From cf50605a245b2f7d6acf00cedf22b19be636ccde Mon Sep 17 00:00:00 2001 From: Yitao <12210830@sustech.edu.cn> Date: Wed, 10 Jul 2024 14:50:27 +0800 Subject: [PATCH] Add alaya pyglass --- .../algorithms/alaya/pyglass/.gitignore | 2 + .../algorithms/alaya/pyglass/CMakeLists.txt | 26 +++ .../algorithms/alaya/pyglass/LICENSE | 21 +++ .../algorithms/alaya/pyglass/README.md | 92 ++++++++++ .../algorithms/alaya/pyglass/bind.cpp | 72 ++++++++ .../algorithms/alaya/pyglass/build.sh | 6 + ...shion-mnist-784-euclidean_10_euclidean.png | Bin 0 -> 188909 bytes .../gist-960-euclidean_10_euclidean.png | Bin 0 -> 179011 bytes .../sift-128-euclidean_10_euclidean.png | Bin 0 -> 225989 bytes .../alaya/pyglass/examples/config.json | 38 ++++ .../alaya/pyglass/examples/demo.ipynb | 127 ++++++++++++++ .../algorithms/alaya/pyglass/examples/main.py | 165 ++++++++++++++++++ .../algorithms/alaya/pyglass/main/main.cpp | 115 ++++++++++++ .../pyglass/python/ann_dataset/__init__.py | 1 + .../pyglass/python/ann_dataset/dataset.py | 147 ++++++++++++++++ .../alaya/pyglass/python/bindings.cc | 160 +++++++++++++++++ .../algorithms/alaya/pyglass/python/setup.py | 117 +++++++++++++ 17 files changed, 1089 insertions(+) create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/.gitignore create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/CMakeLists.txt create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/LICENSE create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/README.md create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/bind.cpp create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/build.sh create mode 100755 ann_benchmarks/algorithms/alaya/pyglass/docs/figures/fashion-mnist-784-euclidean_10_euclidean.png create mode 100755 ann_benchmarks/algorithms/alaya/pyglass/docs/figures/gist-960-euclidean_10_euclidean.png create mode 100755 ann_benchmarks/algorithms/alaya/pyglass/docs/figures/sift-128-euclidean_10_euclidean.png create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/examples/config.json create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/examples/demo.ipynb create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/examples/main.py create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/main/main.cpp create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/python/ann_dataset/__init__.py create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/python/ann_dataset/dataset.py create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/python/bindings.cc create mode 100644 ann_benchmarks/algorithms/alaya/pyglass/python/setup.py diff --git a/ann_benchmarks/algorithms/alaya/pyglass/.gitignore b/ann_benchmarks/algorithms/alaya/pyglass/.gitignore new file mode 100644 index 00000000..97855976 --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/.gitignore @@ -0,0 +1,2 @@ +build +.cache diff --git a/ann_benchmarks/algorithms/alaya/pyglass/CMakeLists.txt b/ann_benchmarks/algorithms/alaya/pyglass/CMakeLists.txt new file mode 100644 index 00000000..29798032 --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/CMakeLists.txt @@ -0,0 +1,26 @@ +cmake_minimum_required (VERSION 3.17) +project(glass LANGUAGES CXX) + + +add_library(glass INTERFACE) +target_link_libraries(glass + INTERFACE +) +target_include_directories(glass INTERFACE .) + +set(CXX_STANDARD 17) + +set(CMAKE_EXPORT_COMPILE_COMMANDS ON) + +# SET(CMAKE_CXX_FLAGS "-Wall -Wextra -O0 -lrt -std=c++20 -march=native -fpic -fopenmp -ftree-vectorize -fno-exceptions -fno-rtti" ) + +SET(CMAKE_CXX_FLAGS "-Wextra -O3 -lrt -std=c++17 -march=native -fPIC -fopenmp -ftree-vectorize -fno-exceptions -fno-rtti" ) + +add_executable(main main/main.cpp) +target_link_libraries(main glass fmt::fmt) + +# add_executable(main examples/main.cc) +# target_link_libraries(main