def _test_atan2_forward(test_case, shape, scalar, device):
np_input_x = 10 * np.random.rand(*shape)
np_input_y = 10 * np.random.randn(*shape)
of_input_x = flow.Tensor(np_input_x,
dtype=flow.float32,
device=flow.device(device))
of_input_y = flow.Tensor(np_input_y,
dtype=flow.float32,
device=flow.device(device))
of_out = flow.atan2(of_input_x, of_input_y)
np_out = np.arctan2(np_input_x, np_input_y)
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-5, 1e-5))
def test_y_grad():
of_input_x = flow.Tensor(np_input_x,
dtype=flow.float32,
device=flow.device(device))
of_input_y = flow.Tensor(
np_input_y,
dtype=flow.float32,
device=flow.device(device),
requires_grad=True,
)
of_out = flow.atan2(of_input_x, of_input_y)
of_out_sum = of_out.sum()
of_out_sum.backward()
test_case.assertTrue(
np.allclose(of_input_y.grad.numpy(), np_y_grad, 1e-4, 1e-4))