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| import pytest | |
| from nltk import config_megam | |
| from nltk.classify.rte_classify import RTEFeatureExtractor, rte_classifier, rte_features | |
| from nltk.corpus import rte as rte_corpus | |
| expected_from_rte_feature_extration = """ | |
| alwayson => True | |
| ne_hyp_extra => 0 | |
| ne_overlap => 1 | |
| neg_hyp => 0 | |
| neg_txt => 0 | |
| word_hyp_extra => 3 | |
| word_overlap => 3 | |
| alwayson => True | |
| ne_hyp_extra => 0 | |
| ne_overlap => 1 | |
| neg_hyp => 0 | |
| neg_txt => 0 | |
| word_hyp_extra => 2 | |
| word_overlap => 1 | |
| alwayson => True | |
| ne_hyp_extra => 1 | |
| ne_overlap => 1 | |
| neg_hyp => 0 | |
| neg_txt => 0 | |
| word_hyp_extra => 1 | |
| word_overlap => 2 | |
| alwayson => True | |
| ne_hyp_extra => 1 | |
| ne_overlap => 0 | |
| neg_hyp => 0 | |
| neg_txt => 0 | |
| word_hyp_extra => 6 | |
| word_overlap => 2 | |
| alwayson => True | |
| ne_hyp_extra => 1 | |
| ne_overlap => 0 | |
| neg_hyp => 0 | |
| neg_txt => 0 | |
| word_hyp_extra => 4 | |
| word_overlap => 0 | |
| alwayson => True | |
| ne_hyp_extra => 1 | |
| ne_overlap => 0 | |
| neg_hyp => 0 | |
| neg_txt => 0 | |
| word_hyp_extra => 3 | |
| word_overlap => 1 | |
| """ | |
| class TestRTEClassifier: | |
| # Test the feature extraction method. | |
| def test_rte_feature_extraction(self): | |
| pairs = rte_corpus.pairs(["rte1_dev.xml"])[:6] | |
| test_output = [ | |
| f"{key:<15} => {rte_features(pair)[key]}" | |
| for pair in pairs | |
| for key in sorted(rte_features(pair)) | |
| ] | |
| expected_output = expected_from_rte_feature_extration.strip().split("\n") | |
| # Remove null strings. | |
| expected_output = list(filter(None, expected_output)) | |
| assert test_output == expected_output | |
| # Test the RTEFeatureExtractor object. | |
| def test_feature_extractor_object(self): | |
| rtepair = rte_corpus.pairs(["rte3_dev.xml"])[33] | |
| extractor = RTEFeatureExtractor(rtepair) | |
| assert extractor.hyp_words == {"member", "China", "SCO."} | |
| assert extractor.overlap("word") == set() | |
| assert extractor.overlap("ne") == {"China"} | |
| assert extractor.hyp_extra("word") == {"member"} | |
| # Test the RTE classifier training. | |
| def test_rte_classification_without_megam(self): | |
| # Use a sample size for unit testing, since we | |
| # don't need to fully train these classifiers | |
| clf = rte_classifier("IIS", sample_N=100) | |
| clf = rte_classifier("GIS", sample_N=100) | |
| def test_rte_classification_with_megam(self): | |
| try: | |
| config_megam() | |
| except (LookupError, AttributeError) as e: | |
| pytest.skip("Skipping tests with dependencies on MEGAM") | |
| clf = rte_classifier("megam", sample_N=100) | |