code: def forward(self, X: Tensor) -> Tensor:
      posterior = self.model.posterior(X)
      samples = self.get_posterior_samples(posterior)
      return self._compute_qehvi(samples=samples, X=X)
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Callable, List, Optional, Union
  import torch
  from botorch.acquisition.acquisition import AcquisitionFunction, MCSamplerMixin
  from botorch.acquisition.multi_objective.objective import IdentityMCMultiOutputObjective, MCMultiOutputObjective
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models.model import Model
  from botorch.models.transforms.input import InputPerturbation
  from botorch.sampling.base import MCSampler
  from botorch.utils.multi_objective.box_decompositions.non_dominated import NondominatedPartitioning
  from botorch.utils.multi_objective.hypervolume import NoisyExpectedHypervolumeMixin, SubsetIndexCachingMixin
  from botorch.utils.objective import compute_smoothed_feasibility_indicator
  from botorch.utils.transforms import concatenate_pending_points, is_ensemble, match_batch_shape, t_batch_mode_transform
  from torch import Tensor
label_desc: Use image node_id 3 for calling the qExpectedHypervolumeImprovement obj's underlying member method code with example usage: obj.forward(X) and returns: self