test_autograd.py 文件源码

def test_mlpg_variance_expand():
    static_dim = 2
    T = 10

    for windows in _get_windows_set():
        torch.manual_seed(1234)
        means = Variable(torch.rand(T, static_dim * len(windows)),
                         requires_grad=True)
        variances = torch.rand(static_dim * len(windows))
        variances_expanded = variances.expand(T, static_dim * len(windows))
        y = AF.mlpg(means, variances, windows)
        y_hat = AF.mlpg(means, variances_expanded, windows)
        assert np.allclose(y.data.numpy(), y_hat.data.numpy())