class_docstr: Fast predictive variances using Lanczos Variance Estimates (LOVE)
  Use this for improved performance when computing predictive variances.
  
  As described in the paper:
  
  `Constant-Time Predictive Distributions for Gaussian Processes`_.
  
  See also: :class:`gpytorch.settings.max_root_decomposition_size` (to control the
  size of the low rank decomposition used for variance estimates).
  
  (Default: False)
  
  .. _`Constant-Time Predictive Distributions for Gaussian Processes`:
      https://arxiv.org/pdf/1803.06058.pdf
class_docstr_tok: ["Fast","predictive","variances","using","Lanczos","Variance","Estimates","(","LOVE",")","Use","this","for","improved","performance","when","computing","predictive","variances",".","As","described","in","the","paper",":","`","Constant-Time","Predictive","Distributions","for","Gaussian","Processes","`","_",".","See","also",":",":","class",":","`","gpytorch.settings.max_root_decomposition_size","`","(","to","control","the","size","of","the","low","rank","decomposition","used","for","variance","estimates",")",".","(","Default",":","False",")","..","_","`","Constant-Time","Predictive","Distributions","for","Gaussian","Processes","`",":","https",":","\/\/arxiv.org\/pdf\/1803.06058.pdf"]
code: def __init__(self, state=True, num_probe_vectors=1):
      self.orig_value = self.__class__.num_probe_vectors()
      self.value = num_probe_vectors
      super().__init__(state)
  
imports: import torch
  from linear_operator.settings import _linalg_dtype_cholesky, _linalg_dtype_symeig, cg_tolerance, cholesky_jitter, cholesky_max_tries, ciq_samples, deterministic_probes, fast_computations, linalg_dtypes, max_cg_iterations, max_cholesky_size, max_lanczos_quadrature_iterations, max_preconditioner_size, max_root_decomposition_size, min_preconditioning_size, minres_tolerance, num_contour_quadrature, num_trace_samples, preconditioner_tolerance, skip_logdet_forward, terminate_cg_by_size, tridiagonal_jitter, use_toeplitz, verbose_linalg
  from torch import Tensor
label_desc: Use image node_id 3 to create a new fast_pred_var object from inherited base classes: _feature_flag with example: obj = fast_pred_var(state, num_probe_vectors)