code: def __init__(self, input_channels, pool_features):
      super().__init__()
      self.branch1x1 = BasicConv2d(input_channels, 64, kernel_size=1)
  
      self.branch5x5 = nn.Sequential(
          BasicConv2d(input_channels, 48, kernel_size=1),
          BasicConv2d(48, 64, kernel_size=5, padding=2),
      )
  
      self.branch3x3 = nn.Sequential(
          BasicConv2d(input_channels, 64, kernel_size=1),
          BasicConv2d(64, 96, kernel_size=3, padding=1),
          BasicConv2d(96, 96, kernel_size=3, padding=1),
      )
  
      self.branchpool = nn.Sequential(
          nn.AvgPool2d(kernel_size=3, stride=1, padding=1),
          BasicConv2d(
              input_channels, pool_features, kernel_size=3, padding=1
          ),
      )
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new InceptionA object from inherited base classes: nn with example: obj = InceptionA(input_channels, pool_features)