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| # | |
| # Pyserini: Reproducible IR research with sparse and dense representations | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # | |
| """Integration tests for MS MARCO V1 doc corpora (full and segmented) using pre-built indexes.""" | |
| import unittest | |
| from integrations.utils import run_retrieval_and_return_scores | |
| class TestPrebuiltMsMarcoV1Doc(unittest.TestCase): | |
| def setUp(self): | |
| self.threads = 16 | |
| self.batch_size = 128 | |
| # | |
| # doc "full" conditions | |
| # | |
| def test_doc_full_trec_output(self): | |
| """Test case for MS MARCO V1 doc (full), dev queries, TREC output | |
| on all three pre-built indexes (base, slim, full).""" | |
| # Loop over all three pre-built indexes. | |
| for index in ['msmarco-v1-doc', 'msmarco-v1-doc-slim', 'msmarco-v1-doc-full']: | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc.trec.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index {index} --topics msmarco-doc-dev --bm25 --hits 1000', | |
| 'msmarco-doc-dev', | |
| 'trec_eval', | |
| [['map', 'map'], ['recall.1000', 'recall_1000']]) | |
| self.assertTrue('map' in scores) | |
| self.assertTrue('recall.1000' in scores) | |
| self.assertAlmostEqual(scores['map'], 0.2774, delta=0.0001) | |
| self.assertAlmostEqual(scores['recall.1000'], 0.9357, delta=0.0001) | |
| def test_doc_full_msmarco_output(self): | |
| """Test case for MS MARCO V1 doc (full), dev queries, MS MARCO output | |
| on all three pre-built indexes (base, slim, full).""" | |
| # Loop over all three pre-built indexes. | |
| for index in ['msmarco-v1-doc', 'msmarco-v1-doc-slim', 'msmarco-v1-doc-full']: | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc.msmarco.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index {index} --topics msmarco-doc-dev --bm25 --hits 100 --output-format msmarco', | |
| 'msmarco-doc-dev', | |
| 'msmarco_doc_string', []) | |
| self.assertTrue('MRR@100' in scores) | |
| self.assertEqual(scores['MRR@100'], '0.2766351807440808') | |
| # | |
| # doc segmented conditions | |
| # | |
| def test_doc_segmented_trec_output(self): | |
| """Test case for MS MARCO V1 doc segmented, dev queries, TREC output | |
| on all three pre-built indexes (base, slim, full).""" | |
| # Loop over all three pre-built indexes. | |
| for index in ['msmarco-v1-doc-segmented', 'msmarco-v1-doc-segmented-slim', 'msmarco-v1-doc-segmented-full']: | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc-segmented.trec.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index {index} --topics msmarco-doc-dev --bm25 --hits 10000 --max-passage --max-passage-hits 1000', | |
| 'msmarco-doc-dev', | |
| 'trec_eval', | |
| [['map', 'map'], ['recall.1000', 'recall_1000']]) | |
| self.assertTrue('map' in scores) | |
| self.assertTrue('recall.1000' in scores) | |
| self.assertAlmostEqual(scores['map'], 0.2762, delta=0.0001) | |
| self.assertAlmostEqual(scores['recall.1000'], 0.9311, delta=0.0001) | |
| def test_doc_segmented_msmarco_output(self): | |
| """Test case for MS MARCO V1 doc segmented, dev queries, MS MARCO output | |
| on all three pre-built indexes (base, slim, full).""" | |
| # Loop over all three pre-built indexes. | |
| for index in ['msmarco-v1-doc-segmented', 'msmarco-v1-doc-segmented-slim', 'msmarco-v1-doc-segmented-full']: | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc-segmented.msmarco.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index {index} --topics msmarco-doc-dev \ | |
| --bm25 --hits 1000 --max-passage --max-passage-hits 100 --output-format msmarco', | |
| 'msmarco-doc-dev', | |
| 'msmarco_doc_string', []) | |
| self.assertTrue('MRR@100' in scores) | |
| self.assertEqual(scores['MRR@100'], '0.2755196341768384') | |
| # | |
| # doc2query conditions | |
| # | |
| def test_doc_full_expanded_trec_output(self): | |
| """Test case for MS MARCO V1 doc (full) + doc2query-T5 expansions, dev queries, TREC output.""" | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc.expanded.trec.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index msmarco-v1-doc-d2q-t5 --topics msmarco-doc-dev --bm25 --hits 1000', | |
| 'msmarco-doc-dev', | |
| 'trec_eval', | |
| [['map', 'map'], ['recall.1000', 'recall_1000']]) | |
| self.assertTrue('map' in scores) | |
| self.assertTrue('recall.1000' in scores) | |
| self.assertAlmostEqual(scores['map'], 0.3273, delta=0.0001) | |
| self.assertAlmostEqual(scores['recall.1000'], 0.9553, delta=0.0001) | |
| def test_doc_full_expanded_msmarco_output(self): | |
| """Test case for MS MARCO V1 doc (full) + doc2query-T5 expansions, dev queries, MS MARCO output.""" | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc.expanded.msmarco.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index msmarco-v1-doc-d2q-t5 --topics msmarco-doc-dev --bm25 --hits 100 --output-format msmarco', | |
| 'msmarco-doc-dev', | |
| 'msmarco_doc_string', []) | |
| self.assertTrue('MRR@100' in scores) | |
| self.assertEqual(scores['MRR@100'], '0.3268656233100833') | |
| def test_doc_segmented_expanded_trec_output(self): | |
| """Test case for MS MARCO V1 doc segmented + doc2query-T5 expansions, dev queries, TREC output.""" | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc-segmented.expanded.trec.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index msmarco-v1-doc-segmented-d2q-t5 --topics msmarco-doc-dev \ | |
| --bm25 --hits 10000 --max-passage --max-passage-hits 1000', | |
| 'msmarco-doc-dev', | |
| 'trec_eval', | |
| [['map', 'map'], ['recall.1000', 'recall_1000']]) | |
| self.assertTrue('map' in scores) | |
| self.assertTrue('recall.1000' in scores) | |
| self.assertAlmostEqual(scores['map'], 0.3213, delta=0.0001) | |
| self.assertAlmostEqual(scores['recall.1000'], 0.9530, delta=0.0001) | |
| def test_doc_segmented_expanded_msmarco_output(self): | |
| """Test case for MS MARCO V1 doc segmented + doc2query-T5 expansions, dev queries, MS MARCO output.""" | |
| scores = run_retrieval_and_return_scores( | |
| 'runs/test_run.msmarco-doc-segmented.expanded.msmarco.txt', | |
| f'python -m pyserini.search.lucene --threads {self.threads} --batch-size {self.batch_size} \ | |
| --index msmarco-v1-doc-segmented-d2q-t5 --topics msmarco-doc-dev \ | |
| --bm25 --hits 1000 --max-passage --max-passage-hits 100 --output-format msmarco', | |
| 'msmarco-doc-dev', | |
| 'msmarco_doc_string', []) | |
| self.assertTrue('MRR@100' in scores) | |
| self.assertEqual(scores['MRR@100'], '0.320918438140918') | |
| if __name__ == '__main__': | |
| unittest.main() | |