code: def main(_):
      print("Sparse Xent vs. SparseToDense + Xent")
      print(
          "batch \t depth \t gpu \t dt(dense) \t dt(sparse) "
          "\t dt(sparse)/dt(dense)"
      )
      for use_gpu in (False, True):
          for batch_size in (32, 64, 128):
              for num_entries in (100, 1000, 10000):
                  sparse_vs_dense_xent_benchmark(
                      batch_size, num_entries, use_gpu
                  )
          sparse_vs_dense_xent_benchmark(32, 100000, use_gpu)
          sparse_vs_dense_xent_benchmark(8, 1000000, use_gpu)
  
file_path: tensorflow-upstream/tensorflow/python/kernel_tests/sparse_ops/sparse_xent_op_test.py
imports: import sys
  import time
  from absl import app
  import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.kernel_tests.sparse_ops import sparse_xent_op_test_base
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.ops.nn_grad import _SparseSoftmaxCrossEntropyWithLogitsGrad
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling a global function with example usage: main(_) without return types