7f0eb809f1509c452d85000fd002b12c22e358ca,kornia/filters/kernels.py,,gaussian,#Any#Any#,17

Before Change

    def gauss_fcn(x):
        return -(x - window_size // 2) ** 2 / float(2 * sigma ** 2)

    gauss = torch.stack(
        [torch.exp(torch.tensor(gauss_fcn(x))) for x in range(window_size)]
    )
    return gauss / gauss.sum()


def laplacian_1d(window_size) -> torch.Tensor:

After Change

def gaussian(window_size, sigma):
    x = torch.arange(window_size).float() - window_size // 2
    if window_size % 2 == 0:
        x = x + 0.5
    gauss = torch.exp((-x.pow(2.0) / float(2 * sigma ** 2)))
    return gauss / gauss.sum()


def laplacian_1d(window_size) -> torch.Tensor:

Instances