class_docstr: The Global Convolutional Network module using large 1D
  Kx1 and 1xK kernels to represent 2D kernels.
class_docstr_tok: ["The","Global","Convolutional","Network","module","using","large","1D","Kx1","and","1xK","kernels","to","represent","2D","kernels","."]
docstr: Args:
      inplanes: number of input channels.
      planes: number of output channels.
      ks: kernel size for one dimension. Defaults to 7.
docstr_tok: ["Args",":","inplanes",":","number","of","input","channels",".","planes",":","number","of","output","channels",".","ks",":","kernel","size","for","one","dimension",".","Defaults","to","7","."]
code: def __init__(self, inplanes: int, planes: int, ks: int = 7):
      """
      Args:
          inplanes: number of input channels.
          planes: number of output channels.
          ks: kernel size for one dimension. Defaults to 7.
      """
      super().__init__()
  
      conv2d_type: type[nn.Conv2d] = Conv[Conv.CONV, 2]
      self.conv_l1 = conv2d_type(
          in_channels=inplanes,
          out_channels=planes,
          kernel_size=(ks, 1),
          padding=(ks // 2, 0),
      )
      self.conv_l2 = conv2d_type(
          in_channels=planes,
          out_channels=planes,
          kernel_size=(1, ks),
          padding=(0, ks // 2),
      )
      self.conv_r1 = conv2d_type(
          in_channels=inplanes,
          out_channels=planes,
          kernel_size=(1, ks),
          padding=(0, ks // 2),
      )
      self.conv_r2 = conv2d_type(
          in_channels=planes,
          out_channels=planes,
          kernel_size=(ks, 1),
          padding=(ks // 2, 0),
      )
  
imports: from __future__ import annotations
  import torch
  import torch.nn
  import torch.nn.functional
  from monai.networks.blocks.convolutions import Convolution
  from monai.networks.blocks.upsample import UpSample
  from monai.networks.layers.factories import Act, Conv, Norm
  from monai.utils import optional_import
label_desc: Use image node_id 1 to create a new GCN object from inherited base classes: nn with example: obj = GCN(inplanes, planes, ks)