def test_vif_loss_computes_grad_for_zeros_tensors() -> None:
x = torch.zeros(4, 3, 256, 256, requires_grad=True)
y = torch.zeros(4, 3, 256, 256)
loss_value = VIFLoss()(x, y)
loss_value.backward()
assert x.grad is not None, NONE_GRAD_ERR_MSG
def test_vif_loss_computes_grad(x, y, device: str) -> None:
x.requires_grad_()
loss_value = VIFLoss()(x.to(device), y.to(device))
loss_value.backward()
assert x.grad is not None, NONE_GRAD_ERR_MSG
def test_vif_loss_computes_grad(prediction: torch.Tensor, target: torch.Tensor,
device: str) -> None:
prediction.requires_grad_()
loss_value = VIFLoss()(prediction.to(device), target.to(device))
loss_value.backward()
assert prediction.grad is not None, NONE_GRAD_ERR_MSG
def test_vif_loss_computes_grad_for_zeros_tensors() -> None:
prediction = torch.zeros(4, 3, 256, 256, requires_grad=True)
target = torch.zeros(4, 3, 256, 256)
loss_value = VIFLoss()(prediction, target)
loss_value.backward()
assert prediction.grad is not None, NONE_GRAD_ERR_MSG
def test_vif_loss_computes_grad_on_gpu(prediction: torch.Tensor,
target: torch.Tensor) -> None:
prediction.requires_grad_()
loss_value = VIFLoss()(prediction.cuda(), target.cuda())
loss_value.backward()
assert prediction.grad is not None, NONE_GRAD_ERR_MSG