code: def run(self):
      op = core.CreateOperator(
          "SoftmaxWithLoss",
          ["X", "label"],
          ["probs", "avgloss"],
      )
  
      for n in itertools.imap(pow, itertools.cycle([10]), range(8)):
          for D in itertools.imap(pow, itertools.cycle([10]), range(3)):
              X = np.random.rand(n, D).astype(np.float32)
              label = (np.random.rand(n) * D).astype(np.int32)
              logger.info(
                  "Running benchmark for n = {}, D= {}".format(n, D)
              )
              ret = runOpBenchmark(gpu_do, op, inputs=[X, label])
              self.results.append(((n, D), ret[1]))
  
imports: import argparse
  import itertools
  import logging
  import os
  import numpy
  from caffe2.python import workspace, core
  from caffe2.python.hypothesis_test_util import runOpBenchmark, gpu_do
label_desc: Use image node_id 1 for calling the SoftMaxWithLoss obj's underlying member method code with example usage: obj.run() without return types