glass) + +add_library(AlayaDB SHARED bind.cpp) +target_link_libraries(AlayaDB glass) diff --git a/ann_benchmarks/algorithms/alaya/pyglass/LICENSE b/ann_benchmarks/algorithms/alaya/pyglass/LICENSE new file mode 100644 index 00000000..2b879dfe --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2023 zh Wang + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/ann_benchmarks/algorithms/alaya/pyglass/README.md b/ann_benchmarks/algorithms/alaya/pyglass/README.md new file mode 100644 index 00000000..c2ea6050 --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/README.md @@ -0,0 +1,92 @@ +# Graph Library for Approximate Similarity Search + +pyglass is a library for fast inference of graph index for approximate similarity search. + +## Features + +- Supports multiple graph algorithms, like [**HNSW**](https://github.com/nmslib/hnswlib) and [**NSG**](https://github.com/ZJULearning/nsg). +- Supports multiple hardware platforms, like **X86** and **ARM**. Support for **GPU** is on the way +- No third-party library dependencies, does not rely on OpenBLAS / MKL or any other computing framework. +- Sophisticated memory management and data structure design, very low memory footprint. +- It's high performant. + +## Installation +### Installation from Wheel +pyglass can be installed using pip as follows: +```bash +pip3 install glassppy +``` + +### Installation from Source +If there's some problem when installing from wheel, you can try to build from source. +``` bash +sudo apt-get update && sudo apt-get install -y build-essential git python3 python3-distutils python3-venv +``` +``` bash +pip3 install numpy +pip3 install pybind11 +``` +``` bash +bash build.sh +``` + +## Quick Tour +A runnable demo is at [examples/demo.ipynb](https://github.com/zilliztech/pyglass/blob/master/examples/demo.ipynb). It's highly recommended to try it. + +## Usage +**Import library** +```python +>>> import glassppy as glass +``` +**Load Data** +```python +>>> n, d = 10000, 128 +>>> X = np.random.randn(n, d) +>>> Y = np.random.randn(d) +``` +**Create Index** +pyglass supports **HNSW** and **NSG** index currently +```python +>>> index = glass.Index(index_type="HNSW", dim=d, metric="L2", R=32, L=50) +>>> index = glass.Index(index_type="NSG", dim=d, metric="L2", R=32, L=50) +``` +**Build Graph** +```python +>>> graph = index.build(X) +``` +**Create Searcher** +Searcher accepts `level` parameter as the optimization level. You can set `level` as `0` or `1` or `2`. The higher the level, the faster the searching, but it may cause unstable recall. +```python +>>> optimize_level = 2 +>>> searcher = glass.Searcher(graph=graph, data=X, metric="L2", level=optimize_level) +>>> searcher.set_ef(32) +``` +**(Optional) Optimize Searcher** +```python +>>> searcher.optimize() +``` +**Searching** +```python +>>> ret = searcher.search(query=Y, k=10) +>>> print(ret) +``` + +## Performance + +Glass is among one of the top performant ann algorithms on [ann-benchmarks](https://ann-benchmarks.com/) + +### fashion-mnist-784-euclidean +![](docs/figures/fashion-mnist-784-euclidean_10_euclidean.png) +### gist-960-euclidean +![](docs/figures/gist-960-euclidean_10_euclidean.png) +### sift-128-euclidean +![](docs/figures/sift-128-euclidean_10_euclidean.png) + +### Quick Benchmark + +1. Change configuration file `examples/config.json` +2. Run benchmark +``` +python3 examples/main.py +``` +3. You could check plots on `results` folder diff --git a/ann_benchmarks/algorithms/alaya/pyglass/bind.cpp b/ann_benchmarks/algorithms/alaya/pyglass/bind.cpp new file mode 100644 index 00000000..390184bf --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/bind.cpp @@ -0,0 +1,72 @@ +#include +#include +#include +#include +#include +#include + +extern "C" { + +void *searcher; +float *data; + +void fit(float *vec_data, int data_num, int