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[skip e2e] Update test cases for binary metrics (#18297)

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Signed-off-by: Binbin Lv <binbin.lv@zilliz.com>
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binbin 2022-07-19 08:58:28 +08:00 committed by GitHub
parent 1efb413b26
commit 048d8a1114
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1 changed files with 33 additions and 27 deletions
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tests/python_client/testcases/test_search.py
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@ -1626,29 +1626,32 @@ class TestCollectionSearch(TestcaseBase):
assert abs(res[0].distances[0] - min(distance_0, distance_1)) <= epsilon
@pytest.mark.tags(CaseLabel.L2)
@pytest.mark.xfail(reason="issue 18283")
@pytest.mark.parametrize("index", ["BIN_FLAT"])
def test_search_binary_substructure_flat_index(self, nq, dim, auto_id, _async, index, is_flush):
def test_search_binary_substructure_flat_index(self, auto_id, _async, index, is_flush):
"""
target: search binary_collection, and check the result: distance
method: compare the return distance value with value computed with SUBSTRUCTURE
method: compare the return distance value with value computed with SUBSTRUCTURE.
(1) The returned limit(topK) are impacted by dimension (dim) of data.
(2) Searched topK is smaller than set limit when dim is large
(3) it does not support "BIN_IVF_FLAT" index
expected: the return distance equals to the computed value
"""
# 1. initialize with binary data
collection_w, _, binary_raw_vector, insert_ids, time_stamp = self.init_collection_general(prefix, True, 2,
is_binary=True,
auto_id=auto_id,
dim=dim,
is_index=True,
is_flush=is_flush)[0:5]
nq = 1
dim = 8
collection_w, _, binary_raw_vector, insert_ids, time_stamp \
= self.init_collection_general(prefix, True, default_nb, is_binary=True, auto_id=auto_id,
dim=dim, is_index=True, is_flush=is_flush)[0:5]
# 2. create index
default_index = {"index_type": index, "params": {"nlist": 128}, "metric_type": "SUBSTRUCTURE"}
collection_w.create_index("binary_vector", default_index)
collection_w.load()
# 3. compute the distance
query_raw_vector, binary_vectors = cf.gen_binary_vectors(3000, dim)
distance_0 = cf.substructure(query_raw_vector[0], binary_raw_vector[0])
distance_1 = cf.substructure(query_raw_vector[0], binary_raw_vector[1])
query_raw_vector, binary_vectors = cf.gen_binary_vectors(nq, dim)
distance_min = 1
for binary_raw in binary_raw_vector:
distance = cf.substructure(query_raw_vector[0], binary_raw)
distance_min = min(distance, distance_min)
# 4. search and compare the distance
search_params = {"metric_type": "SUBSTRUCTURE", "params": {"nprobe": 10}}
res = collection_w.search(binary_vectors[:nq], "binary_vector",
@ -1658,37 +1661,40 @@ class TestCollectionSearch(TestcaseBase):
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": 2,
"limit": default_limit,
"_async": _async})[0]
if _async:
res.done()
res = res.result()
assert abs(res[0].distances[0] - min(distance_0, distance_1)) <= epsilon
assert abs(res[0].distances[0] - distance_min) <= epsilon
@pytest.mark.tags(CaseLabel.L2)
@pytest.mark.xfail(reason="issue 18283")
@pytest.mark.parametrize("index", ["BIN_FLAT"])
def test_search_binary_superstructure_flat_index(self, nq, dim, auto_id, _async, index, is_flush):
def test_search_binary_superstructure_flat_index(self, auto_id, _async, index, is_flush):
"""
target: search binary_collection, and check the result: distance
method: compare the return distance value with value computed with SUPERSTRUCTURE
(1) The returned limit(topK) are impacted by dimension (dim) of data.
(2) Searched topK is smaller than set limit when dim is large
(3) it does not support "BIN_IVF_FLAT" index
expected: the return distance equals to the computed value
"""
# 1. initialize with binary data
collection_w, _, binary_raw_vector, insert_ids, time_stamp = self.init_collection_general(prefix, True, 2,
is_binary=True,
auto_id=auto_id,
dim=dim,
is_index=True,
is_flush=is_flush)[0:5]
nq = 1
dim = 8
collection_w, _, binary_raw_vector, insert_ids, time_stamp \
= self.init_collection_general(prefix, True, default_nb, is_binary=True, auto_id=auto_id,
dim=dim, is_index=True, is_flush=is_flush)[0:5]
# 2. create index
default_index = {"index_type": index, "params": {"nlist": 128}, "metric_type": "SUPERSTRUCTURE"}
collection_w.create_index("binary_vector", default_index)
collection_w.load()
# 3. compute the distance
query_raw_vector, binary_vectors = cf.gen_binary_vectors(3000, dim)
distance_0 = cf.superstructure(query_raw_vector[0], binary_raw_vector[0])
distance_1 = cf.superstructure(query_raw_vector[0], binary_raw_vector[1])
query_raw_vector, binary_vectors = cf.gen_binary_vectors(nq, dim)
distance_min = 1
for binary_raw in binary_raw_vector:
distance = cf.superstructure(query_raw_vector[0], binary_raw)
distance_min = min(distance, distance_min)
# 4. search and compare the distance
search_params = {"metric_type": "SUPERSTRUCTURE", "params": {"nprobe": 10}}
res = collection_w.search(binary_vectors[:nq], "binary_vector",
@ -1698,12 +1704,12 @@ class TestCollectionSearch(TestcaseBase):
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": 2,
"limit": default_limit,
"_async": _async})[0]
if _async:
res.done()
res = res.result()
assert abs(res[0].distances[0] - min(distance_0, distance_1)) <= epsilon
assert abs(res[0].distances[0] - distance_min) <= epsilon
@pytest.mark.tags(CaseLabel.L2)
def test_search_binary_without_flush(self, metrics, auto_id):