def test_grad_transpose_forward(get_clients) -> None:
secret = torch.Tensor([[1, 2, 3], [4, 5, 6]])
mpc_tensor = secret.share(parties=get_clients(4))
ctx = {}
res_mpc = GradT.forward(ctx, mpc_tensor)
res = res_mpc.reconstruct()
expected = secret.t()
assert (res == expected).all()
def test_grad_transpose_backward(get_clients) -> None:
parties = get_clients(4)
grad = torch.Tensor([[1, 2, 3], [4, 5, 6]])
grad_mpc = grad.t().share(parties=parties)
ctx = {}
res_mpc = GradT.backward(ctx, grad_mpc)
res = res_mpc.reconstruct()
expected = grad
assert (res == expected).all()