126 lines
3.8 KiB
Python
126 lines
3.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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import argparse
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import logging
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import os
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from faiss.benchs.bench_fw.benchmark import Benchmark
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from faiss.benchs.bench_fw.benchmark_io import BenchmarkIO
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from faiss.benchs.bench_fw.descriptors import (
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DatasetDescriptor,
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IndexDescriptorClassic,
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)
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logging.basicConfig(level=logging.INFO)
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def sift1M(bio):
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benchmark = Benchmark(
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num_threads=32,
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training_vectors=DatasetDescriptor(
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namespace="std_d", tablename="sift1M"
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),
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database_vectors=DatasetDescriptor(
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namespace="std_d", tablename="sift1M"
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),
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query_vectors=DatasetDescriptor(
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namespace="std_q", tablename="sift1M"
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),
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index_descs=[
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IndexDescriptorClassic(
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factory=f"IVF{2 ** nlist},Flat",
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)
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for nlist in range(8, 15)
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],
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k=1,
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distance_metric="L2",
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)
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benchmark.io = bio
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benchmark.benchmark(result_file="result.json", local=True, train=True, reconstruct=False, knn=True, range=False)
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def bigann(bio):
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for scale in [1, 2, 5, 10, 20, 50]:
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benchmark = Benchmark(
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num_threads=32,
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training_vectors=DatasetDescriptor(
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namespace="std_t", tablename="bigann1M"
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),
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database_vectors=DatasetDescriptor(
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namespace="std_d", tablename=f"bigann{scale}M"
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),
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query_vectors=DatasetDescriptor(
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namespace="std_q", tablename="bigann1M"
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),
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index_descs=[
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IndexDescriptorClassic(
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factory=f"IVF{2 ** nlist},Flat",
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) for nlist in range(11, 19)
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] + [
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IndexDescriptorClassic(
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factory=f"IVF{2 ** nlist}_HNSW32,Flat",
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construction_params=[None, {"efConstruction": 200, "efSearch": 40}],
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) for nlist in range(11, 19)
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],
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k=1,
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distance_metric="L2",
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)
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benchmark.set_io(bio)
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benchmark.benchmark(f"result{scale}.json", local=False, train=True, reconstruct=False, knn=True, range=False)
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def ssnpp(bio):
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benchmark = Benchmark(
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num_threads=32,
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training_vectors=DatasetDescriptor(
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tablename="ssnpp_training_5M.npy"
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),
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database_vectors=DatasetDescriptor(
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tablename="ssnpp_database_5M.npy"
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),
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query_vectors=DatasetDescriptor(
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tablename="ssnpp_queries_10K.npy"
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),
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index_descs=[
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IndexDescriptorClassic(
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factory=f"IVF{2 ** nlist},PQ256x4fs,Refine(SQfp16)",
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) for nlist in range(9, 16)
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] + [
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IndexDescriptorClassic(
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factory=f"IVF{2 ** nlist},Flat",
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) for nlist in range(9, 16)
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] + [
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IndexDescriptorClassic(
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factory=f"PQ256x4fs,Refine(SQfp16)",
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),
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IndexDescriptorClassic(
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factory=f"HNSW32",
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),
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],
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k=1,
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distance_metric="L2",
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)
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benchmark.set_io(bio)
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benchmark.benchmark("result.json", local=False, train=True, reconstruct=False, knn=True, range=False)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument('experiment')
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parser.add_argument('path')
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args = parser.parse_args()
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assert os.path.exists(args.path)
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path = os.path.join(args.path, args.experiment)
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if not os.path.exists(path):
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os.mkdir(path)
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bio = BenchmarkIO(
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path=path,
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)
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if args.experiment == "sift1M":
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sift1M(bio)
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elif args.experiment == "bigann":
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bigann(bio)
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elif args.experiment == "ssnpp":
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ssnpp(bio)
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