code: def __init__(self):
      super().__init__()
      model = DenseNet(32, (6, 12, 24, 16), 64)
      self.base_model = model.features
      self.skip_feature_names = [
          "relu0",
          "pool0",
          "transition1",
          "transition2",
          "norm5",
      ]
      self.skip_out_channels = [64, 64, 128, 256, 1024]
  
file_path: ARKitScenes/depth_upsampling/models/mspf/densenet.py
imports: from collections import OrderedDict
  from typing import Tuple
  import torch
  import torch.nn.functional
  from torch import nn, Tensor
  from models.mspf.blocks.dense_net import _DenseBlock, _Transition
label_desc: Use image node_id 1 to create a new DenseNet121 object from inherited base classes: nn with example: obj = DenseNet121()