code: def _load_class_indices():
      # The caffemodel weights in the original repository
      # (https://github.com/hujie-frank/SENet) have been trained with a modified
      # order of class indices.
  
      indices = np.zeros(1000, dtype=np.int32)
      file = os.path.join(os.path.dirname(__file__), "label_map.csv")
  
      with open(file, "r") as fr:
          lines = fr.readlines()
          for line in lines:
              index_modified, index_origin = map(
                  int, line.strip().split(",")
              )
              indices[index_origin] = index_modified
  
      return indices
  
imports: import argparse
  import numpy
  import os
  import chainer
  from chainer.links.caffe.caffe_function import CaffeFunction
  from chainercv.links import SEResNet101
  from chainercv.links import SEResNet152
  from chainercv.links import SEResNet50
  from chainercv.links import SEResNeXt101
  from chainercv.links import SEResNeXt50
label_desc: Use image node_id 9 for calling a global function with example usage: _load_class_indices() and returns: indices