code: def test_linearly_separable_labeled_examples(
      self, num_examples, weights
  ):
      dimension, num_classes = weights.shape
      dataset = datasets.linearly_separable_labeled_examples(
          num_examples, weights
      )
      self.assertEqual(dataset.points.shape, (num_examples, dimension))
      self.assertEqual(dataset.labels.shape, (num_examples,))
      product = np.matmul(dataset.points, weights)
      for i in range(num_examples):
          for j in range(num_classes):
              self.assertGreaterEqual(
                  product[i, dataset.labels[i]], product[i, j]
              )
  
file_path: privacy/tensorflow_privacy/privacy/logistic_regression/datasets_test.py
imports: import unittest
  from absl.testing import parameterized
  import numpy
  from tensorflow_privacy.privacy.logistic_regression import datasets
label_desc: Use image node_id 1 for calling the DatasetsTest obj's underlying member method code with example usage: obj.test_linearly_separable_labeled_examples(num_examples, weights) without return types