parameters: (self, tensor_dict)
docstring: Maps Keras Tensors to computed Tensors using `tensor_dict`.
docstring_summary: Maps Keras Tensors to computed Tensors using `tensor_dict`.
docstring_tokens: Maps Keras Tensors to computed Tensors using tensor_dict .
function: def map_arguments(self, tensor_dict):
      """Maps Keras Tensors to computed Tensors using `tensor_dict`."""
      if self._single_positional_tensor_passed:
        # Performance optimization for most common case.
        kt_id, _ = self._keras_inputs_ids_and_indices[0]
        return (tensor_dict[kt_id].pop(),), {}
      else:
        flat_arguments = copy.copy(self._flat_arguments)
        for kt_id, kt_index in self._keras_inputs_ids_and_indices:
          flat_arguments[kt_index] = tensor_dict[kt_id].pop()
  
        args, kwargs = nest.pack_sequence_as((self.call_args, self.call_kwargs),
                                             flat_arguments)
        return args, kwargs
function_tokens: def map_arguments ( self , tensor_dict ) : if self . _single_positional_tensor_passed : # Performance optimization for most common case. kt_id , _ = self . _keras_inputs_ids_and_indices [ 0 ] return ( tensor_dict [ kt_id ] . pop ( ) , ) , { } else : flat_arguments = copy . copy ( self . _flat_arguments ) for kt_id , kt_index in self . _keras_inputs_ids_and_indices : flat_arguments [ kt_index ] = tensor_dict [ kt_id ] . pop ( ) args , kwargs = nest . pack_sequence_as ( ( self . call_args , self . call_kwargs ) , flat_arguments ) return args , kwargs