class_docstr: RBF kernel implementation.
class_docstr_tok: ["RBF","kernel","implementation","."]
code: def __init__(
      self,
      length_scale: float | tuple[float, ...] | np.ndarray = 1.0,
      length_scale_bounds: tuple[float, float]
      | list[tuple[float, float]]
      | np.ndarray = (1e-5, 1e5),
      operate_on: np.ndarray | None = None,
      has_conditions: bool = False,
      prior: AbstractPrior | None = None,
  ) -> None:
      super().__init__(
          operate_on=operate_on,
          has_conditions=has_conditions,
          prior=prior,
          length_scale=length_scale,
          length_scale_bounds=length_scale_bounds,
      )
  
file_path: SMAC3/smac/model/gaussian_process/kernels/rbf_kernel.py
imports: from __future__ import annotations
  import numpy
  import scipy.optimize
  import scipy.spatial.distance
  import scipy.special
  import sklearn.gaussian_process.kernels
  from smac.model.gaussian_process.kernels.base_kernels import AbstractKernel
  from smac.model.gaussian_process.priors.abstract_prior import AbstractPrior
label_desc: Use image node_id 1 to create a new RBFKernel object from inherited base classes: AbstractKernel, kernels with example: obj = RBFKernel(length_scale, length_scale_bounds, operate_on, has_conditions, prior)