CEL

Code/train.py

@@ -109,7 +109,7 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 					print("labels shape: ", list(new_labels_batch.shape))
 
 					preds = logits.view(-1, 2).to("cuda")
-					target = torch.nn.functional.softmax(torch.autograd.Variable(new_labels_batch.view(-1).to("cuda")))
+					target = new_labels_batch.view(-1).to("cuda")
 					loss_2 = cross_entropy(preds, target)
 					#loss_2 = SoftCrossEntropyLoss(logits.view(-1, 2).to("cuda"), new_labels_batch.view(-1).to("cuda"))
 					print("MixUp Loss: ", loss_2)