code: def _make_primitives(n_columns=1, random_state=None):
      """Generate one or more primitives, for checking inverse-transform."""
      rng = check_random_state(random_state)
      if n_columns == 1:
          return rng.rand()
      return rng.rand(size=(n_columns,))
  
imports: from inspect import isclass, signature
  import numpy
  import pandas
  from pandas.testing import assert_frame_equal
  from sklearn.utils.validation import check_random_state
  from sktime.alignment.base import BaseAligner
  from sktime.base import BaseEstimator, BaseObject
  from sktime.classification.base import BaseClassifier
  from sktime.classification.early_classification import BaseEarlyClassifier
  from sktime.clustering.base import BaseClusterer
  from sktime.datatypes._panel._check import is_nested_dataframe
  from sktime.dists_kernels import BasePairwiseTransformer, BasePairwiseTransformerPanel
  from sktime.forecasting.base import BaseForecaster
  from sktime.registry import scitype
  from sktime.regression.base import BaseRegressor
  from sktime.tests._config import VALID_ESTIMATOR_TYPES
  from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 3 for calling a global function with example usage: _make_primitives(n_columns, random_state) and returns: rng, rng