code: def result_type(*arrays_and_dtypes):
      """
      Returns the dtype that results from applying the type promotion rules to the arguments.
      Notes
      -----
      `result_type` is a standard API in
      https://data-apis.org/array-api/latest/API_specification/data_type_functions.html#result-type-arrays-and-dtypes
      instead of an official NumPy operator.
      Parameters
      ----------
      arrays_and_dtypes : mixed ndarrays and dtypes
          an arbitrary number of input arrays and/or dtypes.
      Returns
      -------
      out : dtype
          the dtype resulting from an operation involving the input arrays and dtypes.
      """
      if len(arrays_and_dtypes) > 0:
          ret = _get_dtype(arrays_and_dtypes[0])
          for d in arrays_and_dtypes[1:]:
              dd = _get_dtype(d)
              if (ret, dd) in _type_promotion_table:
                  ret = _type_promotion_table[ret, dd]
              elif (dd, ret) in _type_promotion_table:
                  ret = _type_promotion_table[dd, ret]
              else:
                  raise TypeError(
                      "Unknown type promotion between {} and {}".format(
                          ret, dd
                      )
                  )
          return ret
      raise ValueError("at least one array or dtype is required")
  
file_path: mxnet/python/mxnet/numpy/type_functions.py
imports: from typing import NamedTuple
  import numpy
  from .multiarray import ndarray
  from .utils import _type_promotion_table
label_desc: Use image node_id 5 for calling a global function with example usage: result_type() and returns: ret