class_docstr: Large Kernel Matters -- https://arxiv.org/abs/1703.02719
class_docstr_tok: ["Large","Kernel","Matters","--","https",":","\/\/arxiv.org\/abs\/1703.02719"]
code: def __init__(self, in_channels, out_channels, k=3):
      super(GCN, self).__init__()
  
      self.conv_l1 = Conv2D(
          in_channels=in_channels,
          out_channels=out_channels,
          kernel_size=(k, 1),
          padding="same",
      )
      self.conv_l2 = Conv2D(
          in_channels=out_channels,
          out_channels=out_channels,
          kernel_size=(1, k),
          padding="same",
      )
  
      self.conv_r1 = Conv2D(
          in_channels=in_channels,
          out_channels=out_channels,
          kernel_size=(1, k),
          padding="same",
      )
      self.conv_r2 = Conv2D(
          in_channels=out_channels,
          out_channels=out_channels,
          kernel_size=(k, 1),
          padding="same",
      )
  
file_path: gluon-cv/gluoncv/torch/nn/group_norm.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Module, Parameter
  from torch.nn import init
label_desc: Use image node_id 1 to create a new GCN object from inherited base classes: nn with example: obj = GCN(in_channels, out_channels, k)