code: def combined_datasets_strategy(*datasets, name=None, doc=None):
      """
      Combine multiple datasets strategies into a single datasets strategy.
  
      This function will return a new strategy that will build the provided
      strategy functions with the common parameters (dtypes, n_samples,
      n_features) and then draw from one of them.
  
      Parameters:
      -----------
      * datasets: list[Callable[[dtypes, n_samples, n_features], SearchStrategy]]
          A list of functions that return a dataset search strategy when called
          with the shown arguments.
      name: The name of the returned search strategy, default="datasets"
          Defaults to a combination of names of the provided dataset strategy
          functions.
      doc: The doc-string of the returned search strategy, default=None
          Defaults to a generic doc-string.
  
      Returns
      -------
      Datasets search strategy: SearchStrategy[array], SearchStrategy[array]
      """
  
      @composite
      def strategy(
          draw,
          dtypes=floating_dtypes(),
          n_samples=integers(min_value=0, max_value=200),
          n_features=integers(min_value=0, max_value=200),
      ):
          """Datasets strategy composed of multiple datasets strategies."""
          datasets_strategies = (
              dataset(dtypes, n_samples, n_features)
              for dataset in datasets
          )
          return draw(one_of(datasets_strategies))
  
      strategy.__name__ = "datasets" if name is None else name
      if doc is not None:
          strategy.__doc__ = doc
  
      return strategy
  
imports: from cuml.internals.array import CumlArray
  from cuml.internals.safe_imports import cpu_only_import, gpu_only_import
  from hypothesis import assume
  from hypothesis.extra.numpy import array_shapes, arrays, floating_dtypes, integer_dtypes
  from hypothesis.strategies import composite, integers, just, none, one_of, sampled_from
  from sklearn.datasets import make_classification, make_regression
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 13 for calling a global function with example usage: combined_datasets_strategy() and returns: strategy, draw