code: def test_no_path():
      # Test that the ``return_path=False`` option returns the correct output
      alphas_, _, coef_path_ = linear_model.lars_path(
          X, y, method="lar"
      )
      alpha_, _, coef = linear_model.lars_path(
          X, y, method="lar", return_path=False
      )
  
      assert_array_almost_equal(coef, coef_path_[:, -1])
      assert alpha_ == alphas_[-1]
  
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 10 for calling a global function with example usage: test_no_path() without return types