code: def test_make_divisions_ensure_minimum_rows():
      from ludwig.data.split import _make_divisions_ensure_minimum_rows
  
      # Constraints are satisfied, the function should make no change to divisions.
      divisions = _make_divisions_ensure_minimum_rows(
          (70, 80), 100, min_val_rows=3, min_test_rows=3
      )
      assert divisions[0] == 70
      assert divisions[1] == 80
      # Constraints are satisfied, the function should make no change to divisions.
      divisions = _make_divisions_ensure_minimum_rows(
          (20, 22), 25, min_val_rows=0, min_test_rows=0
      )
      assert divisions[0] == 20
      assert divisions[1] == 22
      # The number of rows in validation set is too small.
      divisions = _make_divisions_ensure_minimum_rows(
          (17, 19), 25, min_val_rows=3, min_test_rows=3
      )
      assert divisions[0] == 16
      assert divisions[1] == 19
      # The number of rows in validation and test sets are both too small.
      divisions = _make_divisions_ensure_minimum_rows(
          (20, 22), 25, min_val_rows=3, min_test_rows=3
      )
      assert divisions[0] == 19
      assert divisions[1] == 22
  
file_path: ludwig/tests/ludwig/data/test_split.py
imports: from datetime import datetime, timedelta
  from itertools import combinations
  from random import randrange
  from unittest.mock import Mock
  import numpy
  import pandas
  import pytest
  from ludwig.data.dataframe.pandas import PandasEngine
  from ludwig.data.split import get_splitter
label_desc: Use image node_id 1 for calling a global function with example usage: test_make_divisions_ensure_minimum_rows() without return types