data_dim) { + data = vec_data; + auto hnsw = (glass::HNSW *)new glass::HNSW(data_dim, "L2"); + hnsw->Build(data, data_num); + + // const std::string metric = "L2"; + // int level = 3; + + searcher = (glass::Searcher> + *)(new glass::Searcher>(hnsw->GetGraph())); + + auto hnsw_s = (glass::Searcher> *)searcher; + + // hnsw_s->SetEf(ef); + + hnsw_s->SetData(data, data_num, data_dim); + + hnsw_s->Optimize(1); +} + +void batch_query(float *query, int query_num, int dim, int k, int ef, int rerank_k, unsigned *res) { + printf("init search\n"); + std::vector> tmp_id(query_num, std::vector(ef)); + std::vector> res_pool(query_num, glass::searcher::LPool(rerank_k)); + + printf("before search\n"); + + auto hnsw_s = (glass::Searcher> *)searcher; + hnsw_s->SetEf(ef); + for (size_t q = 0; q < query_num; ++q) { + // printf("query id: %d\n", q); + auto &ids = tmp_id[q]; + auto cur_query = query + q * dim; + hnsw_s->Search(cur_query, ef, ids.data()); + + for (size_t i = 0; i < k; ++i) { + res[q * k + i] = ids[i]; + } + + // printf("a search"); + + // printf("rerank: %d, k: %d, ef: %d\n", rerank_k, k, ef); + // for (size_t i = 0; i < rerank_k; ++i) { + // res_pool[q].insert_back(ids[i], glass::L2SqrRef(cur_query, data + ids[i] * dim, dim)); + // } + // res_pool[q].sorted(); + // for (size_t i = rerank_k; i < ef; ++i) { + // res_pool[q].emplace_insert(ids[i], glass::L2SqrRef(cur_query, data + ids[i] * dim, dim)); + // } + + // printf("res\n"); + // for (size_t i = 0; i < k; ++i) { + // res[q * k + i] = res_pool[q].data_[i].id; + // printf("%d, ", res[q * k + i]); + // } + // printf("\n"); + } +} + +} // extern C \ No newline at end of file diff --git a/ann_benchmarks/algorithms/alaya/pyglass/build.sh b/ann_benchmarks/algorithms/alaya/pyglass/build.sh new file mode 100644 index 00000000..8e4b0497 --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/build.sh @@ -0,0 +1,6 @@ +cd python +rm -rf build +python setup.py bdist_wheel +pip uninstall glassppy -y +cd dist +ls | xargs pip install diff --git a/ann_benchmarks/algorithms/alaya/pyglass/docs/figures/fashion-mnist-784-euclidean_10_euclidean.png b/ann_benchmarks/algorithms/alaya/pyglass/docs/figures/fashion-mnist-784-euclidean_10_euclidean.png new file mode 100755 index 0000000000000000000000000000000000000000..ca527d12c29212d176c8ffd00b6ce2cb65b8d2c4 GIT binary patch literal 188909 zcmbrmWmuJ6)HMpIU;zdK(h4F9(%pi9NO!l=-3>|#0tyO9hjfWZmo!LsY(hY~Tl&oV zsrNnCxz6|J^I|_d8}`2Uz1Es*&N0Uri?_1UV%S%SuA-r#VT(V1CXa@8@jV*ag{zk_ 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zIL^%3kd$udI6oUE$`zZqfFcj2)cF!1ahz=NBnL;x!Y$(POnJ@QimJ*Wf+%vb_LyD{ zZ^S-*Ovu@$f&>wUo_3V;?aR~fET=Cd&XbOgmkejo5KAL4TV6(Zl_;lAtg`-1I(@Ss zF$?*cAu7y9pU;I?0(>5Lc6rPSO*TD5SFpX;PnUd-_P6h8Y>Mmue_yJ%T-KxE@1;^u OeVhG5eP5rCF8l?!h`3(> literal 0 HcmV?d00001 diff --git a/ann_benchmarks/algorithms/alaya/pyglass/examples/config.json b/ann_benchmarks/algorithms/alaya/pyglass/examples/config.json new file mode 100644 index 00000000..207eee52 --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/examples/config.json @@ -0,0 +1,38 @@ +{ + "datasets": [ + "glove-100-angular", + "sift-128-euclidean", + "fashion-mnist-784-euclidean", + "nytimes-256-angular", + "glove-25-angular" + ], + "index_types": [ + "HNSW", + "NSG" + ], + "R": 32, + "L": 200, + "levels": [ + 0, + 1, + 2 + ], + "topk": 10, + "efs": [ + 10, + 15, + 20, + 30, + 40, + 60, + 80, + 100, + 150, + 200, + 300 + ], + "runs": 5, + "batch": true, + "optimize": true, + "plot": true +} \ No newline at end of file diff --git a/ann_benchmarks/algorithms/alaya/pyglass/examples/demo.ipynb b/ann_benchmarks/algorithms/alaya/pyglass/examples/demo.ipynb new file mode 100644 index 00000000..f2af795d --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/examples/demo.ipynb @@ -0,0 +1,127 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import