class_docstr: Horseshoe Prior as it is used in spearmint.
  
  Parameters
  ----------
  scale: float
      Scaling parameter.
  seed : int, defaults to 0
class_docstr_tok: ["Horseshoe","Prior","as","it","is","used","in","spearmint",".","Parameters","--","--","--","--","--","scale",":","float","Scaling","parameter",".","seed",":","int",",","defaults","to","0"]
code: def _sample_from_prior(self, n_samples: int) -> np.ndarray:
      # This is copied from RoBO - scale is most likely the tau parameter
      lamda = np.abs(self._rng.standard_cauchy(size=n_samples))
      p0 = np.abs(self._rng.randn() * lamda * self._scale)
      return p0
  
file_path: SMAC3/smac/model/gaussian_process/priors/horseshoe_prior.py
imports: from __future__ import annotations
  from typing import Any
  import math
  import numpy
  from smac.constants import VERY_SMALL_NUMBER
  from smac.model.gaussian_process.priors.abstract_prior import AbstractPrior
label_desc: Use image node_id 3 for calling the HorseshoePrior obj's underlying member method code with example usage: obj._sample_from_prior(n_samples) and returns: p0