class_docstr: input 17*17*1152
  ouput 8*8*2144
class_docstr_tok: ["input","17","*","17","*","1152","ouput","8","*","8","*","2144"]
code: def __init__(self):
      super(ReductionB, self).__init__()
      self.branch_0 = nn.MaxPool2d(3, stride=2)
      self.branch_1 = nn.Sequential(
          BasicConv2d(1152, 256, kernel_size=1, stride=1),
          BasicConv2d(256, 384, kernel_size=3, stride=2),
      )
      self.branch_2 = nn.Sequential(
          BasicConv2d(1152, 256, kernel_size=1, stride=1),
          BasicConv2d(256, 288, kernel_size=3, stride=2),
      )
      self.branch_3 = nn.Sequential(
          BasicConv2d(1152, 256, kernel_size=1, stride=1),
          BasicConv2d(256, 288, kernel_size=3, stride=1, padding=1),
          BasicConv2d(288, 320, kernel_size=3, stride=2),
      )
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new ReductionB object from inherited base classes: nn with example: obj = ReductionB()