code: def main(_):
      print(
          "DenseDense MatMul (w/ Sparse Flag) vs. SparseTensorDense MatMul"
      )
      print("Matrix sizes:")
      print(
          "  A sparse [m, k] with % nonzero values between 1% and 80%"
      )
      print("  B dense [k, n]")
      print("")
      print(
          "% nnz \t n \t gpu \t m \t k \t dt(dense) \t dt(sparse) "
          "\t dt(sparse)/dt(dense)"
      )
  
      for thresh in (0.99, 0.8, 0.5, 0.2):
          for n in (50, 100):
              for use_gpu in (True, False):
                  for m in (100, 1000):
                      for k in (100, 1000):
                          sparse_tensor_dense_vs_dense_matmul_benchmark(
                              thresh,
                              m,
                              k,
                              n,
                              False,
                              False,
                              use_gpu=use_gpu,
                          )
  
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 constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling a global function with example usage: main(_) without return types