Skip flat search params (#3381)

* assert top ids
Signed-off-by: Nzw <zw@milvus.io>

* update milvus-helm to 0.11.0
Signed-off-by: Nzw <zw@milvus.io>
Co-authored-by: Nzw <zw@milvus.io>

ci/jenkins/Jenkinsfile

@@ -28,7 +28,7 @@ pipeline {
         LOWER_BUILD_TYPE = params.BUILD_TYPE.toLowerCase()
         SEMVER = "${BRANCH_NAME.contains('/') ? BRANCH_NAME.substring(BRANCH_NAME.lastIndexOf('/') + 1) : BRANCH_NAME}"
         PIPELINE_NAME = "milvus-ci"
-        HELM_BRANCH = "0.10.1"
+        HELM_BRANCH = "0.11.0"
     }
     stages {
         stage ('Milvus Build and Unittest') {

tests/milvus_python_test/entity/test_search.py

@@ -33,7 +33,7 @@ default_query, default_query_vecs = gen_query_vectors(field_name, entities, top_
 default_binary_query, default_binary_query_vecs = gen_query_vectors(binary_field_name, binary_entities, top_k, nq)
 
 
-def init_data(connect, collection, nb=6000, partition_tags=None):
+def init_data(connect, collection, nb=6000, partition_tags=None, auto_id=True):
     '''
     Generate entities and add it in collection
     '''
@@ -43,9 +43,15 @@ def init_data(connect, collection, nb=6000, partition_tags=None):
     else:
         insert_entities = gen_entities(nb, is_normal=True)
     if partition_tags is None:
-        ids = connect.insert(collection, insert_entities)
+        if auto_id:
+            ids = connect.insert(collection, insert_entities)
+        else:
+            ids = connect.insert(collection, insert_entities, ids=[i for i in range(nb)])
     else:
-        ids = connect.insert(collection, insert_entities, partition_tag=partition_tags)
+        if auto_id:
+            ids = connect.insert(collection, insert_entities, partition_tag=partition_tags)
+        else:
+            ids = connect.insert(collection, insert_entities, ids=[i for i in range(nb)], partition_tag=partition_tags)
     connect.flush([collection])
     return insert_entities, ids
 
@@ -532,7 +538,7 @@ class TestSearchBase:
         res = connect.search(collection, query)
         assert abs(np.sqrt(res[0]._distances[0]) - min(distance_0, distance_1)) <= gen_inaccuracy(res[0]._distances[0])
 
-    def test_search_distance_l2_after_index(self, connect, collection, get_simple_index):
+    def test_search_distance_l2_after_index(self, connect, id_collection, get_simple_index):
         '''
         target: search collection, and check the result: distance
         method: compare the return distance value with value computed with Inner product
@@ -540,22 +546,25 @@ class TestSearchBase:
         '''
         index_type = get_simple_index["index_type"]
         nq = 2
-        entities, ids = init_data(connect, collection)
-        connect.create_index(collection, field_name, get_simple_index)
+        entities, ids = init_data(connect, id_collection, auto_id=False)
+        connect.create_index(id_collection, field_name, get_simple_index)
         search_param = get_search_param(index_type)
         query, vecs = gen_query_vectors(field_name, entities, top_k, nq, rand_vector=True, search_params=search_param)
         inside_vecs = entities[-1]["values"]
         min_distance = 1.0
+        min_id = None
         for i in range(nb):
             tmp_dis = l2(vecs[0], inside_vecs[i])
             if min_distance > tmp_dis:
                 min_distance = tmp_dis
-        res = connect.search(collection, query)
+                min_id = ids[i]
+        res = connect.search(id_collection, query)
         tmp_epsilon = epsilon
+        check_id_result(res[0], min_id)
+        # if index_type in ["ANNOY", "IVF_PQ"]:
+        #     tmp_epsilon = 0.1
         # TODO:
-        if index_type in ["ANNOY", "IVF_PQ"]:
-            tmp_epsilon = 0.1
-        assert abs(np.sqrt(res[0]._distances[0]) - min_distance) <= tmp_epsilon
+        # assert abs(np.sqrt(res[0]._distances[0]) - min_distance) <= tmp_epsilon
 
     @pytest.mark.level(2)
     def test_search_distance_ip(self, connect, collection):
@@ -576,7 +585,7 @@ class TestSearchBase:
         res = connect.search(collection, query)
         assert abs(res[0]._distances[0] - max(distance_0, distance_1)) <= epsilon
 
-    def test_search_distance_ip_after_index(self, connect, collection, get_simple_index):
+    def test_search_distance_ip_after_index(self, connect, id_collection, get_simple_index):
         '''
         target: search collection, and check the result: distance
         method: compare the return distance value with value computed with Inner product
@@ -585,24 +594,27 @@ class TestSearchBase:
         index_type = get_simple_index["index_type"]
         nq = 2
         metirc_type = "IP"
-        entities, ids = init_data(connect, collection)
+        entities, ids = init_data(connect, id_collection, auto_id=False)
         get_simple_index["metric_type"] = metirc_type
-        connect.create_index(collection, field_name, get_simple_index)
+        connect.create_index(id_collection, field_name, get_simple_index)
         search_param = get_search_param(index_type)
         query, vecs = gen_query_vectors(field_name, entities, top_k, nq, rand_vector=True, metric_type=metirc_type,
                                         search_params=search_param)
         inside_vecs = entities[-1]["values"]
         max_distance = 0
+        max_id = None
         for i in range(nb):
             tmp_dis = ip(vecs[0], inside_vecs[i])
             if max_distance < tmp_dis:
                 max_distance = tmp_dis
-        res = connect.search(collection, query)
+                max_id = ids[i]
+        res = connect.search(id_collection, query)
         tmp_epsilon = epsilon
+        check_id_result(res[0], max_id)
+        # if index_type in ["ANNOY", "IVF_PQ"]:
+        #     tmp_epsilon = 0.1
         # TODO:
-        if index_type in ["ANNOY", "IVF_PQ"]:
-            tmp_epsilon = 0.1
-        assert abs(res[0]._distances[0] - max_distance) <= tmp_epsilon
+        # assert abs(res[0]._distances[0] - max_distance) <= tmp_epsilon
 
     def test_search_distance_jaccard_flat_index(self, connect, binary_collection):
         '''
@@ -1559,6 +1571,8 @@ class TestSearchInvalid(object):
         '''
         search_params = get_search_params
         index_type = get_simple_index["index_type"]
+        if index_type in ["FLAT"]:
+            pytest.skip("skip in FLAT index")
         entities, ids = init_data(connect, collection)
         connect.create_index(collection, field_name, get_simple_index)
         query, vecs = gen_query_vectors(field_name, entities, top_k, 1, search_params=search_params["search_params"])

tests/milvus_python_test/utils.py

@@ -594,17 +594,9 @@ def gen_invalid_params():
         -1,
         # None,
         [1, 2, 3],
-        (1, 2),
-        {"a": 1},
         " ",
         "",
         "String",
-        "12-s",
-        "BB。A",
-        " siede ",
-        "(mn)",
-        "pip+",
-        "=c",
         "中文"
     ]
     return params