Kaiser Filter Lowpass Module for PyTorch. Torchvision's gaussian blur uses the "reflect" padding mode but I'm not sure if that makes sense so I've set it for "replicate" by default.

kaiser_lowpass.py

import torch
import torch.nn as nn
import torch.nn.functional as F

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

class KaiserLowpass(nn.Module):
    def __init__(self, width=7, beta=11, periodic=False, padding_mode='replicate'):
        super().__init__()
        self.padding_mode = padding_mode
        self.padding = 4*[(width-1)//2]
        self.kernel = torch.kaiser_window(width,periodic,beta).reshape(1,1,1,width).to(device)
    def forward(self, x):
        b,c,h,w = x.shape
        x = F.pad(x,self.padding,self.padding_mode)
        x = F.conv2d(x, self.kernel.expand(c,-1,-1,-1), groups=c)
        x = F.conv2d(x, self.kernel.permute(0,1,3,2).expand(c,-1,-1,-1), groups=c)
        return x