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milvus-io--milvus/tests/python_client/deploy/scripts/second_recall_test.py
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chore: import upstream snapshot with attribution
2026-07-13 12:31:17 +08:00

104 lines
3.6 KiB
Python

import h5py
import numpy as np
import time
import sys
import threading
from pathlib import Path
from loguru import logger
from pymilvus import connections, Collection
all_index_types = ["IVF_FLAT", "IVF_SQ8", "HNSW"]
def read_benchmark_hdf5(file_path):
f = h5py.File(file_path, 'r')
train = np.array(f["train"])
test = np.array(f["test"])
neighbors = np.array(f["neighbors"])
f.close()
return train, test, neighbors
def gen_search_param(index_type, metric_type="L2"):
search_params = []
if index_type in ["FLAT", "IVF_FLAT", "IVF_SQ8", "IVF_PQ"]:
for nprobe in [10]:
ivf_search_params = {"metric_type": metric_type, "params": {"nprobe": nprobe}}
search_params.append(ivf_search_params)
elif index_type in ["BIN_FLAT", "BIN_IVF_FLAT"]:
for nprobe in [10]:
bin_search_params = {"metric_type": "HAMMING", "params": {"nprobe": nprobe}}
search_params.append(bin_search_params)
elif index_type in ["HNSW"]:
for ef in [150]:
hnsw_search_param = {"metric_type": metric_type, "params": {"ef": ef}}
search_params.append(hnsw_search_param)
elif index_type == "ANNOY":
for search_k in [1000]:
annoy_search_param = {"metric_type": metric_type, "params": {"search_k": search_k}}
search_params.append(annoy_search_param)
else:
logger.info("Invalid index_type.")
raise Exception("Invalid index_type.")
return search_params[0]
dim = 128
TIMEOUT = 200
def search_test(host="127.0.0.1", index_type="HNSW"):
logger.info(f"recall test for index type {index_type}")
file_path = f"{str(Path(__file__).absolute().parent.parent.parent)}/assets/ann_hdf5/sift-128-euclidean.hdf5"
train, test, neighbors = read_benchmark_hdf5(file_path)
connections.connect(host=host, port="19530")
collection = Collection(name=f"sift_128_euclidean_{index_type}")
nq = 10000
topK = 100
search_params = gen_search_param(index_type)
for i in range(3):
t0 = time.time()
logger.info(f"\nSearch...")
# define output_fields of search result
res = collection.search(
test[:nq], "float_vector", search_params, topK, output_fields=["int64"], timeout=TIMEOUT
)
t1 = time.time()
logger.info(f"search cost {t1 - t0:.4f} seconds")
result_ids = []
for hits in res:
result_id = []
for hit in hits:
result_id.append(hit.entity.get("int64"))
result_ids.append(result_id)
# calculate recall
true_ids = neighbors[:nq, :topK]
sum_radio = 0.0
for index, item in enumerate(result_ids):
# tmp = set(item).intersection(set(flat_id_list[index]))
assert len(item) == len(true_ids[index]), f"get {len(item)} but expect {len(true_ids[index])}"
tmp = set(true_ids[index]).intersection(set(item))
sum_radio = sum_radio + len(tmp) / len(item)
recall = round(sum_radio / len(result_ids), 6)
logger.info(f"recall={recall}")
if index_type in ["IVF_PQ", "ANNOY"]:
assert recall >= 0.6, f"recall={recall} < 0.6"
else:
assert 0.95 <= recall < 1.0, f"recall is {recall}, less than 0.95, greater than or equal to 1.0"
if __name__ == "__main__":
import argparse
import threading
parser = argparse.ArgumentParser(description='config for recall test')
parser.add_argument('--host', type=str, default="127.0.0.1", help='milvus server ip')
args = parser.parse_args()
host = args.host
tasks = []
for index_type in ["HNSW"]:
search_test(host, index_type)