code: def test_roc_curve_end_points(setup):
      # Make sure that roc_curve returns a curve start at 0 and ending and
      # 1 even in corner cases
      rng = np.random.RandomState(0)
      y_true = np.array([0] * 50 + [1] * 50)
      y_pred = rng.randint(3, size=100)
      fpr, tpr, thr = roc_curve(
          y_true, y_pred, drop_intermediate=True
      ).fetch()
      assert fpr[0] == 0
      assert fpr[-1] == 1
      assert fpr.shape == tpr.shape
      assert fpr.shape == thr.shape
  
imports: import re
  import warnings
  import numpy
  import pandas
  import pytest
  from sklearn.metrics import roc_curve, auc, accuracy_score
  from sklearn.metrics.tests.test_ranking import make_prediction, _auc
  from sklearn.exceptions import UndefinedMetricWarning
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal
  from ....None import dataframe
  from ....None import tensor
  from ...utils.extmath import softmax
  from ..None import roc_curve, auc, accuracy_score, roc_auc_score
label_desc: Use image node_id 3 for calling a global function with example usage: test_roc_curve_end_points(setup) without return types