code: def test_match_batch_shape(self):
      X = torch.rand(3, 2)
      Y = torch.rand(1, 3, 2)
      X_tf = match_batch_shape(X, Y)
      self.assertTrue(torch.equal(X_tf, X.unsqueeze(0)))
  
      X = torch.rand(1, 3, 2)
      Y = torch.rand(2, 3, 2)
      X_tf = match_batch_shape(X, Y)
      self.assertTrue(torch.equal(X_tf, X.repeat(2, 1, 1)))
  
      X = torch.rand(2, 3, 2)
      Y = torch.rand(1, 3, 2)
      with self.assertRaises(RuntimeError):
          match_batch_shape(X, Y)
  
imports: from typing import Any
  import torch
  from botorch.models import GenericDeterministicModel, HigherOrderGP, ModelList, PairwiseGP, SaasFullyBayesianSingleTaskGP, SingleTaskGP
  from botorch.models.fully_bayesian_multitask import SaasFullyBayesianMultiTaskGP
  from botorch.models.gp_regression_fidelity import SingleTaskMultiFidelityGP
  from botorch.models.gp_regression_mixed import MixedSingleTaskGP
  from botorch.models.model import Model
  from botorch.models.multitask import MultiTaskGP
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
  from botorch.utils.transforms import _verify_output_shape, concatenate_pending_points, is_ensemble, is_fully_bayesian, match_batch_shape, normalize, normalize_indices, standardize, t_batch_mode_transform, unnormalize
  from torch import Tensor
label_desc: Use image node_id 1 for calling the TestMatchBatchShape obj's underlying member method code with example usage: obj.test_match_batch_shape() without return types