def test_cos(test_case):
input = flow.Tensor(np.random.randn(1, 3, 6), dtype=flow.float32)
of_out = flow.cos(input)
np_out = np.cos(input.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-5, 1e-5))
test_case.assertTrue(
np.allclose(input.cos().numpy(), np_out, 1e-5, 1e-5))
def _test_cos(test_case, shape, device):
input = flow.Tensor(np.random.randn(*shape),
dtype=flow.float32,
device=flow.device(device))
of_out = flow.cos(input)
np_out = np.cos(input.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-5, 1e-5))
def _test_cos_backward(test_case, shape, device):
x = flow.Tensor(
np.random.randn(*shape),
dtype=flow.float32,
device=flow.device(device),
requires_grad=True,
)
y = flow.cos(x)
z = y.sum()
z.backward()
np_grad = -np.sin(x.numpy())
test_case.assertTrue(np.allclose(x.grad.numpy(), np_grad, 1e-5, 1e-5))