From 37208ff3d87e7b3b6086ea62990f38bb365c8a6d Mon Sep 17 00:00:00 2001 From: binbin <83755740+binbinlv@users.noreply.github.com> Date: Thu, 21 Oct 2021 20:17:39 +0800 Subject: [PATCH] Refine parameter call back way (#10338) Signed-off-by: Binbin Lv --- .../python_client/testcases/test_search_20.py | 170 +++++++++--------- 1 file changed, 85 insertions(+), 85 deletions(-) diff --git a/tests/python_client/testcases/test_search_20.py b/tests/python_client/testcases/test_search_20.py index 6511c4faf2..2bd97994c8 100644 --- a/tests/python_client/testcases/test_search_20.py +++ b/tests/python_client/testcases/test_search_20.py @@ -280,8 +280,8 @@ class TestCollectionSearchInvalid(TestcaseBase): if index == "FLAT": pytest.skip("skip in FLAT index") # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, 5000, - is_index=True) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, 5000, + is_index=True)[0:4] # 2. create index and load default_index = {"index_type": index, "params": params, "metric_type": "L2"} collection_w.create_index("float_vector", default_index) @@ -552,9 +552,9 @@ class TestCollectionSearchInvalid(TestcaseBase): expected: searched successfully """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, 5000, - partition_num=1, - is_index=True) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, 5000, + partition_num=1, + is_index=True)[0:4] # 2. create different index if params.get("m"): if (default_dim % params["m"]) != 0: @@ -641,7 +641,7 @@ class TestCollectionSearchInvalid(TestcaseBase): expected: raise exception """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True)[0:4] # 2. search log.info("test_search_with_output_fields_not_exist: Searching collection %s" % collection_w.name) collection_w.search(vectors[:default_nq], default_search_field, @@ -731,7 +731,7 @@ class TestCollectionSearch(TestcaseBase): """ # 1. initialize with data collection_w, _, _, insert_ids, time_stamp = \ - self.init_collection_general(prefix, True, auto_id=auto_id, dim=dim) + self.init_collection_general(prefix, True, auto_id=auto_id, dim=dim)[0:5] # 2. search log.info("test_search_normal: searching collection %s" % collection_w.name) vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] @@ -751,8 +751,8 @@ class TestCollectionSearch(TestcaseBase): method: create connections,collection insert and search vectors in collections expected: search successfully with limit(topK) and can be hit at top 1 (min distance is 0) """ - collection_w, _vectors, _, insert_ids, _ = \ - self.init_collection_general(prefix, True, auto_id=auto_id, dim=dim) + collection_w, _vectors, _, insert_ids = \ + self.init_collection_general(prefix, True, auto_id=auto_id, dim=dim)[0:4] # get vectors that inserted into collection vectors = np.array(_vectors[0]).tolist() vectors = [vectors[i][-1] for i in range(nq)] @@ -797,8 +797,8 @@ class TestCollectionSearch(TestcaseBase): expected: search successfully with limit(topK) """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = \ - self.init_collection_general(prefix, True, auto_id=auto_id, dim=dim) + collection_w, _, _, insert_ids = \ + self.init_collection_general(prefix, True, auto_id=auto_id, dim=dim)[0:4] # 2. search log.info("test_search_normal: searching collection %s" % collection_w.name) vectors = [[random.random() for _ in range(dim)] for _ in range(default_nq)] @@ -825,10 +825,10 @@ class TestCollectionSearch(TestcaseBase): nb = 1000 limit = 1000 partition_num = 1 - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - partition_num, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + partition_num, + auto_id=auto_id, + dim=dim)[0:4] # 2. search all the partitions before partition deletion vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] log.info("test_search_before_after_delete: searching before deleting partitions") @@ -872,10 +872,10 @@ class TestCollectionSearch(TestcaseBase): nb = 1000 limit = 1000 partition_num = 1 - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - partition_num, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + partition_num, + auto_id=auto_id, + dim=dim)[0:4] # 2. search all the partitions before partition deletion vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] log.info("test_search_partition_after_release_one: searching before deleting partitions") @@ -918,9 +918,9 @@ class TestCollectionSearch(TestcaseBase): # 1. initialize with data nb = 1000 limit = 1000 - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - 1, auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + 1, auto_id=auto_id, + dim=dim)[0:4] # 2. search all the partitions before partition deletion vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] log.info("test_search_partition_after_release_all: searching before deleting partitions") @@ -961,7 +961,7 @@ class TestCollectionSearch(TestcaseBase): # 