code: def test_predict_wrong_X_dimensions():
      seed = 1
      rs = np.random.RandomState(seed)
      model = get_gp(10, seed)
  
      X = rs.rand(10)
      with pytest.raises(ValueError, match="Expected 2d array.*"):
          model.predict(X)
  
      X = rs.rand(10, 10, 10)
      with pytest.raises(ValueError, match="Expected 2d array.*"):
          model.predict(X)
  
      X = rs.rand(10, 5)
      with pytest.raises(ValueError, match="Feature mismatch.*"):
          model.predict(X)
  
file_path: SMAC3/tests/test_model/test_gp_mcmc.py
imports: from unittest.mock import patch
  import numpy
  import pytest
  import sklearn.datasets
  import sklearn.model_selection
  from ConfigSpace import ConfigurationSpace, UniformFloatHyperparameter
  from smac.model.gaussian_process.mcmc_gaussian_process import MCMCGaussianProcess
  from smac.model.gaussian_process.priors import HorseshoePrior, LogNormalPrior
label_desc: Use image node_id 2 for calling a global function with example usage: test_predict_wrong_X_dimensions() without return types