code: def __init__(
      self, num_input_features: int, num_output_features: int
  ) -> None:
      super(_Transition, self).__init__()
      self.add_module("norm", nn.BatchNorm2d(num_input_features))
      self.add_module("relu", nn.ReLU(inplace=True))
      self.add_module(
          "conv",
          nn.Conv2d(
              num_input_features,
              num_output_features,
              kernel_size=1,
              stride=1,
              bias=False,
          ),
      )
      self.add_module("pool", nn.AvgPool2d(kernel_size=2, stride=2))
  
file_path: ARKitScenes/depth_upsampling/models/mspf/blocks/dense_net.py
imports: from typing import List
  import torch
  import torch.nn.functional
  from torch import nn, Tensor
label_desc: Use image node_id 1 to create a new _Transition object from inherited base classes: nn with example: obj = _Transition(num_input_features, num_output_features)