code: def test_intra_cv_engineer_experiment(
      dataset_recorder_env, experiment_fixture, end_data
  ):
      """Tests that original and transformed train/validation inputs for each fold are correct"""
      for f, datasets in enumerate(
          experiment_fixture.stat_aggregates["_datasets"][
              "on_fold_start"
          ]
      ):
          assert_frame_equal(
              datasets["data_train"].input.fold, end_data[0][f]
          )
          assert_frame_equal(
              datasets["data_oof"].input.fold, end_data[1][f]
          )
          assert_frame_equal(
              datasets["data_train"].input.T.fold, end_data[2][f]
          )
          assert_frame_equal(
              datasets["data_oof"].input.T.fold, end_data[3][f]
          )
  
imports: from hyperparameter_hunter import Environment, CVExperiment, FeatureEngineer, EngineerStep
  from hyperparameter_hunter.callbacks.recipes import dataset_recorder
  import numpy
  from numpy.testing import assert_array_almost_equal
  import pandas
  from pandas.testing import assert_frame_equal
  import pytest
  from sklearn.ensemble import AdaBoostClassifier
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 17 for calling a global function with example usage: test_intra_cv_engineer_experiment(dataset_recorder_env, experiment_fixture, end_data) without return types