code: def __init__(self):
      super(Inception_C, self).__init__()
  
      self.branch0 = BasicConv2d(1536, 256, kernel_size=1, stride=1)
  
      self.branch1_0 = BasicConv2d(1536, 384, kernel_size=1, stride=1)
      self.branch1_1a = BasicConv2d(
          384, 256, kernel_size=(1, 3), stride=1, padding=(0, 1)
      )
      self.branch1_1b = BasicConv2d(
          384, 256, kernel_size=(3, 1), stride=1, padding=(1, 0)
      )
  
      self.branch2_0 = BasicConv2d(1536, 384, kernel_size=1, stride=1)
      self.branch2_1 = BasicConv2d(
          384, 448, kernel_size=(3, 1), stride=1, padding=(1, 0)
      )
      self.branch2_2 = BasicConv2d(
          448, 512, kernel_size=(1, 3), stride=1, padding=(0, 1)
      )
      self.branch2_3a = BasicConv2d(
          512, 256, kernel_size=(1, 3), stride=1, padding=(0, 1)
      )
      self.branch2_3b = BasicConv2d(
          512, 256, kernel_size=(3, 1), stride=1, padding=(1, 0)
      )
  
      self.branch3 = nn.Sequential(
          nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False),
          BasicConv2d(1536, 256, kernel_size=1, stride=1),
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.model_zoo
label_desc: Use image node_id 1 to create a new Inception_C object from inherited base classes: nn with example: obj = Inception_C()