code: def check_memory(memory):
      """Check that ``memory`` is joblib.Memory-like.
  
      joblib.Memory-like means that ``memory`` can be converted into a
      joblib.Memory instance (typically a str denoting the ``location``)
      or has the same interface (has a ``cache`` method).
  
      Parameters
      ----------
      memory : None, str or object with the joblib.Memory interface
          - If string, the location where to create the `joblib.Memory` interface.
          - If None, no caching is done and the Memory object is completely transparent.
  
      Returns
      -------
      memory : object with the joblib.Memory interface
          A correct joblib.Memory object.
  
      Raises
      ------
      ValueError
          If ``memory`` is not joblib.Memory-like.
      """
      if memory is None or isinstance(memory, str):
          memory = joblib.Memory(location=memory, verbose=0)
      elif not hasattr(memory, "cache"):
          raise ValueError(
              "'memory' should be None, a string or have the same"
              " interface as joblib.Memory."
              " Got memory='{}' instead.".format(memory)
          )
      return memory
  
imports: import numbers
  import operator
  import warnings
  from contextlib import suppress
  from functools import reduce, wraps
  from inspect import Parameter, isclass, signature
  import joblib
  import numpy
  import scipy.sparse
  from ..None import get_config
  from ..exceptions import DataConversionWarning, NotFittedError, PositiveSpectrumWarning
  from ..utils._array_api import _asarray_with_order, _is_numpy_namespace, get_namespace
  from ..utils.fixes import ComplexWarning
  from ._isfinite import FiniteStatus, cy_isfinite
  from .fixes import _object_dtype_isnan
label_desc: Use image node_id 10 for calling a global function with example usage: check_memory(memory) and returns: memory