code: def is_scipy_sparse(arr):
      """
      Check whether an array-like is a scipy.sparse.spmatrix instance.
  
      Parameters
      ----------
      arr : array-like
          The array-like to check.
  
      Returns
      -------
      boolean : Whether or not the array-like is a
                scipy.sparse.spmatrix instance.
  
      Notes
      -----
      If scipy is not installed, this function will always return False.
  
      Examples
      --------
      >>> from scipy.sparse import bsr_matrix
      >>> is_scipy_sparse(bsr_matrix([1, 2, 3]))
      True
      >>> is_scipy_sparse(pd.SparseArray([1, 2, 3]))
      False
      >>> is_scipy_sparse(pd.SparseSeries([1, 2, 3]))
      False
      """
  
      global _is_scipy_sparse
  
      if _is_scipy_sparse is None:
          try:
              from scipy.sparse import issparse as _is_scipy_sparse
          except ImportError:
              _is_scipy_sparse = lambda _: False
  
      return _is_scipy_sparse(arr)
  
imports: import warnings
  import numpy
  from pandas._libs import algos, lib
  from pandas._libs.tslibs import conversion
  from pandas.compat import PY3, PY36, string_types
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PandasExtensionDtype, PeriodDtype, registry
  from pandas.core.dtypes.generic import ABCCategorical, ABCDateOffset, ABCDatetimeIndex, ABCIndexClass, ABCPeriodArray, ABCPeriodIndex, ABCSeries
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, is_decimal, is_dict_like, is_file_like, is_float, is_hashable, is_integer, is_interval, is_iterator, is_list_like, is_named_tuple, is_nested_list_like, is_number, is_re, is_re_compilable, is_scalar, is_sequence, is_string_like
label_desc: Use image node_id 8 for calling a global function with example usage: is_scipy_sparse(arr) and returns: _is_scipy_sparse