[script] fixed the default value for the conditional dim, print out the total number of IDs

bob/learn/pytorch/scripts/train_drgan_multipie.py

@@ -14,7 +14,7 @@ Options:
   -V, --version                 Show version.
   -l, --latent-dim=<int>        the dimension of the encoded ID [default: 320]
   -n, --noise-dim=<int>         the dimension of the noise [default: 100]
-  -c, --conditional-dim=<int>   the dimension of the noise [default: 100]
+  -c, --conditional-dim=<int>   the dimension of the conditioning variable [default: 13]
   -b, --batch-size=<int>        The size of your mini-batch [default: 64]
   -e, --epochs=<int>            The number of training epochs [default: 100] 
   -s, --sample=<int>            Save generated images at every 'sample' batch iteration [default: 100000000000] 
@@ -124,13 +124,15 @@ def main(user_input=None):
                                    ])
                                  )
   dataloader = torch.utils.data.DataLoader(face_dataset, batch_size=batch_size, shuffle=True)
-  logger.info("There are {} training images".format(len(face_dataset))) 
+  logger.info("There are {} training images".format(len(face_dataset)))
+  
+  # get the number of ids
+  number_of_ids = numpy.max(face_dataset.id_labels) + 1
+  logger.info("There are {} different identities".format(number_of_ids))
 
   # get the image size
   image_size = face_dataset[0]['image'].numpy().shape
 
-  # get the number of ids
-  number_of_ids = numpy.max(face_dataset.id_labels)
 
   # ===============
   # === NETWORK ===