def _test_sin_backward(test_case, shape, device):
x = flow.Tensor(np.random.randn(*shape),
requires_grad=True,
device=flow.device(device))
y = flow.sin(x)
z = y.sum()
z.backward()
test_case.assertTrue(
np.allclose(x.grad.numpy(), np.cos(x.numpy()), 1e-5, 1e-5))
def test_sin(test_case):
input = flow.Tensor(np.random.randn(2, 6, 5, 3))
of_out = flow.sin(input)
np_out = np.sin(input.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-5, 1e-5))
def _test_sin(test_case, shape, device):
input = flow.Tensor(np.random.randn(*shape), device=flow.device(device))
of_out = flow.sin(input)
np_out = np.sin(input.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-5, 1e-5))