def test_content_loss_computes_grad(input_tensors: Tuple[torch.Tensor,
torch.Tensor],
device: str) -> None:
x, y = input_tensors
x.requires_grad_()
loss_value = ContentLoss()(x.to(device), y.to(device))
loss_value.backward()
assert x.grad is not None, NONE_GRAD_ERR_MSG
def test_content_loss_computes_grad(input_tensors: Tuple[torch.Tensor,
torch.Tensor],
device: str) -> None:
prediction, target = input_tensors
prediction.requires_grad_()
loss_value = ContentLoss()(prediction.to(device), target.to(device))
loss_value.backward()
assert prediction.grad is not None, NONE_GRAD_ERR_MSG
