code: def forward(self, inp):
      if self.filt_size == 1:
          if self.pad_off == 0:
              return inp[:, :, :: self.stride, :: self.stride]
          else:
              return self.pad(inp)[:, :, :: self.stride, :: self.stride]
      else:
          return F.conv2d(
              self.pad(inp),
              self.filt,
              stride=self.stride,
              groups=inp.shape[1],
          )
  
file_path: antialiased-cnns/antialiased_cnns/blurpool.py
imports: import torch
  import torch.nn.parallel
  import numpy
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the BlurPool obj's underlying member method code with example usage: obj.forward(inp) and returns: F, inp, self