def _test_sign_impl(test_case, shape, device):
np_input = np.random.randn(*shape)
of_input = flow.tensor(np_input,
dtype=flow.float32,
device=flow.device(device),
requires_grad=True)
of_out = flow.sign(of_input)
np_out = np.sign(np_input)
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 0.0001, 0.0001))
of_out = of_out.sum()
of_out.backward()
np_grad = np.zeros_like(np_input)
test_case.assertTrue(
np.allclose(of_input.grad.numpy(), np_grad, 0.0001, 0.0001))
def _sign(self):
return flow.sign(self)
def forward(self, x):
return flow.sign(x)
