code: def __init__(self):
      super(Inception_B, self).__init__()
      self.branch0 = BasicConv2d(1024, 384, kernel_size=1, stride=1)
  
      self.branch1 = nn.Sequential(
          BasicConv2d(1024, 192, kernel_size=1, stride=1),
          BasicConv2d(
              192, 224, kernel_size=(1, 7), stride=1, padding=(0, 3)
          ),
          BasicConv2d(
              224, 256, kernel_size=(7, 1), stride=1, padding=(3, 0)
          ),
      )
  
      self.branch2 = nn.Sequential(
          BasicConv2d(1024, 192, kernel_size=1, stride=1),
          BasicConv2d(
              192, 192, kernel_size=(7, 1), stride=1, padding=(3, 0)
          ),
          BasicConv2d(
              192, 224, kernel_size=(1, 7), stride=1, padding=(0, 3)
          ),
          BasicConv2d(
              224, 224, kernel_size=(7, 1), stride=1, padding=(3, 0)
          ),
          BasicConv2d(
              224, 256, kernel_size=(1, 7), stride=1, padding=(0, 3)
          ),
      )
  
      self.branch3 = nn.Sequential(
          nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False),
          BasicConv2d(1024, 128, 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_B object from inherited base classes: nn with example: obj = Inception_B()