// Guard area size to use near thread stacks to use (in bytes), zero implies
  // that the system default will be used.
  size_t guard_size;

  // The NUMA node to use, -1 implies that there should be no NUMA affinity for
  // this thread.
  int numa_node;
} TF_ThreadOptions;

// Creates the specified directory. Typical status code are:
//  * TF_OK - successfully created the directory

      'mkl_aarch64',
      'Build with oneDNN and Compute Library for the Arm Architecture (ACL).')
  config_info_line('monolithic', 'Config for mostly static monolithic build.')
  config_info_line('numa', 'Build with NUMA support.')
  config_info_line(
      'dynamic_kernels',
      '(Experimental) Build kernels into separate shared objects.')
  config_info_line('v1', 'Build with TensorFlow 1 API instead of TF 2 API.')

  options->guard_size = 0;
  options->numa_node = -1;
}

TF_Thread* TF_StartThread(const TF_ThreadOptions* options,
                          const char* thread_name, void (*work_func)(void*),
                          void* param) {
  ::tensorflow::ThreadOptions cc_options;
  cc_options.stack_size = options->stack_size;
  cc_options.guard_size = options->guard_size;
  cc_options.numa_node = options->numa_node;

    *   Extending the TF 2.0 support for `shuffle(...,
        reshuffle_each_iteration=True)` and `cache()` to work across different
        Python iterators for the same dataset.
    *   Removing the `experimental_numa_aware` option from `tf.data.Options`.
    *   Add `num_parallel_reads` and passing in a Dataset containing filenames
        into `TextLineDataset` and `FixedLengthRecordDataset`.