code: def get_eval_gp_sample_callable(
      w: Tensor, basis: RandomFourierFeatures
  ) -> Tensor:
      def _f(X):
          return basis(X) @ w.unsqueeze(-1)
  
      return _f
  
imports: from __future__ import annotations
  from copy import deepcopy
  from math import pi
  from typing import List, Optional
  import torch
  from botorch.models.converter import batched_to_model_list
  from botorch.models.deterministic import GenericDeterministicModel
  from botorch.models.model import Model, ModelList
  from botorch.models.model_list_gp_regression import ModelListGP
  from botorch.models.multitask import MultiTaskGP
  from botorch.utils.sampling import manual_seed
  from botorch.utils.transforms import is_ensemble
  from gpytorch.kernels import Kernel, MaternKernel, RBFKernel, ScaleKernel
  from linear_operator.utils.cholesky import psd_safe_cholesky
  from torch import Tensor
  from torch.distributions import MultivariateNormal
  from torch.nn import Module
label_desc: Use image node_id 2 for calling a global function with example usage: get_eval_gp_sample_callable(w, basis) and returns: _f, unknown