How do I solve the error: Only one element tensors can be converted to python scalars

Question

I am doing transfer learning with a vision transformer model and I have a bit of manipulation on the images therein.

for epoch in range(epochs):
    with tqdm(train_loader) as p_bar:
        for batch_idx, (data, target) in enumerate(p_bar):
            data, target = data.to(device), target.to(device)
            
            data.requires_grad = True

            output = model(data, fine_tune=True)
            init_pred = output.max(1, keepdim = True)[1]
            # init_pred = torch.max(output.data, 1)
            print(init_pred.shape, " and ", target.shape)
            if init_pred.item() != target.item():
                continue

            
            loss = criterion(output, target)

            model.zero_grad()

            loss.backward()

            data_grad = data.grad.data

            uf = F.unfold(data, kernel_size=16, stride=16, padding=0)
            patch = uf[..., 130]
            perturbed_patch = fgsm_attack(patch, epsilon, data_grad)
            uf[..., 130] =  patch
            perturbed_data = F.fold(uf, data.shape[-2:], kernel_size=16, stride=16, padding=0)

            output = model(perturbed_data)

            #check for success
            final_pred = output.max(1, keepdim=True)[1] # get the index of max log-probability

            if final_pred.item() == target.item():
                correct += 1

                    #Special case for saving 0 epsilon examples
                if (epsilon == 0) and (len(adv_examples) < 5):
                    adv_ex = perturbed_data.squeeze().detach().cpu().numpy()
                    adv_examples.append( (init_pred.item(), final_pred.item(), adv_ex) )
            else:
            # Save some adv examples for visualization later
                if len(adv_examples) < 5:
                    adv_ex = perturbed_data.squeeze().detach().cpu().numpy()
                    adv_examples.append( (init_pred.item(), final_pred.item(), adv_ex) )

# Calculate final accuracy for this epsilon
final_acc = correct/float(len(test_loader))
print("Epsilon: {}\tTest Accuracy = {} / {} = {}".format(epsilon, correct, len(test_loader), final_acc))

Unfortunately I got the below error on the line with if init_pred.item() != target.item(): :

ValueError: only one element tensors can be converted to Python scalars

When I tried to print out the values of init_pred and target, I got a list of numbers. I do not know how to fix this error.