class_docstr: Sampling form the inverse of the metric volume element of a :class:`~pythae.models.RHVAE`
  model.
  
  Args:
      model (RHVAE): The VAE model to sample from
      sampler_config (RHVAESamplerConfig): A RHVAESamplerConfig instance containing the main
          parameters of the sampler. If None, a pre-defined configuration is used. Default: None
class_docstr_tok: ["Sampling","form","the","inverse","of","the","metric","volume","element","of","a",":","class",":","`","~pythae.models.RHVAE","`","model",".","Args",":","model","(","RHVAE",")",":","The","VAE","model","to","sample","from","sampler_config","(","RHVAESamplerConfig",")",":","A","RHVAESamplerConfig","instance","containing","the","main","parameters","of","the","sampler",".","If","None",",","a","pre-defined","configuration","is","used",".","Default",":","None"]
code: def tempering(k, K, beta_zero_sqrt):
      beta_k = (
          (1 - 1 / beta_zero_sqrt) * (k / K) ** 2
      ) + 1 / beta_zero_sqrt
  
      return 1 / beta_k
  
file_path: benchmark_VAE/src/pythae/samplers/manifold_sampler/rhvae_sampler.py
imports: import torch
  from ...models import RHVAE
  from ..base import BaseSampler
  from .rhvae_sampler_config import RHVAESamplerConfig
label_desc: Use image node_id 4 for calling the RHVAESampler obj's underlying member method code with example usage: obj.tempering(k, K, beta_zero_sqrt) and returns: unknown