code: def _to_cat(index_ops: IndexOpsLike) -> IndexOpsLike:
      categories = cast(CategoricalDtype, index_ops.dtype).categories
      if len(categories) == 0:
          scol = F.lit(None)
      else:
          kvs = chain(
              *[
                  (F.lit(code), F.lit(category))
                  for code, category in enumerate(categories)
              ]
          )
          map_scol = F.create_map(*kvs)
          scol = map_scol[index_ops.spark.column]
      return index_ops._with_new_scol(scol)
  
imports: from itertools import chain
  from typing import cast, Any, Union
  import pandas
  import numpy
  from pandas.api.types import is_list_like, CategoricalDtype
  from pyspark.pandas._typing import Dtype, IndexOpsLike, SeriesOrIndex
  from pyspark.pandas.base import IndexOpsMixin
  from pyspark.pandas.data_type_ops.base import _sanitize_list_like, DataTypeOps
  from pyspark.pandas.typedef import pandas_on_spark_type
  from pyspark.sql import functions
  from pyspark.sql.utils import pyspark_column_op
label_desc: Use image node_id 2 for calling a global function with example usage: _to_cat(index_ops) and returns: index_ops