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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 commands in Pradeep et al. resource paper at ECIR 2023.""" | |
| import os | |
| import unittest | |
| from integrations.utils import clean_files, run_command, parse_score, parse_score_qa | |
| class TestECIR2023(unittest.TestCase): | |
| def setUp(self): | |
| self.temp_files = [] | |
| def test_section5_sub2_first(self): | |
| """Sample code of the first command in Section 5.2.""" | |
| metrics = ["Top5", "Top20", "Top100"] | |
| ground_truth = [73.8, 84.27, 89.34] | |
| output_file = 'runs/run.nq-test.dkrr.trec' | |
| json_file = 'runs/run.nq-test.dkrr.json' | |
| self.temp_files.append(output_file) | |
| self.temp_files.append(json_file) | |
| # retrieval | |
| run_cmd = f'python -m pyserini.search.faiss \ | |
| --index wikipedia-dpr-dkrr-nq \ | |
| --topics nq-test \ | |
| --encoder castorini/dkrr-dpr-nq-retriever \ | |
| --output {output_file} --query-prefix question: \ | |
| --threads 72 --batch-size 72 \ | |
| --hits 100' | |
| status = os.system(run_cmd) | |
| self.assertEqual(status, 0) | |
| # conversion | |
| convert_cmd = f'python -m pyserini.eval.convert_trec_run_to_dpr_retrieval_run \ | |
| --topics nq-test \ | |
| --index wikipedia-dpr \ | |
| --input {output_file} \ | |
| --output {json_file}' | |
| status = os.system(convert_cmd) | |
| self.assertEqual(status, 0) | |
| # evaluation | |
| eval_cmd = f'python -m pyserini.eval.evaluate_dpr_retrieval \ | |
| --retrieval {json_file} \ | |
| --topk 5 20 100' | |
| stdout, stderr = run_command(eval_cmd) | |
| scores = [] | |
| for mt in metrics: | |
| scores.append(parse_score_qa(stdout, mt, 4) * 100) | |
| for score in zip(scores, ground_truth): | |
| self.assertAlmostEqual(score[0], score[1], delta=0.02) | |
| def test_section5_sub2_second(self): | |
| """Sample code of the second command in Section 5.2.""" | |
| cmd_nq = 'python scripts/repro_matrix/run_all_odqa.py --topics nq' | |
| cmd_tqa = 'python scripts/repro_matrix/run_all_odqa.py --topics nq' | |
| # run both commands, check if all tests passed (i.e., returned OK) | |
| stdout_nq, stderr_nq = run_command(cmd_nq) | |
| self.assertEqual(stdout_nq.count('[OK]'), 21) | |
| stdout_tqa, stderr_tqa = run_command(cmd_tqa) | |
| self.assertEqual(stdout_tqa.count('[OK]'), 21) | |
| def tearDown(self): | |
| clean_files(self.temp_files) | |
| if __name__ == '__main__': | |
| unittest.main() | |