code: def get_decoder(name: str) -> ResNet:
      """Get decoder model based on the name of the backbone.
  
      Args:
          name (str): Name of the backbone.
  
      Returns:
          ResNet: Decoder ResNet architecture.
      """
      if name in (
          "resnet18",
          "resnet34",
          "resnet50",
          "resnet101",
          "resnet152",
          "resnext50_32x4d",
          "resnext101_32x8d",
          "wide_resnet50_2",
          "wide_resnet101_2",
      ):
          decoder = globals()[f"de_{name}"]
      else:
          raise ValueError(
              f"Decoder with architecture {name} not supported"
          )
      return decoder()
  
imports: from __future__ import annotations
  from typing import Any, Callable
  from torch import Tensor, nn
  from torchvision.models.resnet import conv1x1, conv3x3
label_desc: Use image node_id 11 for calling a global function with example usage: get_decoder(name) and returns: decoder