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Modify range search test cases (#22791) 

Signed-off-by: Binbin Lv <binbin.lv@zilliz.com>
pull/22806/head
binbin 2023-03-16 17:15:54 +08:00 committed by GitHub
parent bb5088e605
commit 6e47312138
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1 changed files with 24 additions and 9 deletions
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33
tests/python_client/testcases/test_search.py
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@ -5389,8 +5389,8 @@ class TestCollectionRangeSearch(TestcaseBase):
@pytest.mark.tags(CaseLabel.L2)
@pytest.mark.parametrize("index, params",
zip(ct.all_index_types[:7],
ct.default_index_params[:7]))
zip(range_search_supported_index,
range_search_supported_index_params))
def test_range_search_after_index_different_metric_type(self, dim, index, params):
"""
target: test range search with different metric type
@ -5615,7 +5615,7 @@ class TestCollectionRangeSearch(TestcaseBase):
@pytest.mark.tags(CaseLabel.L2)
@pytest.mark.parametrize("index", ["BIN_FLAT", "BIN_IVF_FLAT"])
def test_range_search_binary_tanimoto_flat_index(self, nq, dim, auto_id, _async, index, is_flush):
def test_range_search_binary_tanimoto_flat_index(self, dim, auto_id, _async, index, is_flush):
"""
target: range search binary_collection, and check the result: distance
method: compare the return distance value with value computed with TANIMOTO
@ -5637,16 +5637,31 @@ class TestCollectionRangeSearch(TestcaseBase):
query_raw_vector, binary_vectors = cf.gen_binary_vectors(3000, dim)
distance_0 = cf.tanimoto(query_raw_vector[0], binary_raw_vector[0])
distance_1 = cf.tanimoto(query_raw_vector[0], binary_raw_vector[1])
# 4. search and compare the distance
search_params = {"metric_type": "TANIMOTO", "params": {"nprobe": 10, "radius": 1000,
"range_filter": 0}}
res = collection_w.search(binary_vectors[:nq], "binary_vector",
# 4. search
search_params = {"metric_type": "TANIMOTO", "params": {"nprobe": 10}}
res = collection_w.search(binary_vectors[:1], "binary_vector",
search_params, default_limit, "int64 >= 0",
_async=_async)[0]
if _async:
res.done()
res = res.result()
limit = 0
radius = 1000
range_filter = 0
# filter the range search results to be compared
for distance_single in res[0].distances:
if radius > distance_single >= range_filter:
limit += 1
# 5. range search and compare the distance
search_params = {"metric_type": "TANIMOTO", "params": {"nprobe": 10, "radius": radius,
"range_filter": range_filter}}
res = collection_w.search(binary_vectors[:1], "binary_vector",
search_params, default_limit, "int64 >= 0",
_async=_async,
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
check_items={"nq": 1,
"ids": insert_ids,
"limit": 2,
"limit": limit,
"_async": _async})[0]
if _async:
res.done()