class_docstr: Abstract class for preparing data in order to train a surrogate model.
  
  Parameters
  ----------
  scenario : Scenario object.
  considered_states : list[StatusType], defaults to [StatusType.SUCCESS, StatusType.CRASHED, StatusType.MEMORYOUT]  # noqa: E501
      Trials with the passed states are considered.
  lower_budget_states : list[StatusType], defaults to []
      Additionally consider all trials with these states for budget < current budget.
  scale_percentage : int, defaults to 5
      Scaled y-transformation use a percentile to estimate distance to optimum. Only used in some sub-classes.
  seed : int | None, defaults to none
  
  Raises
  ------
  TypeError
      If no success states are given.
docstr: Returns the meta-data of the created object.
  
  Returns
  -------
  dict[str, Any]: meta-data of the created object: name, considered states, lower budget
  states, scale_percentage, seed.
docstr_tok: ["Returns","the","meta-data","of","the","created","object",".","Returns","--","--","--","-","dict","[","str",",","Any","]",":","meta-data","of","the","created","object",":","name",",","considered","states",",","lower","budget","states",",","scale_percentage",",","seed","."]
code: def meta(self) -> dict[str, Any]:
      """
      Returns the meta-data of the created object.
  
      Returns
      -------
      dict[str, Any]: meta-data of the created object: name, considered states, lower budget
      states, scale_percentage, seed.
      """
      return {
          "name": self.__class__.__name__,
          "considered_states": self._considered_states,
          "lower_budget_states": self._lower_budget_states,
          "scale_percentage": self._scale_percentage,
          "seed": self._seed,
      }
  
imports: from __future__ import annotations
  from abc import abstractmethod
  from typing import Any, Mapping
  import numpy
  from smac.multi_objective import AbstractMultiObjectiveAlgorithm
  from smac.runhistory.runhistory import RunHistory, TrialKey, TrialValue
  from smac.runner.abstract_runner import StatusType
  from smac.scenario import Scenario
  from smac.utils.configspace import convert_configurations_to_array
  from smac.utils.logging import get_logger
label_desc: Use image node_id 2 for calling the AbstractRunHistoryEncoder obj's underlying member method code with example usage: obj.meta() and returns: dict