code: def TranslateReduction(layer, pretrained_blobs, is_test, **kwargs):
      param = layer.reduction_param
      if param.operation == caffe_pb2.ReductionParameter.SUM:
          caffe_op = BaseTranslate(layer, "ReduceBackSum")
      elif param.operation == caffe_pb2.ReductionParameter.MEAN:
          caffe_op = BaseTranslate(layer, "ReduceBackMean")
      else:
          raise NotImplementedError("Not yet supported")
  
      if param.axis > 0:
          # We can't figure out the number of dims to reduce from positive axis
          # for back reduction since the shape info is not known here.
          raise NotImplementedError("Not yet supported")
      num_reduce_dim = -param.axis
      AddArgument(caffe_op, "num_reduce_dim", num_reduce_dim)
  
      return caffe_op, []
  
imports: import argparse
  import copy
  import logging
  import re
  import numpy
  from caffe2.proto import caffe2_pb2, caffe2_legacy_pb2
  from caffe.proto import caffe_pb2
  from caffe2.python import core, utils, workspace
  from google.protobuf import text_format
label_desc: Use image node_id 41 for calling a global function with example usage: TranslateReduction(layer, pretrained_blobs, is_test) and returns: caffe_op,  list