code: def get_weighted_val(ei_val, prob, exponent, use_log):
      if use_log:
          return prob * exponent + ei_val
      return prob.pow(exponent) * ei_val
  
file_path: botorch/test/acquisition/test_prior_guided.py
imports: from itertools import product
  import torch
  from botorch.acquisition.analytic import ExpectedImprovement
  from botorch.acquisition.monte_carlo import qExpectedImprovement
  from botorch.acquisition.prior_guided import PriorGuidedAcquisitionFunction
  from botorch.models import SingleTaskGP
  from botorch.utils.testing import BotorchTestCase
  from botorch.utils.transforms import match_batch_shape
  from torch.nn import Module
label_desc: Use image node_id 2 for calling a global function with example usage: get_weighted_val(ei_val, prob, exponent, use_log) and returns: unknown, unknown