code: def _make_tabular_X(
      n_instances=20, n_columns=1, return_numpy=True, random_state=None
  ):
      """Generate tabular X, for checking inverse-transform."""
      rng = check_random_state(random_state)
      X = rng.rand(n_instances, n_columns)
      if return_numpy:
          return X
      else:
          return pd.DataFrame(X)
  
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 4 for calling a global function with example usage: _make_tabular_X(n_instances, n_columns, return_numpy, random_state) and returns: X, pd