add delta

pytorchtools.py

@@ -3,20 +3,23 @@
 
 class EarlyStopping:
     """Early stops the training if validation loss doesn't improve after a given patience."""
-    def __init__(self, patience=7, verbose=False):
+    def __init__(self, patience=7, verbose=False, delta=0):
         """
         Args:
             patience (int): How long to wait after last time validation loss improved.
                             Default: 7
             verbose (bool): If True, prints a message for each validation loss improvement. 
                             Default: False
+            delta (float): Minimum change in the monitored quantity to qualify as an improvement.
+                            Default: 0
         """
         self.patience = patience
         self.verbose = verbose
         self.counter = 0
         self.best_score = None
         self.early_stop = False
         self.val_loss_min = np.Inf
+        self.delta = delta
 
     def __call__(self, val_loss, model):
 
@@ -25,7 +28,7 @@ def __call__(self, val_loss, model):
         if self.best_score is None:
             self.best_score = score
             self.save_checkpoint(val_loss, model)
-        elif score < self.best_score:
+        elif score < self.best_score - delta:
             self.counter += 1
             print(f'EarlyStopping counter: {self.counter} out of {self.patience}')
             if self.counter >= self.patience: