code: def __init__(self, input_channels):
      super().__init__()
  
      self.branch3x3 = nn.Sequential(
          BasicConv2d(input_channels, 192, kernel_size=1),
          BasicConv2d(192, 320, kernel_size=3, stride=2),
      )
  
      self.branch7x7 = nn.Sequential(
          BasicConv2d(input_channels, 192, kernel_size=1),
          BasicConv2d(192, 192, kernel_size=(1, 7), padding=(0, 3)),
          BasicConv2d(192, 192, kernel_size=(7, 1), padding=(3, 0)),
          BasicConv2d(192, 192, kernel_size=3, stride=2),
      )
  
      self.branchpool = nn.AvgPool2d(kernel_size=3, stride=2)
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new InceptionD object from inherited base classes: nn with example: obj = InceptionD(input_channels)