debug

nnet/augmentation.py

@@ -169,6 +169,7 @@ class AddNoise(object):
             noises = []
             left = original_duration
 
+
             while left > 0:
                 # select noise file at random
                 file = random.choice(self.noises)

nnet/xvector.py

@@ -1225,7 +1225,7 @@ def cross_validation(model, validation_loader, device, validation_shape, mask, m
                 accuracy += (torch.argmax(batch_predictions.data, 1) == target).sum()
                 loss += criterion(batch_predictions, target)
             embeddings[batch_idx * batch_size:batch_idx * batch_size + batch_predictions.shape[0],:] = batch_embeddings.detach().cpu()
-            #classes[batch_idx * batch_size:batch_idx * batch_size + batch_predictions.shape[0]] = target.detach().cpu()
+            classes[batch_idx * batch_size:batch_idx * batch_size + batch_predictions.shape[0]] = target.detach().cpu()
 
     #print(classes.shape[0])
     local_device = "cpu" if embeddings.shape[0] > 3e4 else device