class_docstr: Model with only Conv2d layers, some with bias, some in a Sequential and some outside.
  Used to test pruned Conv2d-Bias-Conv2d fusion.
class_docstr_tok: ["Model","with","only","Conv2d","layers",",","some","with","bias",",","some","in","a","Sequential","and","some","outside",".","Used","to","test","pruned","Conv2d-Bias-Conv2d","fusion","."]
code: def forward(self, x):
      x = self.seq(x)
      x = self.conv2d1(x)
      x = self.conv2d2(x)
      return x
  
imports: from torch.ao.pruning import BaseSparsifier
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the Conv2dBias obj's underlying member method code with example usage: obj.forward(x) and returns: x