code: def test_class_number_error(self, y):
      clf = DAGClassifier(alpha=0.1)
      X = pd.DataFrame(np.random.normal(size=(100, 2)))
      with pytest.raises(
          ValueError,
          match="This solver needs samples of at least 2 classes"
          " in the data, but the data contains only one"
          " class: 0",
      ):
          clf.fit(X, y)
  
imports: import os
  import IPython
  import networkx
  import numpy
  import pandas
  import pytest
  import torch
  from sklearn.exceptions import NotFittedError
  from sklearn.gaussian_process.kernels import RBF
  from sklearn.model_selection import KFold, cross_val_score
  from causalnex.structure import data_generators
  from causalnex.structure.pytorch import DAGClassifier, DAGRegressor
label_desc: Use image node_id 10 for calling the TestDAGClassifier obj's underlying member method code with example usage: obj.test_class_number_error(y) without return types