admin/milvus
1
0
Fork 0
mirror of https://gitee.com/milvus-io/milvus.git synced 2026-01-07 19:31:51 +08:00
Code Issues Packages Projects Releases Wiki Activity

test: add different datatype for some functions (#33869)

Browse Source 
Signed-off-by: nico <cheng.yuan@zilliz.com>
This commit is contained in:
nico 2024-06-14 17:51:57 +08:00 committed by GitHub
parent a963afa0d3
commit b748d8af5d
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 84 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

35
tests/python_client/testcases/test_query.py
View File

@ -2363,6 +2363,20 @@ class TestQueryOperation(TestcaseBase):
res, _ = collection_w.query(default_term_expr, output_fields=[ct.default_binary_vec_field_name])
assert res[0].keys() == set(fields)
@pytest.mark.tags(CaseLabel.L1)
@pytest.mark.parametrize("vector_data_type", ["FLOAT_VECTOR", "FLOAT16_VECTOR", "BFLOAT16_VECTOR"])
def test_query_output_all_vector_type(self, vector_data_type):
"""
target: test query output different vector type
method: create index and specify vec field as output field
expected: return primary field and vec field
"""
collection_w, vectors = self.init_collection_general(prefix, True,
vector_data_type=vector_data_type)[0:2]
fields = [ct.default_int64_field_name, ct.default_float_vec_field_name]
res, _ = collection_w.query(default_term_expr, output_fields=[ct.default_float_vec_field_name])
assert res[0].keys() == set(fields)
@pytest.mark.tags(CaseLabel.L2)
def test_query_partition_repeatedly(self):
"""
@ -3741,6 +3755,27 @@ class TestQueryIterator(TestcaseBase):
check_items={"count": ct.default_nb - offset,
"batch_size": batch_size})
@pytest.mark.tags(CaseLabel.L2)
@pytest.mark.parametrize("vector_data_type", ["FLOAT_VECTOR", "FLOAT16_VECTOR", "BFLOAT16_VECTOR"])
def test_query_iterator_output_different_vector_type(self, vector_data_type):
"""
target: test query iterator with output fields
method: 1. query iterator output different vector type
2. check the result, expect pk
expected: query successfully
"""
# 1. initialize with data
batch_size = 400
collection_w = self.init_collection_general(prefix, True,
vector_data_type=vector_data_type)[0]
# 2. query iterator
expr = "int64 >= 0"
collection_w.query_iterator(batch_size, expr=expr,
output_fields=[ct.default_float_vec_field_name],
check_task=CheckTasks.check_query_iterator,
check_items={"count": ct.default_nb,
"batch_size": batch_size})
@pytest.mark.tags(CaseLabel.L1)
@pytest.mark.parametrize("batch_size", [10, 100, 777, 2000])
def test_query_iterator_with_different_batch_size(self, batch_size):