1. initialize without data collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, nb, 1, auto_id=auto_id, - dim=dim) + dim=dim)[0:5] # 2. release collection log.info("test_search_collection_after_release_load: releasing collection %s" % collection_w.name) collection_w.release() @@ -994,7 +994,7 @@ class TestCollectionSearch(TestcaseBase): # 1. initialize without data collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, nb, 1, auto_id=auto_id, - dim=dim) + dim=dim)[0:5] # 2. release collection log.info("test_search_partition_after_release_load: releasing a partition") par = collection_w.partitions @@ -1072,7 +1072,7 @@ class TestCollectionSearch(TestcaseBase): nb_old = 500 collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, nb_old, auto_id=auto_id, - dim=dim) + dim=dim)[0:5] # 2. search for original data after load vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] log.info("test_search_new_data: searching for original data after load") @@ -1113,9 +1113,9 @@ class TestCollectionSearch(TestcaseBase): expected: search successfully with limit(topK) """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, 100, - auto_id=auto_id, - dim=max_dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, 100, + auto_id=auto_id, + dim=max_dim)[0:4] # 2. search nq = 2 log.info("test_search_max_dim: searching collection %s" % collection_w.name) @@ -1143,7 +1143,7 @@ class TestCollectionSearch(TestcaseBase): collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, 5000, partition_num=1, auto_id=auto_id, - dim=dim, is_index=True) + dim=dim, is_index=True)[0:5] # 2. create index and load if params.get("m"): if (dim % params["m"]) != 0: @@ -1183,7 +1183,7 @@ class TestCollectionSearch(TestcaseBase): collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, 5000, partition_num=1, auto_id=auto_id, - dim=dim, is_index=True) + dim=dim, is_index=True)[0:5] # 2. create different index if params.get("m"): if (dim % params["m"]) != 0: @@ -1219,9 +1219,9 @@ class TestCollectionSearch(TestcaseBase): expected: searched successfully """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + auto_id=auto_id, + dim=dim)[0:4] # 2. search for multiple times vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] for i in range(search_num): @@ -1246,7 +1246,7 @@ class TestCollectionSearch(TestcaseBase): # 1. initialize with data collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, nb, auto_id=auto_id, - dim=dim) + dim=dim)[0:5] # 2. search log.info("test_search_sync_async_multiple_times: searching collection %s" % collection_w.name) vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] @@ -1322,7 +1322,7 @@ class TestCollectionSearch(TestcaseBase): collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, nb, partition_num=1, auto_id=auto_id, - is_index=True) + is_index=True)[0:5] # 2. create index default_index = {"index_type": "IVF_FLAT", "params": {"nlist": 128}, "metric_type": "L2"} @@ -1355,11 +1355,11 @@ class TestCollectionSearch(TestcaseBase): expected: searched successfully """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - partition_num=1, - auto_id=auto_id, - dim=dim, - is_index=True) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + partition_num=1, + auto_id=auto_id, + dim=dim, + is_index=True)[0:4] vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] # 2. create index default_index = {"index_type": "IVF_FLAT", "params": {"nlist": 128}, "metric_type": "L2"} @@ -1390,10 +1390,10 @@ class TestCollectionSearch(TestcaseBase): expected: searched successfully """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - partition_num=1, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + partition_num=1, + auto_id=auto_id, + dim=dim)[0:4] vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] # 2. create index default_index = {"index_type": "IVF_FLAT", "params": {"nlist": 128}, "metric_type": "L2"} @@ -1462,7 +1462,7 @@ class TestCollectionSearch(TestcaseBase): is_binary=True, auto_id=auto_id, dim=dim, - is_index=True) + is_index=True)[0:5] # 2. create index default_index = {"index_type": index, "params": {"nlist": 128}, "metric_type": "JACCARD"} collection_w.create_index("binary_vector", default_index) @@ -1496,11 +1496,11 @@ class TestCollectionSearch(TestcaseBase): expected: the return distance equals to the computed value """ # 1. initialize with binary data - collection_w, _, binary_raw_vector, insert_ids, _ = self.init_collection_general(prefix, True, 2, - is_binary=True, - auto_id=auto_id, - dim=dim, - is_index=True) + collection_w, _, binary_raw_vector, insert_ids = self.init_collection_general(prefix, True, 2, + is_binary=True, + auto_id=auto_id, + dim=dim, + is_index=True)[0:4] # 2. create index default_index = {"index_type": index, "params": {"nlist": 128}, "metric_type": "HAMMING"} collection_w.create_index("binary_vector", default_index) @@ -1534,11 +1534,11 @@ class TestCollectionSearch(TestcaseBase): expected: the return distance equals to the computed value """ # 1. initialize with binary data - collection_w, _, binary_raw_vector, insert_ids, _ = self.init_collection_general(prefix, True, 2, - is_binary=True, - auto_id=auto_id, - dim=dim, - is_index=True) + collection_w, _, binary_raw_vector, insert_ids = self.init_collection_general(prefix, True, 2, + is_binary=True, + auto_id=auto_id, + dim=dim, + is_index=True)[0:4] log.info("auto_id= %s, _async= %s" % (auto_id, _async)) # 2. create index default_index = {"index_type": index, "params": {"nlist": 128}, "metric_type": "TANIMOTO"} @@ -1573,9 +1573,9 @@ class TestCollectionSearch(TestcaseBase): """ # 1. initialize with data nb = 1000 - collection_w, _vectors, _, insert_ids, _ = self.init_collection_general(prefix, True, - nb, dim=dim, - is_index=True) + collection_w, _vectors, _, insert_ids = self.init_collection_general(prefix, True, + nb, dim=dim, + is_index=True)[0:4] # filter result with expression in collection _vectors = _vectors[0] @@ -1623,10 +1623,10 @@ class TestCollectionSearch(TestcaseBase): """ # 1. initialize with data nb = 1000 - collection_w, _vectors, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - is_all_data_type=True, - auto_id=auto_id, - dim=dim) + collection_w, _vectors, _, insert_ids = self.init_collection_general(prefix, True, nb, + is_all_data_type=True, + auto_id=auto_id, + dim=dim)[0:4] # 2. create index index_param = {"index_type": "IVF_FLAT", "metric_type": "L2", "params": {"nlist": 100}} @@ -1676,10 +1676,10 @@ class TestCollectionSearch(TestcaseBase): """ # 1. initialize with data nb = 1000 - collection_w, _vectors, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - auto_id=True, - dim=dim, - is_index=True) + collection_w, _vectors, _, insert_ids = self.init_collection_general(prefix, True, nb, + auto_id=True, + dim=dim, + is_index=True)[0:4] # filter result with expression in collection _vectors = _vectors[0] @@ -1723,10 +1723,10 @@ class TestCollectionSearch(TestcaseBase): expected: search success """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - is_all_data_type=True, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + is_all_data_type=True, + auto_id=auto_id, + dim=dim)[0:4] # 2. search log.info("test_search_expression_all_data_type: Searching collection %s" % collection_w.name) vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] @@ -1756,9 +1756,9 @@ class TestCollectionSearch(TestcaseBase): expected: search success """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + auto_id=auto_id, + dim=dim)[0:4] # 2. search log.info("test_search_with_output_fields_empty: Searching collection %s" % collection_w.name) vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] @@ -1784,8 +1784,8 @@ class TestCollectionSearch(TestcaseBase): expected: search success """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, - auto_id=auto_id) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, + auto_id=auto_id)[0:4] # 2. search log.info("test_search_with_output_field: Searching collection %s" % collection_w.name) @@ -1812,10 +1812,10 @@ class TestCollectionSearch(TestcaseBase): expected: search success """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - is_all_data_type=True, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + is_all_data_type=True, + auto_id=auto_id, + dim=dim)[0:4] # 2. search log.info("test_search_with_output_fields: Searching collection %s" % collection_w.name) vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] @@ -1844,8 +1844,8 @@ class TestCollectionSearch(TestcaseBase): expected: search success """ # 1. initialize with data - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, - auto_id=auto_id) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, + auto_id=auto_id)[0:4] # 2. search log.info("test_search_with_output_field_wildcard: Searching collection %s" % collection_w.name) @@ -1876,9 +1876,9 @@ class TestCollectionSearch(TestcaseBase): for i in range(collection_num): # 1. initialize with data log.info("test_search_multi_collections: search round %d" % (i + 1)) - collection_w, _, _, insert_ids, _ = self.init_collection_general(prefix, True, nb, - auto_id=auto_id, - dim=dim) + collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb, + auto_id=auto_id, + dim=dim)[0:4] # 2. search vectors = [[random.random() for _ in range(dim)] for _ in range(nq)] log.info("test_search_multi_collections: searching %s entities (nq = %s) from collection %s" % @@ -1904,7 +1904,7 @@ class TestCollectionSearch(TestcaseBase): threads = [] collection_w, _, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, nb, auto_id=auto_id, - dim=dim) + dim=dim)[0:5] def search(collection_w): vectors = [[random.random() for _ in range(dim)] for _ in range(nq)]