code: def assert_sample_size_per_class(
      data, target_column_name, expected_samples_per_class
  ):
      count_per_class = Counter(data[target_column_name]).values()
  
      for count in count_per_class:
          assert (
              abs(count - expected_samples_per_class)
              <= MAX_STRATIFIED_SPLIT_SIZE_DIFFERENCE
          )
  
file_path: fklearn/tests/preprocessing/test_splitting.py
imports: from collections import Counter
  import hypothesis.strategies
  import pandas
  from hypothesis import given
  from hypothesis.extra.pandas import columns, data_frames, range_indexes
  from pandas.testing import assert_frame_equal
  from fklearn.preprocessing.splitting import space_time_split_dataset, time_split_dataset, stratified_split_dataset
label_desc: Use image node_id 4 for calling a global function with example usage: assert_sample_size_per_class(data, target_column_name, expected_samples_per_class) without return types