code: def TranslateSoftmaxWithLoss(
      layer, pretrained_blobs, is_test, **kwargs
  ):
      softmax_op = core.CreateOperator(
          "Softmax",
          [layer.bottom[0]],
          layer.bottom[0] + "_translator_autogen_softmax",
      )
      xent_op = core.CreateOperator(
          "LabelCrossEntropy",
          [softmax_op.output[0], layer.bottom[1]],
          layer.bottom[0] + "_translator_autogen_xent",
      )
      loss_op = core.CreateOperator(
          "AveragedLoss", xent_op.output[0], layer.top[0]
      )
      return [softmax_op, xent_op, loss_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 28 for calling a global function with example usage: TranslateSoftmaxWithLoss(layer, pretrained_blobs, is_test) and returns: list,  list