code: def test_predict_wrong_X_dimensions():
      seed = 1
      rs = np.random.RandomState(seed)
  
      # cont
      X, Y, n_dims = get_cont_data(rs)
      # cat
      X, Y, cat_dims, cont_dims = get_cat_data(rs)
  
      for model in (
          get_gp(n_dims, seed),
          get_mixed_gp(cat_dims, cont_dims, seed=1),
      ):
          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)
  
imports: from unittest.mock import patch
  import numpy
  import pytest
  import scipy.optimize
  import sklearn.datasets
  import sklearn.model_selection
  from ConfigSpace import CategoricalHyperparameter, ConfigurationSpace, EqualsCondition, UniformFloatHyperparameter
  from smac.model.gaussian_process.gaussian_process import GaussianProcess
  from smac.model.gaussian_process.priors import HorseshoePrior, LogNormalPrior
  from smac.utils.configspace import convert_configurations_to_array
label_desc: Use image node_id 5 for calling a global function with example usage: test_predict_wrong_X_dimensions() without return types