code: def __init__(self, in_dim, out_dim, kernel_size):
      super(_GlobalConvModule, self).__init__()
  
      pad0 = floor((kernel_size[0] - 1) / 2)
      pad1 = floor((kernel_size[1] - 1) / 2)
  
      self.conv_l1 = nn.Conv2d(
          in_dim,
          out_dim,
          kernel_size=(kernel_size[0], 1),
          padding=(pad0, 0),
      )
      self.conv_l2 = nn.Conv2d(
          out_dim,
          out_dim,
          kernel_size=(1, kernel_size[1]),
          padding=(0, pad1),
      )
      self.conv_r1 = nn.Conv2d(
          in_dim,
          out_dim,
          kernel_size=(1, kernel_size[1]),
          padding=(0, pad1),
      )
      self.conv_r2 = nn.Conv2d(
          out_dim,
          out_dim,
          kernel_size=(kernel_size[0], 1),
          padding=(pad0, 0),
      )
  
file_path: pywick/pywick/models/segmentation/gcnnets/gcn.py
imports: import torch
  import torch.nn.functional
  from torch import nn
  from torchvision import models
  import os
  from math import floor
label_desc: Use image node_id 1 to create a new _GlobalConvModule object from inherited base classes: nn with example: obj = _GlobalConvModule(in_dim, out_dim, kernel_size)