code: def test_get_chunk_n_rows(
      row_bytes, max_n_rows, working_memory, expected
  ):
      with warnings.catch_warnings():
          warnings.simplefilter("error", UserWarning)
          actual = get_chunk_n_rows(
              row_bytes=row_bytes,
              max_n_rows=max_n_rows,
              working_memory=working_memory,
          )
  
      assert actual == expected
      assert type(actual) is type(expected)
      with config_context(working_memory=working_memory):
          with warnings.catch_warnings():
              warnings.simplefilter("error", UserWarning)
              actual = get_chunk_n_rows(
                  row_bytes=row_bytes, max_n_rows=max_n_rows
              )
          assert actual == expected
          assert type(actual) is type(expected)
  
imports: import string
  import timeit
  import warnings
  from copy import copy
  from itertools import chain
  import numpy
  import pytest
  from sklearn import config_context
  from sklearn.utils import _approximate_mode, _determine_key_type, _get_column_indices, _is_polars_df, _message_with_time, _print_elapsed_time, _safe_assign, _safe_indexing, _to_object_array, check_random_state, column_or_1d, deprecated, gen_even_slices, get_chunk_n_rows, is_scalar_nan, resample, safe_mask, shuffle
  from sklearn.utils._mocking import MockDataFrame
  from sklearn.utils._testing import _convert_container, assert_allclose_dense_sparse, assert_array_equal, assert_no_warnings
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 33 for calling a global function with example usage: test_get_chunk_n_rows(row_bytes, max_n_rows, working_memory, expected) without return types