code: def test_lars_n_nonzero_coefs(verbose=False):
      lars = linear_model.Lars(n_nonzero_coefs=6, verbose=verbose)
      lars.fit(X, y)
      assert len(lars.coef_.nonzero()[0]) == 6
      # The path should be of length 6 + 1 in a Lars going down to 6
      # non-zero coefs
      assert len(lars.alphas_) == 7
  
imports: import warnings
  import numpy
  import pytest
  from scipy import linalg
  from sklearn import datasets, linear_model
  from sklearn.base import clone
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.linear_model import Lars, LarsCV, LassoLars, LassoLarsCV, LassoLarsIC, lars_path
  from sklearn.linear_model._least_angle import _lars_path_residues
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils._testing import TempMemmap, assert_allclose, assert_array_almost_equal, ignore_warnings
label_desc: Use image node_id 22 for calling a global function with example usage: test_lars_n_nonzero_coefs(verbose) without return types