parameters: (self, key_func, input_dataset)
docstring: Make wrapping defun for key_func.
docstring_summary: Make wrapping defun for key_func.
docstring_tokens: Make wrapping defun for key_func .
function: def _make_key_func(self, key_func, input_dataset):
      """Make wrapping defun for key_func."""
      self._key_func = dataset_ops.StructuredFunctionWrapper(
          key_func, self._transformation_name(), dataset=input_dataset)
      if not self._key_func.output_structure.is_compatible_with(
          tensor_spec.TensorSpec([], dtypes.int64)):
        raise ValueError(
            "`key_func` must return a single tf.int64 tensor. "
            "Got type=%s and shape=%s"
            % (self._key_func.output_types, self._key_func.output_shapes))
function_tokens: def _make_key_func ( self , key_func , input_dataset ) : self . _key_func = dataset_ops . StructuredFunctionWrapper ( key_func , self . _transformation_name ( ) , dataset = input_dataset ) if not self . _key_func . output_structure . is_compatible_with ( tensor_spec . TensorSpec ( [ ] , dtypes . int64 ) ) : raise ValueError ( "`key_func` must return a single tf.int64 tensor. " "Got type=%s and shape=%s" % ( self . _key_func . output_types , self . _key_func . output_shapes ) )