code: def __init__(self, pretrained=True, layers=None):
      from timm.models import dpn
  
      if layers is None:
          layers = [0, 1, 2, 3]
  
      encoder = dpn.dpn92(
          pretrained=pretrained,
          features_only=True,
          out_indices=(1, 2, 3, 4),
      )
      super().__init__([336, 704, 1552, 2688], [4, 8, 16, 32], layers)
      self.encoder = encoder
  
imports: import torch
  from ..common import EncoderModule, make_n_channel_input
label_desc: Use image node_id 1 to create a new DPN92Encoder object from inherited base classes: EncoderModule with example: obj = DPN92Encoder(pretrained, layers)