code: def inducingpoint_wrapper(
      inducing_variable: InducingVariablesLike,
  ) -> InducingVariables:
      """
      This wrapper allows transparently passing either an InducingVariables
      object or an array specifying InducingPoints positions.
      """
      if not isinstance(inducing_variable, InducingVariables):
          inducing_variable = InducingPoints(inducing_variable)
      return inducing_variable
  
file_path: GPflow/gpflow/models/util.py
imports: from typing import Any, Callable, Sequence, Union
  import numpy
  import tensorflow
  from check_shapes import check_shapes
  from ..base import AnyNDArray
  from ..config import default_float
  from ..inducing_variables import InducingPoints, InducingVariables
  from .model import BayesianModel
  from .training_mixins import Data, ExternalDataTrainingLossMixin
label_desc: Use image node_id 1 for calling a global function with example usage: inducingpoint_wrapper(inducing_variable) and returns: inducing_variable