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/trainers/MCCNNTrainer.py

@@ -341,6 +341,6 @@ class MCCNNTrainer(object):
 
 		self.network.load_state_dict(best_model_wts)
 
-		# best epoch is named as best
+		# best epoch is named as 100
 
 		self.save_model(output_dir, epoch=100, iteration=0, losses=losses)