code: def normalize_point_columns(*cols):
      """
      Normalize the input columns by inferring a common floating point dtype.
  
      If the common dtype isn't a floating point dtype, promote the common dtype
      to float64.
  
      Parameters
      ----------
      {params}
  
      Returns
      -------
      tuple : the input columns cast to the inferred common floating point dtype
      """
      dtype = np.result_type(*cols)
      if not np.issubdtype(dtype, np.floating):
          dtype = np.float32 if dtype.itemsize <= 4 else np.float64
      return (x.astype(dtype) for x in cols)
  
file_path: cuspatial/python/cuspatial/cuspatial/utils/column_utils.py
imports: from typing import TypeVar
  import numpy
  from cudf.api.types import is_datetime_dtype
  from cudf.core.column.column import column_empty
  from cuspatial.core._column.geometa import Feature_Enum
  from cuspatial.core.dtypes import linestring_dtype, multipoint_dtype, point_dtype, polygon_dtype
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_point_columns() and returns: unknown