hi. I got this error “RuntimeError: Expected object of scalar type Long but got scalar type Float for argument #2 ‘target’ in call to _thnn_nll_loss2d_forward”  when I executed the following code:
model = torchvision.models.resnet50(pretrained=False)
criterion=MSELoss().cuda()
train_loss = 0
for i_batch, sample_batched in enumerate(TraindataLoader):
local_X = sample_batched[‘input’].cuda()
local_Y = sample_batched[‘EEGResponse’].cuda()
can anbody tell me how to solve this problem?
    # compute the model output
    yhat = model(local_X)
    yhat= torch.reshape(yhat,[size_batches,1,17,100])
    # calculate loss
    loss = criterion(yhat, local_Y)
    train_loss += loss.item()
    losses.update(loss.item(), size_batches)
        
    # compute gradient and do SGD step
    optimizer.zero_grad()

        
    # credit assignment
    loss.backward()
    # update model weights
    optimizer.step()