# # 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 ANCE and ANCE PRF using on-the-fly query encoding.""" import os import socket import unittest from integrations.utils import clean_files, run_command, parse_score, parse_score_qa, parse_score_msmarco from pyserini.search import QueryEncoder from pyserini.search import get_topics class TestSearchIntegration(unittest.TestCase): def setUp(self): self.temp_files = [] self.threads = 16 self.batch_size = 256 self.rocchio_alpha = 0.4 self.rocchio_beta = 0.6 # Hard-code larger values for internal servers if socket.gethostname().startswith('damiano') or socket.gethostname().startswith('orca'): self.threads = 36 self.batch_size = 144 def test_ance_encoded_queries(self): encoded = QueryEncoder.load_encoded_queries('ance-msmarco-passage-dev-subset') topics = get_topics('msmarco-passage-dev-subset') for t in topics: self.assertTrue(topics[t]['title'] in encoded.embedding) encoded = QueryEncoder.load_encoded_queries('ance-dl19-passage') topics = get_topics('dl19-passage') for t in topics: self.assertTrue(topics[t]['title'] in encoded.embedding) encoded = QueryEncoder.load_encoded_queries('ance-dl20') topics = get_topics('dl20') for t in topics: self.assertTrue(topics[t]['title'] in encoded.embedding) def test_msmarco_passage_ance_avg_prf_otf(self): output_file = 'test_run.dl2019.ance.avg-prf.otf.trec' self.temp_files.append(output_file) cmd1 = f'python -m pyserini.search.faiss --topics dl19-passage \ --index msmarco-passage-ance-bf \ --encoder castorini/ance-msmarco-passage \ --batch-size {self.batch_size} \ --threads {self.threads} \ --output {output_file} \ --prf-depth 3 \ --prf-method avg' cmd2 = f'python -m pyserini.eval.trec_eval -l 2 -m map dl19-passage {output_file}' status = os.system(cmd1) stdout, stderr = run_command(cmd2) score = parse_score(stdout, 'map') self.assertEqual(status, 0) self.assertAlmostEqual(score, 0.4247, delta=0.0001) def test_msmarco_passage_ance_rocchio_prf_otf(self): output_file = 'test_run.dl2019.ance.rocchio-prf.otf.trec' self.temp_files.append(output_file) cmd1 = f'python -m pyserini.search.faiss --topics dl19-passage \ --index msmarco-passage-ance-bf \ --encoder castorini/ance-msmarco-passage \ --batch-size {self.batch_size} \ --threads {self.threads} \ --output {output_file} \ --prf-depth 5 \ --prf-method rocchio \ --rocchio-topk 5 \ --threads {self.threads} \ --rocchio-alpha {self.rocchio_alpha} \ --rocchio-beta {self.rocchio_beta}' cmd2 = f'python -m pyserini.eval.trec_eval -l 2 -m map dl19-passage {output_file}' status = os.system(cmd1) stdout, stderr = run_command(cmd2) score = parse_score(stdout, 'map') self.assertEqual(status, 0) self.assertAlmostEqual(score, 0.4211, delta=0.0001) def test_msmarco_doc_ance_bf_otf(self): output_file = 'test_run.msmarco-doc.passage.ance-maxp.otf.txt' self.temp_files.append(output_file) cmd1 = f'python -m pyserini.search.faiss --topics msmarco-doc-dev \ --index msmarco-doc-ance-maxp-bf \ --encoder castorini/ance-msmarco-doc-maxp \ --output {output_file}\ --hits 1000 \ --max-passage \ --max-passage-hits 100 \ --output-format msmarco \ --batch-size {self.batch_size} \ --threads {self.threads}' cmd2 = f'python -m pyserini.eval.msmarco_doc_eval --judgments msmarco-doc-dev --run {output_file}' status = os.system(cmd1) stdout, stderr = run_command(cmd2) score = parse_score_msmarco(stdout, 'MRR @100') self.assertEqual(status, 0) # We get a small difference, 0.3794 on macOS. self.assertAlmostEqual(score, 0.3796, delta=0.0002) def test_msmarco_doc_ance_bf_encoded_queries(self): encoder = QueryEncoder.load_encoded_queries('ance_maxp-msmarco-doc-dev') topics = get_topics('msmarco-doc-dev') for t in topics: self.assertTrue(topics[t]['title'] in encoder.embedding) def test_nq_test_ance_bf_otf(self): output_file = 'test_run.ance.nq-test.multi.bf.otf.trec' retrieval_file = 'test_run.ance.nq-test.multi.bf.otf.json' self.temp_files.extend([output_file, retrieval_file]) cmd1 = f'python -m pyserini.search.faiss --topics dpr-nq-test \ --index wikipedia-ance-multi-bf \ --encoder castorini/ance-dpr-question-multi \ --output {output_file} \ --batch-size {self.batch_size} --threads {self.threads}' cmd2 = f'python -m pyserini.eval.convert_trec_run_to_dpr_retrieval_run --topics dpr-nq-test \ --index wikipedia-dpr \ --input {output_file} \ --output {retrieval_file}' cmd3 = f'python -m pyserini.eval.evaluate_dpr_retrieval --retrieval {retrieval_file} --topk 20' status1 = os.system(cmd1) status2 = os.system(cmd2) stdout, stderr = run_command(cmd3) score = parse_score_qa(stdout, 'Top20') self.assertEqual(status1, 0) self.assertEqual(status2, 0) self.assertAlmostEqual(score, 0.8224, places=4) def test_nq_test_ance_encoded_queries(self): encoder = QueryEncoder.load_encoded_queries('dpr_multi-nq-test') topics = get_topics('dpr-nq-test') for t in topics: self.assertTrue(topics[t]['title'] in encoder.embedding) def test_trivia_test_ance_bf_otf(self): output_file = 'test_run.ance.trivia-test.multi.bf.otf.trec' retrieval_file = 'test_run.ance.trivia-test.multi.bf.otf.json' self.temp_files.extend([output_file, retrieval_file]) cmd1 = f'python -m pyserini.search.faiss --topics dpr-trivia-test \ --index wikipedia-ance-multi-bf \ --encoder castorini/ance-dpr-question-multi \ --output {output_file} \ --batch-size {self.batch_size} --threads {self.threads}' cmd2 = f'python -m pyserini.eval.convert_trec_run_to_dpr_retrieval_run --topics dpr-trivia-test \ --index wikipedia-dpr \ --input {output_file} \ --output {retrieval_file}' cmd3 = f'python -m pyserini.eval.evaluate_dpr_retrieval --retrieval {retrieval_file} --topk 20' status1 = os.system(cmd1) status2 = os.system(cmd2) stdout, stderr = run_command(cmd3) score = parse_score_qa(stdout, 'Top20') self.assertEqual(status1, 0) self.assertEqual(status2, 0) self.assertAlmostEqual(score, 0.8010, places=4) def test_trivia_test_ance_encoded_queries(self): encoder = QueryEncoder.load_encoded_queries('dpr_multi-trivia-test') topics = get_topics('dpr-trivia-test') for t in topics: self.assertTrue(topics[t]['title'] in encoder.embedding) def tearDown(self): clean_files(self.temp_files) if __name__ == '__main__': unittest.main()