def _test_add_forward(test_case, device):
x = flow.Tensor(np.random.randn(2, 3), device=flow.device(device))
y = flow.Tensor(np.random.randn(2, 3), device=flow.device(device))
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = 5
y = flow.Tensor(np.random.randn(2, 3), device=flow.device(device))
of_out = flow.add(x, y)
np_out = np.add(x, y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = flow.Tensor(np.random.randn(2, 3), device=flow.device(device))
y = 5
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y)
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = flow.Tensor(np.random.randn(2, 3), device=flow.device(device))
y = flow.Tensor(np.array([5.0]), device=flow.device(device))
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = flow.Tensor(np.random.randn(1, 1), device=flow.device(device))
y = flow.Tensor(np.random.randn(2, 3), device=flow.device(device))
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
def test_add(test_case):
x = flow.Tensor(np.random.randn(2, 3))
y = flow.Tensor(np.random.randn(2, 3))
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = 5
y = flow.Tensor(np.random.randn(2, 3))
of_out = flow.add(x, y)
np_out = np.add(x, y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = flow.Tensor(np.random.randn(2, 3))
y = 5
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y)
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = flow.Tensor(np.random.randn(2, 3))
y = flow.Tensor(np.array([5.0]))
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
x = flow.Tensor(np.random.randn(1, 1))
y = flow.Tensor(np.random.randn(2, 3))
of_out = flow.add(x, y)
np_out = np.add(x.numpy(), y.numpy())
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
def _test_add_backward(test_case, device):
x = 5
y = flow.Tensor(
np.random.randn(2, 3), requires_grad=True, device=flow.device(device)
)
of_out = flow.add(x, y).sum()
of_out.backward()
test_case.assertTrue(np.allclose(y.grad.numpy(), np.ones((2, 3)), 1e-4, 1e-4))