glassppy as glass\n", + "from ann_dataset import dataset_dict" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "topk = 10\n", + "dataset = dataset_dict['sift-128-euclidean']()\n", + "X_train = dataset.get_database()\n", + "X_test = dataset.get_queries()\n", + "Y = dataset.get_groundtruth(topk)\n", + "n, d = X_train.shape\n", + "nq, d = X_test.shape\n", + "metric = dataset.metric\n", + "print(f\"n = {n}, d = {d}, nq = {nq}, metric = {metric}\")\n", + "print(f\"dataset size = {n * d * 4 / 1024 / 1024:.2f}MB\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "index = glass.Index(index_type=\"HNSW\", dim=d, metric=metric, R=32, L=100)\n", + "g = index.build(X_train)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "s = glass.Searcher(graph=g, data=X_train, metric=metric, level=2)\n", + "s.set_ef(36)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from os import cpu_count\n", + "from time import time\n", + "num_threads = cpu_count()\n", + "\n", + "pred = s.batch_search(query=X_test, k=topk, num_threads=num_threads).reshape(-1, topk)\n", + "recall = dataset.evaluate(pred, topk)\n", + "print(f\"Recall = {recall * 100:.2f}%\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "s.batch_search(query=X_test, k=topk, num_threads=num_threads) # warmup\n", + "for iter in range(10):\n", + " t1 = time()\n", + " pred = s.batch_search(query=X_test, k=topk, num_threads=num_threads)\n", + " t2 = time()\n", + " print(f\"QPS = {nq / (t2 - t1):.2f}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "s.optimize()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "s.batch_search(query=X_test, k=topk, num_threads=num_threads) # warmup\n", + "for iter in range(10):\n", + " t1 = time()\n", + " pred = s.batch_search(query=X_test, k=topk,\n", + " num_threads=num_threads).reshape(-1, topk)\n", + " t2 = time()\n", + " print(f\"QPS = {nq / (t2 - t1)}\")\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "hy", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/ann_benchmarks/algorithms/alaya/pyglass/examples/main.py b/ann_benchmarks/algorithms/alaya/pyglass/examples/main.py new file mode 100644 index 00000000..8d24a9da --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/examples/main.py @@ -0,0 +1,165 @@ +import numpy as np +from time import time +from sklearn import preprocessing +import matplotlib.pyplot as plt +import psutil +import os +import json + +import glassppy as glass +from datasets import dataset_dict + + +class Glass: + def __init__(self, name, level, metric, method_param): + self.metric = metric + self.R = method_param['R'] + self.L = method_param['L'] + self.index_type = method_param['index_type'] + self.optimize = method_param['optimize'] + self.batch = method_param['batch'] + self.name = 'glass_(%s)' % (method_param) + self.dir = 'indices' + self.path = f'{name}_{self.index_type}_R_{self.R}_L_{self.L}.glass' + self.level = level + + def fit(self, X): + if self.metric == "IP": + X = preprocessing.normalize(X, "l2", axis=1) + self.d = X.shape[1] + if not os.path.exists(self.dir): + os.mkdir(self.dir) + if self.path not in os.listdir(self.dir): + p = glass.Index(self.index_type, dim=self.d, + metric=self.metric, R=self.R, L=self.L) + g = p.build(X) + g.save(os.path.join(self.dir, self.path)) + del p + del g + g = glass.Graph(os.path.join(self.dir, self.path)) + self.searcher = glass.Searcher(g, X, self.metric, self.level) + if self.optimize: + if batch: + self.searcher.optimize() + else: + self.searcher.optimize(1) + + def set_query_arguments(self, ef): + self.searcher.set_ef(ef) + self.ef = ef + + def prepare_query(self, q, n): + if self.metric == 'IP': + q = q / np.linalg.norm(q) + self.q = q + self.n = n + + def run_prepared_query(self): + self.res = self.searcher.search( + self.q, self.n) + + def