code: def custom_error_split(df):
      from pandas import Series
  
      splits = Series(SplitValues.TRAINING.value, index=range(len(df)))
      splits[df["a"] >= 500] = "VALIDATE"
      splits[df["a"] >= 800] = "TESTING"
  
      return splits
  
imports: from pathlib import Path
  from unittest import mock
  from unittest.mock import Mock
  import numpy
  import pandas
  import pytest
  import mlflow
  from mlflow.environment_variables import MLFLOW_RECIPES_EXECUTION_DIRECTORY
  from mlflow.exceptions import MlflowException
  from mlflow.recipes.steps.split import _OUTPUT_TEST_FILE_NAME, _OUTPUT_TRAIN_FILE_NAME, _OUTPUT_VALIDATION_FILE_NAME, SplitStep, SplitValues, _get_split_df, _hash_pandas_dataframe, _make_elem_hashable, _validate_user_code_output
  from mlflow.recipes.utils import _RECIPE_CONFIG_FILE_NAME
  from mlflow.utils.file_utils import read_yaml
label_desc: Use image node_id 13 for calling a global function with example usage: custom_error_split(df) and returns: splits