code: def test_raises_for_quality_function_with_invalid_shape(self):
      inputs = torch.rand(15, 1, device=self.device)
      with torch.no_grad():
          train_train_kernel = (
              MaternKernel().to(self.device)(inputs).evaluate_kernel()
          )
      quality_scores = torch.ones([10, 1], device=self.device)
      with self.assertRaisesRegex(
          ValueError, ".*requires a quality score"
      ):
          _pivoted_cholesky_init(
              train_inputs=inputs,
              kernel_matrix=train_train_kernel,
              max_length=10,
              quality_scores=quality_scores,
          )
  
imports: import gc
  import torch
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models.approximate_gp import SingleTaskVariationalGP
  from botorch.models.utils.inducing_point_allocators import _pivoted_cholesky_init, ExpectedImprovementQualityFunction, GreedyImprovementReduction, GreedyVarianceReduction, UnitQualityFunction
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.kernels import MaternKernel, ScaleKernel
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.mlls import VariationalELBO
label_desc: Use image node_id 1 for calling the TestPivotedCholeskyInit obj's underlying member method code with example usage: obj.test_raises_for_quality_function_with_invalid_shape() without return types