code: def test_no_y_validation_model_fit(y):
      # Make sure that other non-conventional y labels are not accepted
  
      X, clusters = make_blobs(n_features=6)
      sfs = SequentialFeatureSelector(
          KMeans(),
          n_features_to_select=3,
      )
  
      with pytest.raises((TypeError, ValueError)):
          sfs.fit(X, y)
  
imports: import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from sklearn.cluster import KMeans
  from sklearn.datasets import make_blobs, make_classification, make_regression
  from sklearn.ensemble import HistGradientBoostingRegressor
  from sklearn.feature_selection import SequentialFeatureSelector
  from sklearn.linear_model import LinearRegression
  from sklearn.model_selection import LeaveOneGroupOut, cross_val_score
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 11 for calling a global function with example usage: test_no_y_validation_model_fit(y) without return types