code: def indexable(*iterables, session=None, run_kwargs=None):
      """Make arrays indexable for cross-validation.
  
      Checks consistent length, passes through None, and ensures that everything
      can be indexed by converting sparse matrices to csr and converting
      non-interable objects to arrays.
  
      Parameters
      ----------
      *iterables : lists, dataframes, arrays, sparse matrices
          List of objects to ensure sliceability.
      """
      result = [_make_indexable(X) for X in iterables]
      check_consistent_length(
          *result, session=session, run_kwargs=run_kwargs
      )
      return result
  
imports: import warnings
  import numbers
  import numpy
  from numpy.core.numeric import ComplexWarning
  from ...None import dataframe
  from ...None import tensor
  from ...core import ExecutableTuple
  from ...lib.sparse import issparse
  from ...tensor import Tensor
  from .checks import check_non_negative_then_return_value, assert_all_finite, AssertAllFinite
label_desc: Use image node_id 4 for calling a global function with example usage: indexable() and returns: result