class_docstr: Soft Tophat prior as it used in the original spearmint code.
  
  Parameters
  ----------
  lower_bound : float
      Lower bound of the prior. In original scale.
  upper_bound : float
      Upper bound of the prior. In original scale.
  exponent : float
      Exponent of the prior.
  seed : int, defaults to 0
code: def _get_log_probability(self, theta: float) -> float:
      return 0
  
imports: from __future__ import annotations
  from typing import Any
  import warnings
  import numpy
  from smac.model.gaussian_process.priors.abstract_prior import AbstractPrior
label_desc: Use image node_id 6 for calling the SoftTopHatPrior obj's underlying member method code with example usage: obj._get_log_probability(theta) and returns: int