I have an input size of BxCxHxW and a label size of BxHxW, where B is the batch size. We often compute the loss likes
criterion= nn.CrossEntropyWithLoss()
pred = model(input)
loss = criterion(pred, label)

If I want to compute the loss for each batch, then I will use
criterion= nn.CrossEntropyWithLoss()
pred = model(input)
loss = 0
for i in range (B):
    loss += criterion(pred[i:i+1,...], label[i:i+1,...])

Does the second approach provide same result as the first approach? Thanks