Getting RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn

vision
2

Hi @bing, you can’t differentiate torch.argmax with respect to output (as torch.argmax has no grad_fn) so you need to find another way to convert your output tensor to a prediction with an operation that has a grad_fn. A minimal example below to show that torch.argmax has no grad_fn.

import torch
x=torch.randn(10,4,requires_grad=True)
output = torch.argmax(x, dim=1)
print(output.grad_fn) #returns None

You might just be able to remove the torch.argmax call as your Loss seems to expect the raw logits and replace the loss calculation as,

      loss = criterion(output.float(), target.float()). # Conversion of pred and target to float

More info in this post here (about logits with a different loss function you might find useful)

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