shape try 2

Code/train.py

@@ -105,10 +105,10 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 						
 					print("logits: ", logits) 
 					print("logits size: ", logits.size())
-					print("logits shape: ", logits.getShape())
+					print("logits shape: ", list(logits.shape))
 					print("Newlabels: ", new_labels_batch)
 					print("labels size: ", new_labels_batch.size())
-					print("labels shape: ", new_labels_batch.getShape())
+					print("labels shape: ", list(new_labels_batch.shape))
 
 					input = torch.autograd.Variable(logits.view(-1, 2).to("cuda"))
 					target = torch.nn.functional.softmax(torch.autograd.Variable(new_labels_batch.view(-1).to("cuda")))