formatting

Author: hadim

pytorch_lightning/callbacks/gradient_accumulation_scheduler.py

@@ -9,7 +9,8 @@ class GradientAccumulationScheduler(Callback):
 
     Args:
         scheduling (dict): scheduling in format {epoch: accumulation_factor}
-        .. warning:: Epochs indexing starts from "1" until v0.6.x, but will start from "0" in v0.8.0.
+        .. warning:: Epochs indexing starts from "1" until v0.6.x, but will start from "0" in
+        v0.8.0.
 
     Example::
 

pytorch_lightning/callbacks/model_checkpoint.py

@@ -62,9 +62,9 @@ def __init__(self, filepath, monitor='val_loss', verbose=0,
                  mode='auto', period=1, prefix=''):
         super(ModelCheckpoint, self).__init__()
         if (
-            save_top_k
-            and os.path.isdir(filepath)
-            and len(os.listdir(filepath)) > 0
+            save_top_k and
+            os.path.isdir(filepath) and
+            len(os.listdir(filepath)) > 0
         ):
             warnings.warn(
                 f"Checkpoint directory {filepath} exists and is not empty with save_top_k != 0."
@@ -175,9 +175,11 @@ def on_validation_end(self):
                         if len(self.best_k_models.keys()) == self.save_top_k:
                             # monitor dict has reached k elements
                             if self.mode == 'min':
-                                self.kth_best_model = max(self.best_k_models, key=self.best_k_models.get)
+                                self.kth_best_model = max(
+                                    self.best_k_models, key=self.best_k_models.get)
                             else:
-                                self.kth_best_model = min(self.best_k_models, key=self.best_k_models.get)
+                                self.kth_best_model = min(
+                                    self.best_k_models, key=self.best_k_models.get)
                             self.kth_value = self.best_k_models[self.kth_best_model]
 
                         if self.mode == 'min':