code: def _convert_to_output_function(
      input_data: InputData,
      transformed_features: np.ndarray,
      data_type: DataTypesEnum = DataTypesEnum.table,
  ):
      """Function prepare prediction of operation as OutputData object
  
      :param input_data: data with features, target and ids to process
      :param transformed_features: transformed features
      :param data_type: type of output data
      """
  
      # After preprocessing operations by default we get tabular data
      converted = OutputData(
          idx=input_data.idx,
          features=input_data.features,
          predict=transformed_features,
          task=input_data.task,
          target=input_data.target,
          data_type=data_type,
          supplementary_data=input_data.supplementary_data,
      )
  
      return converted
  
imports: from abc import ABC, abstractmethod
  from copy import deepcopy
  from typing import Optional
  import numpy
  from golem.core.log import default_log
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.utilities.custom_errors import AbstractMethodNotImplementError
label_desc: Use image node_id 1 for calling a global function with example usage: _convert_to_output_function(input_data, transformed_features, data_type) and returns: converted