class_docstr: Linear Elliptical Slice Sampler.
  
  Ideas:
  - Add batch support, broadcasting over parallel chains.
  - Optimize computations if possible, potentially with torch.compile.
  - Extend fixed features constraint to general linear equality constraints.
class_docstr_tok: ["Linear","Elliptical","Slice","Sampler",".","Ideas",":","-","Add","batch","support",",","broadcasting","over","parallel","chains",".","-","Optimize","computations","if","possible",",","potentially","with","torch.compile",".","-","Extend","fixed","features","constraint","to","general","linear","equality","constraints","."]
docstr: The total number of samples generated by the sampler during its lifetime.
docstr_tok: ["The","total","number","of","samples","generated","by","the","sampler","during","its","lifetime","."]
code: def lifetime_samples(self) -> int:
      """The total number of samples generated by the sampler during its lifetime."""
      return self._lifetime_samples
  
imports: from __future__ import annotations
  import math
  from typing import List, Optional, Tuple, Union
  import torch
  from botorch.utils.sampling import PolytopeSampler
  from torch import Tensor
label_desc: Use image node_id 4 for calling the LinearEllipticalSliceSampler obj's underlying member method code with example usage: obj.lifetime_samples() and returns: self