Add validation loss computation as optional argument

keras_retinanet/bin/train.py

@@ -410,6 +410,7 @@ def csv_list(string):
     parser.add_argument('--image-max-side',   help='Rescale the image if the largest side is larger than max_side.', type=int, default=1333)
     parser.add_argument('--config',           help='Path to a configuration parameters .ini file.')
     parser.add_argument('--weighted-average', help='Compute the mAP using the weighted average of precisions among classes.', action='store_true')
+    parser.add_argument('--compute-val-loss', help='Compute validation loss during training', dest='compute_val_loss', action='store_false')
 
     # Fit generator arguments
     parser.add_argument('--workers', help='Number of multiprocessing workers. To disable multiprocessing, set workers to 0', type=int, default=1)
@@ -492,6 +493,9 @@ def main(args=None):
     else:
         use_multiprocessing = False
 
+    if not args.compute_val_loss:
+        validation_generator = None
+
     # start training
     return training_model.fit_generator(
         generator=train_generator,