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Code/train.py

@@ -139,7 +139,12 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 
 	return evaluation_test, evaluation_train
 
+#Fkt vom Meeting
+def cross_entropy(logits, target):
+    logprobs = torch.nn.functional.log_softmax (logits, dim = 1)
+    return  -torch.mean(torch.sum(target * logprobs, dim=1))
 
+#kann weg
 # def cross_entropy(logits, target):
 #     log_q = torch.log_softmax(logits, dim=1)
 #     return -torch.sum(log_q[range(log_q.shape[0]), target])