code: def __init__(self, input_c: int, output_c: int):
      super(_Transition, self).__init__()
      self.add_module("norm", nn.BatchNorm2d(input_c))
      self.add_module("relu", nn.ReLU(inplace=True))
      self.add_module(
          "conv",
          nn.Conv2d(
              input_c, output_c, kernel_size=1, stride=1, bias=False
          ),
      )
      self.add_module("pool", nn.AvgPool2d(kernel_size=2, stride=2))
  
imports: import re
  from typing import Any, List, Tuple
  from collections import OrderedDict
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from torch import Tensor
label_desc: Use image node_id 1 to create a new _Transition object from inherited base classes: nn with example: obj = _Transition(input_c, output_c)