code: def _exact_predictive_covar_inv_quad_form_root(
      self, precomputed_cache, test_train_covar
  ):
      # Here the precomputed cache represents K_UU W S,
      # where S S^T = (K_XX + sigma^2 I)^-1
      test_interp_indices = test_train_covar.left_interp_indices
      test_interp_values = test_train_covar.left_interp_values
      res = left_interp(
          test_interp_indices, test_interp_values, precomputed_cache
      )
      return res
  
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 3 for calling the InterpolatedPredictionStrategy obj's underlying member method code with example usage: obj._exact_predictive_covar_inv_quad_form_root(precomputed_cache, test_train_covar) and returns: res