Initial commit

packages/leann-backend-hnsw/third_party/faiss/benchs/bench_fw_ivf.py

@@ -0,0 +1,125 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+#
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+import argparse
+import logging
+import os
+
+from faiss.benchs.bench_fw.benchmark import Benchmark
+from faiss.benchs.bench_fw.benchmark_io import BenchmarkIO
+from faiss.benchs.bench_fw.descriptors import (
+    DatasetDescriptor,
+    IndexDescriptorClassic,
+)
+
+logging.basicConfig(level=logging.INFO)
+
+
+def sift1M(bio):
+    benchmark = Benchmark(
+        num_threads=32,
+        training_vectors=DatasetDescriptor(
+            namespace="std_d", tablename="sift1M"
+        ),
+        database_vectors=DatasetDescriptor(
+            namespace="std_d", tablename="sift1M"
+        ),
+        query_vectors=DatasetDescriptor(
+            namespace="std_q", tablename="sift1M"
+        ),
+        index_descs=[
+            IndexDescriptorClassic(
+                factory=f"IVF{2 ** nlist},Flat",
+            )
+            for nlist in range(8, 15)
+        ],
+        k=1,
+        distance_metric="L2",
+    )
+    benchmark.io = bio
+    benchmark.benchmark(result_file="result.json", local=True, train=True, reconstruct=False, knn=True, range=False)
+
+
+def bigann(bio):
+    for scale in [1, 2, 5, 10, 20, 50]:
+        benchmark = Benchmark(
+            num_threads=32,
+            training_vectors=DatasetDescriptor(
+                namespace="std_t", tablename="bigann1M"
+            ),
+            database_vectors=DatasetDescriptor(
+                namespace="std_d", tablename=f"bigann{scale}M"
+            ),
+            query_vectors=DatasetDescriptor(
+                namespace="std_q", tablename="bigann1M"
+            ),
+            index_descs=[
+                IndexDescriptorClassic(
+                    factory=f"IVF{2 ** nlist},Flat",
+                ) for nlist in range(11, 19)
+            ] + [
+                IndexDescriptorClassic(
+                    factory=f"IVF{2 ** nlist}_HNSW32,Flat",
+                    construction_params=[None, {"efConstruction": 200, "efSearch": 40}],
+                ) for nlist in range(11, 19)
+            ],
+            k=1,
+            distance_metric="L2",
+        )
+        benchmark.set_io(bio)
+        benchmark.benchmark(f"result{scale}.json", local=False, train=True, reconstruct=False, knn=True, range=False)
+
+def ssnpp(bio):
+    benchmark = Benchmark(
+        num_threads=32,
+        training_vectors=DatasetDescriptor(
+            tablename="ssnpp_training_5M.npy"
+        ),
+        database_vectors=DatasetDescriptor(
+            tablename="ssnpp_database_5M.npy"
+        ),
+        query_vectors=DatasetDescriptor(
+            tablename="ssnpp_queries_10K.npy"
+        ),
+        index_descs=[
+            IndexDescriptorClassic(
+                factory=f"IVF{2 ** nlist},PQ256x4fs,Refine(SQfp16)",
+            ) for nlist in range(9, 16)
+        ] + [
+            IndexDescriptorClassic(
+                factory=f"IVF{2 ** nlist},Flat",
+            ) for nlist in range(9, 16)
+        ] + [
+            IndexDescriptorClassic(
+                factory=f"PQ256x4fs,Refine(SQfp16)",
+            ),
+            IndexDescriptorClassic(
+                factory=f"HNSW32",
+            ),
+        ],
+        k=1,
+        distance_metric="L2",
+    )
+    benchmark.set_io(bio)
+    benchmark.benchmark("result.json", local=False, train=True, reconstruct=False, knn=True, range=False)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('experiment')
+    parser.add_argument('path')
+    args = parser.parse_args()
+    assert os.path.exists(args.path)
+    path = os.path.join(args.path, args.experiment)
+    if not os.path.exists(path):
+        os.mkdir(path)
+    bio = BenchmarkIO(
+        path=path,
+    )
+    if args.experiment == "sift1M":
+        sift1M(bio)
+    elif args.experiment == "bigann":
+        bigann(bio)
+    elif args.experiment == "ssnpp":
+        ssnpp(bio)