code: def __init__(
      self,
      train_inputs,
      train_prior_dist,
      train_labels,
      likelihood,
      uses_wiski=False,
  ):
      train_prior_dist = train_prior_dist.__class__(
          train_prior_dist.mean,
          train_prior_dist.lazy_covariance_matrix.evaluate_kernel(),
      )
      super().__init__(
          train_inputs, train_prior_dist, train_labels, likelihood
      )
      # covar = self.train_prior_dist.lazy_covariance_matrix.evaluate_kernel()
      # if isinstance(covar, LazyEvaluatedKernelTensor):
      #     covar = covar.evaluate_kernel()
      # self.train_prior_dist = self.train_prior_dist.__class__(
      #     self.train_prior_dist.mean, covar
      # )
      self.uses_wiski = uses_wiski
  
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 1 to create a new InterpolatedPredictionStrategy object from inherited base classes: DefaultPredictionStrategy with example: obj = InterpolatedPredictionStrategy(train_inputs, train_prior_dist, train_labels, likelihood, uses_wiski)