code: def test_io_dataset_in_dataset_parallel(
      fixture_lookup, io_dataset_fixture, num_parallel_calls
  ):
      """test_io_dataset_in_dataset_parallel"""
      args, func, expected = fixture_lookup(io_dataset_fixture)
  
      dataset = func(args)
  
      # Note: @tf.function is actually not needed, as tf.data.Dataset
      # will automatically wrap the `func` into a graph anyway.
      # The following is purely for explanation purposes.
      @tf.function
      def f(v):
          return func(v)
  
      args_dataset = tf.data.Dataset.from_tensor_slices([args, args])
  
      dataset = args_dataset.map(
          f, num_parallel_calls=num_parallel_calls
      )
  
      item = 0
      # Notice dataset in dataset:
      for d in dataset:
          i = 0
          for v in d:
              assert element_equal(expected[i], v)
              i += 1
          assert i == len(expected)
          item += 1
      assert item == 2
  
imports: import os
  import sys
  import time
  import shutil
  import tempfile
  import numpy
  import pytest
  import tensorflow
  import tensorflow_io
label_desc: Use image node_id 37 for calling a global function with example usage: test_io_dataset_in_dataset_parallel(fixture_lookup, io_dataset_fixture, num_parallel_calls) and returns: func