code: def forward(self, input: torch.Tensor) -> torch.Tensor:
      # self.weight.data *= self.mask
  
      return F.conv2d(
          input,
          self.weight * self.mask,
          self.bias,
          self.stride,
          self.padding,
          self.dilation,
      )
  
file_path: benchmark_VAE/src/pythae/models/normalizing_flows/pixelcnn/utils.py
imports: from typing import Union
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the MaskedConv2d obj's underlying member method code with example usage: obj.forward(input) and returns: F