Update CEL

Code/train.py

@@ -178,7 +178,7 @@ def cross_entropy(logits, target):
 		if value == 1 or value == 0: #check if non-mixed label
 			one_hot = torch.tensor([1-value,value], device='cuda:0') #creating one-hot vector e.g. [0. ,1.]
 			loss_clear_labels = -((one_hot[0] * logprobs[0][0]) + (one_hot[1] * logprobs[0][1]))
-			#calculation with indexing (- 1-label * )
+			#calculation with indexing 
 			results = torch.cat((loss_clear_labels.view(1), results), dim=0)
 		else:
 			mixed_vec = torch.tensor([value, 1-value]) #creating on-hot mixed vec.