Cross validation

This MR adds the following

• Adds cross-validation using a validation set; the best model based on the lowest validation loss is saved automatically now
• Adds trainer, extractor, training script and unit tests for FASNet architecture
• Small change in MCCNN architecture; added a flag for selecting whether to use sigmoid in eval phase.

bob/learn/pytorch/test/test.py

@@ -225,9 +225,9 @@ def test_MCCNNtrainer():
   from ..architectures import MCCNN
   net = MCCNN(num_channels=4)
 
- dataloader={}
- dataloader{'train'} = torch.utils.data.DataLoader(DummyDataSetMCCNN(), batch_size=32, shuffle=True)
-  
+  dataloader={}
+  dataloader['train'] = torch.utils.data.DataLoader(DummyDataSetMCCNN(), batch_size=32, shuffle=True)
+
   from ..trainers import MCCNNTrainer
   trainer = MCCNNTrainer(net, verbosity_level=3)
   trainer.train(dataloader, n_epochs=1, output_dir='.')