code: def covar_cache(self):
      train_train_covar = self.lik_train_train_covar
      train_train_covar_inv_root = to_dense(
          train_train_covar.root_inv_decomposition().root
      )
      return self._exact_predictive_covar_inv_quad_form_cache(
          train_train_covar_inv_root, self._last_test_train_covar
      )
  
imports: import functools
  import string
  import warnings
  import torch
  from linear_operator import to_dense, to_linear_operator
  from linear_operator.operators import AddedDiagLinearOperator, BatchRepeatLinearOperator, ConstantMulLinearOperator, DenseLinearOperator, InterpolatedLinearOperator, LinearOperator, LowRankRootAddedDiagLinearOperator, MaskedLinearOperator, MatmulLinearOperator, RootLinearOperator, ZeroLinearOperator
  from linear_operator.utils.cholesky import psd_safe_cholesky
  from linear_operator.utils.interpolation import left_interp, left_t_interp
  from torch import Tensor
  from ..None import settings
  from ..distributions import MultitaskMultivariateNormal
  from ..lazy import LazyEvaluatedKernelTensor
  from ..utils.memoize import add_to_cache, cached, clear_cache_hook, pop_from_cache
label_desc: Use image node_id 6 for calling the DefaultPredictionStrategy obj's underlying member method code with example usage: obj.covar_cache() and returns: self