code: def test_results_queue_size_propagation_in_make_batch_reader(
      scalar_dataset,
  ):
      expected_results_queue_size = 42
      with make_batch_reader(
          scalar_dataset.url,
          reader_pool_type="thread",
          results_queue_size=expected_results_queue_size,
      ) as batch_reader:
          actual_results_queue_size = (
              batch_reader._workers_pool._results_queue_size
          )
      assert actual_results_queue_size == expected_results_queue_size
  
imports: import glob
  import itertools
  import numpy
  import pandas
  import pytest
  from pyarrow import parquet
  from petastorm import make_batch_reader, make_reader
  from petastorm.arrow_reader_worker import ArrowReaderWorker
  from petastorm.tests.test_common import create_test_scalar_dataset
  from petastorm.transform import TransformSpec
  from petastorm.unischema import UnischemaField
label_desc: Use image node_id 15 for calling a global function with example usage: test_results_queue_size_propagation_in_make_batch_reader(scalar_dataset) without return types