fix

bob/learn/pytorch/trainers/MCCNNTrainer.py

@@ -13,7 +13,7 @@ logger = bob.core.log.setup("bob.learn.pytorch")
 
 import time
 import os
-
+"""
 #TODO: 
 #0. Add class balancing
 #1. Logging to tensorboardX or a simpler logger
@@ -21,8 +21,9 @@ import os
 #3. Use to(device) instead of .cuda()?
 #4. Functionality to select channels from the dataloader: may be move this to the datafolder class
 #5. Moving more arguments to config?
+#6. Implement the selection of channels as a transform
 
-
+"""
 def comp_bce_loss_weights(target):
     """
     Compute the balancing weights for the BCE loss function.
@@ -64,7 +65,7 @@ class MCCNNTrainer(object):
     The network to train
   batch_size: int
     The size of your minibatch
-  use_gpu: boolean
+  use_gpu: bool
     If you would like to use the gpu
   verbosity_level: int
     The level of verbosity output to stdout
@@ -80,7 +81,7 @@ class MCCNNTrainer(object):
       The network to train
     batch_size: int
       The size of your minibatch
-    use_gpu: boolean
+    use_gpu: bool
       If you would like to use the gpu
     adapted_layers: str
       The blocks in the CNN to adapt; only the ones listed are adapted in the training. The layers are separated by '-' in the