code: def dataset_recorder_env(request):
      return Environment(
          train_dataset=small_toy_dataset,
          holdout_dataset=getattr(request, "param", None),
          metrics=["accuracy_score"],
          target_column="t",
          cv_params=dict(n_splits=4, shuffle=True, random_state=32),
          experiment_callbacks=[dataset_recorder()],
      )
  
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 13 for calling a global function with example usage: dataset_recorder_env(request) and returns: Environment