code: def __init__(
      self,
      layers=None,
      pretrained=True,
      memory_efficient=False,
      first_avg_pool=False,
  ):
      densenet = densenet169(
          pretrained=pretrained, memory_efficient=memory_efficient
      )
      strides = [2, 4, 8, 16, 32]
      channels = [64, 128, 256, 640, 1664]
      super().__init__(
          densenet, strides, channels, layers, first_avg_pool
      )
  
imports: from collections import OrderedDict
  from typing import List
  import torch
  from torch import nn
  from torchvision.models import densenet121, densenet161, densenet169, densenet201, DenseNet
  from .common import EncoderModule, _take, make_n_channel_input
label_desc: Use image node_id 1 to create a new DenseNet169Encoder object from inherited base classes: DenseNetEncoder with example: obj = DenseNet169Encoder(layers, pretrained, memory_efficient, first_avg_pool)