| 892 | self.mock_deep_estimator.partial_fit = MagicMock(name='partial_fit') |
| 893 | |
| 894 | def test_teach(self): |
| 895 | |
| 896 | for bootstrap, warm_start in product([True, False], [True, False]): |
| 897 | for n_samples in range(1, 10): |
| 898 | X = torch.randn(n_samples, 1) |
| 899 | y = torch.randn(n_samples) |
| 900 | |
| 901 | learner = modAL.models.learners.DeepActiveLearner( |
| 902 | estimator=self.mock_deep_estimator |
| 903 | ) |
| 904 | |
| 905 | learner.teach(X, y, bootstrap=bootstrap, warm_start=warm_start) |
| 906 | |
| 907 | def test_batch_size(self): |
| 908 | learner = modAL.models.learners.DeepActiveLearner( |