class_docstr: Class to execute target functions which are python functions. Evaluates function for given
  configuration and resource limit.
  
  The target function can either return a float (the loss), or a tuple with the first element
  being a float and the second being additional run information. In a multi-objective
  setting, the float value is replaced by a list of floats.
  
  Parameters
  ----------
  target_function : Callable
      The target function.
  scenario : Scenario
  required_arguments : list[str], defaults to []
      A list of required arguments, which are passed to the target function.
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code: def meta(self) -> dict[str, Any]:  # noqa: D102
      meta = super().meta
  
      # Partial's don't have a __code__ attribute but are a convenient
      # way a user might want to pass a function to SMAC, specifying
      # keyword arguments.
      f = self._target_function
      if isinstance(f, partial):
          f = f.func
          meta.update({"code": str(f.__code__.co_code)})
          meta.update({"code-partial-args": repr(f)})
      else:
          meta.update(
              {"code": str(self._target_function.__code__.co_code)}
          )
  
      return meta
  
imports: from __future__ import annotations
  from typing import Any, Callable
  import copy
  import inspect
  import math
  import time
  import traceback
  from functools import partial
  import numpy
  from ConfigSpace import Configuration
  from pynisher import MemoryLimitException, WallTimeoutException, limit
  from smac.runner.abstract_runner import StatusType
  from smac.runner.abstract_serial_runner import AbstractSerialRunner
  from smac.scenario import Scenario
  from smac.utils.logging import get_logger
label_desc: Use image node_id 2 for calling the TargetFunctionRunner obj's underlying member method code with example usage: obj.meta() and returns: meta