class_docstr: Interleave a random configuration according to a given probability which is decreased over time.
  
  Parameters
  ----------
  probability : float
      Probability that a configuration will be drawn at random.
  factor : float
      Multiply the `probability` by `factor` in each iteration.
  seed : int, defaults to 0
      Integer used to initialize the random state.
code: def meta(self) -> dict[str, Any]:  # noqa: D102
      meta = super().meta
      meta.update(
          {"probability": self._probability, "factor": self._factor}
      )
  
      return meta
  
file_path: SMAC3/smac/random_design/probability_design.py
imports: from __future__ import annotations
  from typing import Any
  from smac.random_design.abstract_random_design import AbstractRandomDesign
  from smac.utils.logging import get_logger
label_desc: Use image node_id 2 for calling the DynamicProbabilityRandomDesign obj's underlying member method code with example usage: obj.meta() and returns: meta