code: def test_verify_output_shape(self):
      obj = IdentityMCObjective()
      self.assertTrue(obj._verify_output_shape)
      samples = torch.zeros(2, 3, 1)
      X = torch.ones(2, 1)
      # No error if X is not given.
      obj(samples=samples)
      # Error if X is given, 2 != 3
      with self.assertRaises(RuntimeError):
          obj(samples=samples, X=X)
      # No error if _verify_output_shape=False
      obj._verify_output_shape = False
      obj(samples=samples, X=X)
  
imports: import itertools
  import warnings
  from typing import Optional
  import torch
  from botorch import settings
  from botorch.acquisition import LearnedObjective
  from botorch.acquisition.objective import ConstrainedMCObjective, DEFAULT_NUM_PREF_SAMPLES, ExpectationPosteriorTransform, GenericMCObjective, IdentityMCObjective, LEARNED_OBJECTIVE_PREF_MODEL_MIXED_DTYPE_WARN, LinearMCObjective, MCAcquisitionObjective, PosteriorTransform, ScalarizedPosteriorTransform
  from botorch.exceptions.errors import UnsupportedError
  from botorch.exceptions.warnings import _get_single_precision_warning, InputDataWarning
  from botorch.models.deterministic import PosteriorMeanModel
  from botorch.models.pairwise_gp import PairwiseGP
  from botorch.models.transforms.input import Normalize
  from botorch.posteriors import GPyTorchPosterior
  from botorch.utils import apply_constraints
  from botorch.utils.testing import _get_test_posterior, BotorchTestCase
  from gpytorch.distributions import MultitaskMultivariateNormal, MultivariateNormal
  from linear_operator.operators.dense_linear_operator import to_linear_operator
  from torch import Tensor
label_desc: Use image node_id 2 for calling the TestMCAcquisitionObjective obj's underlying member method code with example usage: obj.test_verify_output_shape() without return types