code: def _result_type_binary(
      t1, t2
  ):  # pylint: disable=missing-function-docstring
      """A specialization of result_type for 2 arguments for performance reasons."""
      try:
          return np_dtypes._result_type(  # pylint: disable=protected-access
              _maybe_get_dtype(t1),
              _maybe_get_dtype(t2),
          )
      except ValueError:
          return result_type(t1, t2)
  
imports: import inspect
  import numbers
  import os
  import re
  import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import flexible_dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.numpy_ops import np_arrays
  from tensorflow.python.ops.numpy_ops import np_dtypes
  from tensorflow.python.types import core
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_export
label_desc: Use image node_id 27 for calling a global function with example usage: _result_type_binary(t1, t2) and returns: np_dtypes, result_type