code: def test_checking_inputs_length(model):
      iris = load_iris()
      X, y = iris.data, iris.target
      y = 2 * (y > 0) - 1
      X_, mask = to_niimgs(X, (2, 2, 2))
  
      # Remove ten samples from y
      y = y[:-10]
  
      with pytest.raises(
          ValueError, match="inconsistent numbers of samples"
      ):
          model(
              mask=mask,
              alphas=1.0 / 0.01 / X.shape[0],
              l1_ratios=1.0,
              tol=1e-10,
              screening_percentile=100.0,
              verbose=0,
          ).fit(
              X_,
              y,
          )
  
imports: from functools import partial
  import numpy
  import pytest
  from numpy.testing import assert_almost_equal, assert_array_equal
  from scipy import linalg
  from sklearn.datasets import load_iris
  from sklearn.linear_model import Lasso, LogisticRegression
  from sklearn.linear_model._coordinate_descent import _alpha_grid
  from sklearn.metrics import accuracy_score
  from nilearn._utils.param_validation import adjust_screening_percentile
  from nilearn.decoding.space_net import BaseSpaceNet, SpaceNetClassifier, SpaceNetRegressor, _crop_mask, _EarlyStoppingCallback, _space_net_alpha_grid, _univariate_feature_screening, path_scores
  from nilearn.decoding.space_net_solvers import graph_net_logistic, graph_net_squared_loss
  from nilearn.decoding.tests._testing import create_graph_net_simulation_data
  from nilearn.image import get_data
  from .test_same_api import to_niimgs
label_desc: Use image node_id 23 for calling a global function with example usage: test_checking_inputs_length(model) without return types