inf |
| 40 | self.delta = delta |
| 41 | |
| 42 | self.basedir = args.basedir |
| 43 | self.model_name = args.model_name |
| 44 | |
| 45 | self.out_folder = os.path.join(self.basedir, self.model_name) |
| 46 | self.ckpt_save_path = os.path.join(self.out_folder, 'checkpoint.pt') |
| 47 | if not os.path.isdir(self.out_folder): |
| 48 | os.mkdir(self.out_folder) |
| 49 | |
| 50 | def __call__(self, val_loss, model, epoch=-1, save_multiple=False, save_all=False, val_psnr=None): |
| 51 |
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