address multimodal dense_searcher compatibility for hybrid_searcher (c…

…astorini#1831)

Fix issue castorini#1830: Add test case for hybrid searcher on beir arguana

pyserini/search/faiss/__main__.py

@@ -91,7 +91,7 @@ def define_dsearch_args(parser):
                         help="Set efSearch for HNSW index")
 
 
-def init_query_encoder(encoder, encoder_class, tokenizer_name, topics_name, encoded_queries, device, max_length, pooling, l2_norm, prefix, multimodal):
+def init_query_encoder(encoder, encoder_class, tokenizer_name, topics_name, encoded_queries, device, max_length, pooling, l2_norm, prefix, multimodal=False):
     encoded_queries_map = {
         'msmarco-passage-dev-subset': 'tct_colbert-msmarco-passage-dev-subset',
         'dpr-nq-dev': 'dpr_multi-nq-dev',

tests/test_hybrid_search.py

@@ -0,0 +1,73 @@
+#
+# 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.
+#
+
+import os
+import shutil
+import tarfile
+import unittest
+from random import randint
+from typing import List, Dict
+from urllib.request import urlretrieve
+
+from pyserini.search.lucene import LuceneSearcher, JScoredDoc
+from pyserini.index.lucene import Document
+from pyserini.search.faiss import FaissSearcher, AutoQueryEncoder
+from pyserini.search.hybrid import HybridSearcher
+
+
+class TestHybridSearch(unittest.TestCase):
+    tarball_name = None
+    collection_url = None
+    searcher = None
+    searcher_index_dir = None
+    no_vec_searcher = None
+    no_vec_searcher_index_dir = None
+
+    @classmethod
+    def setUpClass(cls):
+        # Download pre-built CACM index built using Lucene 9; append a random value to avoid filename clashes.
+        r = randint(0, 10000000)
+
+        cls.s_index_name = 'beir-v1.0.0-arguana.flat'
+        cls.d_searcher_name = 'facebook/contriever-msmarco'
+        cls.d_index_name = 'beir-v1.0.0-arguana.contriever-msmarco'
+
+        cls.s_searcher = LuceneSearcher.from_prebuilt_index(f'{cls.s_index_name}')
+        cls.d_encoder = AutoQueryEncoder(cls.d_searcher_name, pooling='mean', l2_norm=False)
+        cls.d_searcher = FaissSearcher.from_prebuilt_index(f'{cls.d_index_name}', cls.d_encoder)
+        cls.searcher = HybridSearcher(cls.d_searcher, cls.s_searcher)
+
+    def test_hybrid_searcher(self):
+        hits = self.searcher.search('information retrieval')
+        self.assertTrue(isinstance(hits, List))
+        self.assertEqual(hits[0].docid, 'test-digital-freedoms-aihbiahr-con03b')
+        self.assertAlmostEqual(hits[0].score, 1.440788245201111, places=5)
+
+    def test_hybrid_searcher_batch(self):
+        hits = self.searcher.batch_search(['information retrieval', 'search'], ['q1', 'q2'], threads=2)
+        self.assertTrue(isinstance(hits, Dict))
+
+        self.assertTrue(isinstance(hits['q1'], List))
+        self.assertEqual(hits['q1'][0].docid, 'test-digital-freedoms-aihbiahr-con03b')
+        self.assertAlmostEqual(hits['q1'][0].score, 1.440788245201111, places=5)
+
+        self.assertTrue(isinstance(hits['q2'], List))
+        self.assertEqual(hits['q2'][0].docid, 'test-digital-freedoms-piidfaihbg-pro01a')
+        self.assertAlmostEqual(hits['q2'][0].score, 1.4042499542236329, places=5)
+
+
+if __name__ == '__main__':
+    unittest.main()