style edits and removing use_multiprocessing flag in args

keras_retinanet/bin/train.py

@@ -410,9 +410,8 @@ def csv_list(string):
     parser.add_argument('--weighted-average', help='Compute the mAP using the weighted average of precisions among classes.', action='store_true')
 
     #Fit generator arguments
-    parser.add_argument('--multiprocessing', help='Fit generator mulitprocessing for n worker processes', action='store_true')
-    parser.add_argument('--workers', help='Number of multiprocessing workers', default=1)
-    parser.add_argument('--max_queue_size', help='Queue length for multiprocessing workers in fit generator', default=10)
+    parser.add_argument('--workers', help='Number of multiprocessing workers. To disable multiprocessing, set workers to 0', default=1)
+    parser.add_argument('--max-queue-size', help='Queue length for multiprocessing workers in fit generator.', default=10)
 
     return check_args(parser.parse_args(args))
 
@@ -483,7 +482,13 @@ def main(args=None):
         validation_generator,
         args,
     )
-
+
+    #Use multiprocessing if workers > 0
+    if args.workers > 0:
+        use_multiprocessing = True
+    else:
+        use_multiprocessing = False
+
     # start training
     training_model.fit_generator(
         generator=train_generator,
@@ -492,7 +497,7 @@ def main(args=None):
         verbose=1,
         callbacks=callbacks,
         workers=args.workers,
-        use_multiprocessing=args.multiprocessing,
+        use_multiprocessing=use_multiprocessing,
         max_queue_size=args.max_queue_size
     )
 

keras_retinanet/preprocessing/generator.py

@@ -35,6 +35,7 @@
 )
 from ..utils.transform import transform_aabb
 
+
 class Generator(keras.utils.Sequence):
     """ Abstract generator class.
     """
@@ -314,15 +315,18 @@ def compute_input_output(self, group):
 
         return inputs, targets
 
-    #Keras Sequence methods
     def __len__(self):
-        """Number of batches for generator"""
+        """
+        Number of batches for generator.
+        """
+
         return len(self.groups)
 
     def __getitem__(self,index):
         """
-        Keras sequence method for generating batches
+        Keras sequence method for generating batches.
         """
         group = self.groups[index]        
         inputs,targets=self.compute_input_output(group)
+
         return inputs,targets

tests/preprocessing/test_generator.py

@@ -262,7 +262,7 @@ def test_complete(self):
         simple_generator = SimpleGenerator(input_bboxes_group, input_labels_group, image=input_image, num_classes=6)
         # expect a UserWarning
         with pytest.warns(UserWarning):
-            _, [_, labels_batch] = simple_generator.__getitem__(0)
+            _, [_, labels_batch] = simple_generator[0]
 
         # test that only object with class 5 is present in labels_batch
         labels = np.unique(np.argmax(labels_batch == 5, axis=2))