code: def alpha_pose_resnet101_v1b_coco(**kwargs):
      r"""ResNet-101 backbone model from AlphaPose
      Parameters
      ----------
      num_gpus : int
          Number of usable GPUs.
  
      Returns
      -------
      mxnet.gluon.HybridBlock
          The AlphaPose network.
  
      """
      from ...data import COCOKeyPoints
  
      keypoints = COCOKeyPoints.KEYPOINTS
      num_gpus = kwargs.pop("num_gpus", None)
      if num_gpus is not None and int(num_gpus) > 1:
          norm_layer = mx.gluon.contrib.nn.SyncBatchNorm
          norm_kwargs = {
              "use_global_stats": False,
              "num_devices": int(num_gpus),
          }
      else:
          norm_layer = mx.gluon.nn.BatchNorm
          norm_kwargs = {"use_global_stats": False}
  
      return get_alphapose(
          name="resnet101_v1b",
          dataset="coco",
          num_joints=len(keypoints),
          norm_layer=norm_layer,
          norm_kwargs=norm_kwargs,
          **kwargs,
      )
  
imports: import math
  import os
  import mxnet
  from mxnet import initializer
  from mxnet.gluon import nn
  from mxnet.gluon.block import HybridBlock
  from .utils import ZeroUniform, _try_load_parameters
label_desc: Use image node_id 2 for calling a global function with example usage: alpha_pose_resnet101_v1b_coco() and returns: get_alphapose