code: def de_resnext101_32x8d() -> ResNet:
      """ResNeXt-101 32x8d model."""
      return _resnet(
          DecoderBottleneck, [3, 4, 23, 3], groups=32, width_per_group=8
      )
  
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 8 for calling a global function with example usage: de_resnext101_32x8d() and returns: _resnet