CEL

Code/test_loss.py

@@ -25,8 +25,8 @@ target = torch.tensor([0.0000, 0.6000])
 l = 0.4
 logits = torch.tensor([[ 0.9391, -1.2892], [-0.1607,  0.1771]], dtype=torch.float32)
 
-for t, l in zip(target, logits):
-    print(l[0])
+for t, l in logits, target:
+    print(l)
 
 # print(target)
 # value = target.item()

Code/train.py

@@ -142,7 +142,7 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 #log base e
 #Fkt vom Meeting
 def cross_entropy(logits, target, l):
-	for t, l in zip(target, logits):
+	for t, l in target, logits:
 		#makes the logits in log (base) probabilities
 		logprobs = torch.nn.functional.log_softmax(l, dim=1)
 		value = t.item() #gets Item (0. or 1.)