class_docstr: A wrapper around :class:`torch.nn.Conv2d` to support empty inputs and
  more features.
class_docstr_tok: ["A","wrapper","around",":","class",":","`","torch.nn.Conv2d","`","to","support","empty","inputs","and","more","features","."]
code: def forward(self, x):
      x = F.conv2d(
          x,
          self.weight,
          self.bias,
          self.stride,
          self.padding,
          self.dilation,
          self.groups,
      )
      if self.norm is not None:
          x = self.norm(x)
      if self.activation is not None:
          x = self.activation(x)
      return x
  
imports: import copy
  import math
  from typing import Optional
  import torch
  import torch.nn.functional
  from torch import Tensor, nn
label_desc: Use image node_id 2 for calling the Conv2d obj's underlying member method code with example usage: obj.forward(x) and returns: x