code: def test_parallel_validator(data):
      result = parallel_validator(
          data, split_fn, train_fn, eval_fn, n_jobs=2
      )
  
      validator_log = result["validator_log"]
  
      assert len(validator_log) == 2
      assert validator_log[0]["fold_num"] == 0
      assert result["train_log"][0]["xgb_classification_learner"][
          "features"
      ] == ["f1"]
  
      assert len(validator_log[0]["eval_results"]) == 3
  
      assert validator_log[1]["fold_num"] == 1
      assert len(validator_log[1]["eval_results"]) == 1
  
file_path: fklearn/tests/validation/test_validator.py
imports: import warnings
  from datetime import datetime, timedelta
  import pandas
  from toolz.functoolz import identity
  from fklearn.training.classification import lgbm_classification_learner
  from fklearn.validation import splitters, evaluators
  from fklearn.validation.validator import validator_iteration, validator, parallel_validator
  from fklearn.validation.perturbators import perturbator, nullify
  import pytest
label_desc: Use image node_id 8 for calling a global function with example usage: test_parallel_validator(data) without return types