60
tests/python_client/testcases/test_search.py
View File

@ -5074,6 +5074,8 @@ class TestSearchBase(TestcaseBase):
# 4. check the search results
for i in range(default_nq):
assert res_ip[i].ids == res_cosine[i].ids
log.info(res_cosine[i].distances)
log.info(res_ip[i].distances)
@pytest.mark.tags(CaseLabel.L2)
def test_search_without_connect(self):
@ -5874,6 +5876,10 @@ class TestSearchPagination(TestcaseBase):
def enable_dynamic_field(self, request):
yield request.param
@pytest.fixture(scope="function", params=["FLOAT_VECTOR", "FLOAT16_VECTOR", "BFLOAT16_VECTOR"])
def vector_data_type(self, request):
yield request.param
"""
******************************************************************
# The following are valid base cases
@ -5897,10 +5903,8 @@ class TestSearchPagination(TestcaseBase):
collection_w = self.init_collection_general(prefix, True, auto_id=auto_id, dim=default_dim,
enable_dynamic_field=enable_dynamic_field)[0]
# 2. search pagination with offset
search_param = {"metric_type": "COSINE",
"params": {"nprobe": 10}, "offset": offset}
vectors = [[random.random() for _ in range(default_dim)]
for _ in range(default_nq)]
search_param = {"metric_type": "COSINE", "params": {"nprobe": 10}, "offset": offset}
vectors = [[random.random() for _ in range(default_dim)] for _ in range(default_nq)]
search_res = collection_w.search(vectors[:default_nq], default_search_field,
search_param, limit,
default_search_exp, _async=_async,
@ -5937,10 +5941,8 @@ class TestSearchPagination(TestcaseBase):
self.init_collection_general(prefix, True, auto_id=auto_id, dim=default_dim,
enable_dynamic_field=enable_dynamic_field)[0:4]
# 2. search
search_param = {"metric_type": "COSINE",
"params": {"nprobe": 10}, "offset": offset}
vectors = [[random.random() for _ in range(default_dim)]
for _ in range(default_nq)]
search_param = {"metric_type": "COSINE", "params": {"nprobe": 10}, "offset": offset}
vectors = [[random.random() for _ in range(default_dim)] for _ in range(default_nq)]
output_fields = [default_string_field_name, default_float_field_name]
search_res = collection_w.search(vectors[:default_nq], default_search_field,
search_param, default_limit,
@ -5999,6 +6001,40 @@ class TestSearchPagination(TestcaseBase):
assert sorted(search_res[0].distances, key=numpy.float32) == sorted(
res[0].distances[offset:], key=numpy.float32)
@pytest.mark.tags(CaseLabel.L1)
def test_search_all_vector_type_with_pagination(self, vector_data_type):
"""
target: test search with pagination using different vector datatype
method: 1. connect and create a collection
2. search pagination with offset
3. search with offset+limit
4. compare with the search results whose corresponding ids should be the same
expected: search successfully and ids is correct
"""
# 1. create a collection
auto_id = False
enable_dynamic_field = True
offset = 100
limit = 20
collection_w = self.init_collection_general(prefix, True, auto_id=auto_id, dim=default_dim,
enable_dynamic_field=enable_dynamic_field,
vector_data_type=vector_data_type)[0]
# 2. search pagination with offset
search_param = {"metric_type": "COSINE", "params": {"nprobe": 10}, "offset": offset}
vectors = cf.gen_vectors_based_on_vector_type(default_nq, default_dim, vector_data_type)
search_res = collection_w.search(vectors[:default_nq], default_search_field,
search_param, limit,
default_search_exp,
check_task=CheckTasks.check_search_results,
check_items={"nq": default_nq,
"limit": limit})[0]
# 3. search with offset+limit
res = collection_w.search(vectors[:default_nq], default_search_field, default_search_params,
limit + offset, default_search_exp)[0]
res_distance = res[0].distances[offset:]
# assert sorted(search_res[0].distances, key=numpy.float32) == sorted(res_distance, key=numpy.float32)
assert set(search_res[0].ids) == set(res[0].ids[offset:])
@pytest.mark.tags(CaseLabel.L2)
@pytest.mark.parametrize("limit", [100, 3000, 10000])
def test_search_with_pagination_topK(self, limit, _async):
@ -9854,7 +9890,8 @@ class TestSearchIterator(TestcaseBase):
""" Test case of search iterator """
@pytest.mark.tags(CaseLabel.L1)
def test_search_iterator_normal(self):
@pytest.mark.parametrize("vector_data_type", ["FLOAT_VECTOR", "FLOAT16_VECTOR", "BFLOAT16_VECTOR"])
def test_search_iterator_normal(self, vector_data_type):
"""
target: test search iterator normal
method: 1. search iterator
@ -9863,12 +9900,13 @@ class TestSearchIterator(TestcaseBase):
"""
# 1. initialize with data
dim = 128
collection_w = self.init_collection_general(
prefix, True, dim=dim, is_index=False)[0]
collection_w = self.init_collection_general(prefix, True, dim=dim, is_index=False,
vector_data_type=vector_data_type)[0]
collection_w.create_index(field_name, {"metric_type": "L2"})
collection_w.load()
# 2. search iterator
search_params = {"metric_type": "L2"}
vectors = cf.gen_vectors_based_on_vector_type(1, dim, vector_data_type)
batch_size = 200
collection_w.search_iterator(vectors[:1], field_name, search_params, batch_size,
check_task=CheckTasks.check_search_iterator,