def make_gaussian_kernel(kernel_size: int) -> torch.Tensor:
sigma = torch.tensor(kernel_size / 3.0)
kernel = gaussian_1d(sigma=sigma,
truncated=kernel_size // 2,
approx="sampled",
normalize=False) * (2.5066282 * sigma)
return kernel[:kernel_size]
def make_gaussian_kernel(sigma: int) -> torch.Tensor:
if sigma <= 0:
raise ValueError(f"expecting positive sigma, got sigma={sigma}")
return gaussian_1d(sigma=torch.tensor(sigma),
truncated=3,
approx="sampled",
normalize=False)