get_prepared_query_results(self): + return self.res + + def prepare_batch_query(self, X, n): + if self.metric == 'angular': + X = preprocessing.normalize(X, axis=1, norm='l2') + self.queries = X + self.n = n + self.nq = len(X) + + def run_batch_query(self): + self.result = self.searcher.batch_search( + self.queries, self.n) + + def get_batch_results(self): + return self.result.reshape(self.nq, -1) + + def get_memory_usage(self): + return psutil.Process().memory_info().rss / 1024 / 1024 + + def freeIndex(self): + del self.searcher + + +if __name__ == '__main__': + plt.style.use('seaborn-whitegrid') + + with open('examples/config.json', 'r') as f: + config = json.load(f) + + index_types = config['index_types'] + levels = config['levels'] + efs = config['efs'] + R = config['R'] + L = config['L'] + topk = config['topk'] + runs = config['runs'] + batch = config['batch'] + optimize = config['optimize'] + dataset_names = config['datasets'] + + results_dir = "results" + if not os.path.exists(results_dir): + os.mkdir(results_dir) + + for dataset_name in dataset_names: + plt.figure(figsize=(10, 6), dpi=120) + dataset = dataset_dict[dataset_name]() + base = dataset.get_base() + query = dataset.get_queries() + gt = dataset.get_groundtruth(topk) + name = dataset.name + metric = dataset.metric + nq = dataset.nq + for it, index_type in enumerate(index_types): + for level in levels: + p = Glass(name, level, metric, { + 'index_type': index_type, 'R': R, 'L': L, 'optimize': optimize, 'batch': batch}) + t = time() + p.fit(base) + ela = time() - t + print(f"Building time of index: {ela}s") + print(f"Memory usage of index: {p.get_memory_usage()}MB") + qpss = [] + recalls = [] + print( + f"dataset: {name}, index: {index_type}, level: {level}") + for ef in efs: + print(f" ef: {ef}") + p.set_query_arguments(ef) + mx_qps = 0.0 + for run in range(runs): + T = 0 + res = np.zeros_like(gt) + if batch: + p.prepare_batch_query(query, topk) + t = time() + p.run_batch_query() + T = time() - t + res = p.get_batch_results() + else: + for i in range(nq): + p.prepare_query(query[i], topk) + t = time() + p.run_prepared_query() + T += time() - t + res[i] = p.get_prepared_query_results() + cnt = 0 + for i in range(nq): + cnt += np.intersect1d(res[i], gt[i]).size + recall = cnt / nq / 10 + qps = nq / T + print( + f" runs [{run + 1}/{runs}], recall: {recall:.4f}, qps: {qps:.2f}") + mx_qps = max(mx_qps, qps) + qpss.append(mx_qps) + recalls.append(recall) + plt.plot(recalls, qpss, + label=f'{index_type} + level{level}', marker=['x', 'o'][it]) + plt.xlabel(f'Recall@{topk}') + plt.ylabel("QPS") + plt.legend() + plt.title(f'{name}') + plt.savefig(os.path.join( + results_dir, f'{name}_R{R}_L{L}_batch{batch}_optimize{optimize}_top{topk}.png')) diff --git a/ann_benchmarks/algorithms/alaya/pyglass/main/main.cpp b/ann_benchmarks/algorithms/alaya/pyglass/main/main.cpp new file mode 100644 index 00000000..7e08999a --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/main/main.cpp @@ -0,0 +1,115 @@ +#include +#include + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +int main(int argc, char **argv) { + if (argc != 7) { + fmt::println("{} data_file query_file answer_file result_path", argv[0]); + exit(-1); + } + + char *data_file = argv[1]; + char *query_file = argv[2]; + char *ans_file = argv[3]; + + int topk = atoi(argv[4]); + int ef = atoi(argv[5]); + int rerank_k = atoi(argv[6]); + + float *data_load = NULL; + unsigned points_num, dim; + glass::load_fvecs(data_file, data_load, points_num, dim); + + float *query_load = NULL; + unsigned query_num, query_dim; + glass::load_fvecs(query_file, query_load, query_num, query_dim); + assert(dim == query_dim); + + unsigned *answers = NULL; + unsigned ans_num, kk; + glass::load_ivecs(ans_file, answers, ans_num, kk); + assert(ans_num == query_num); + + auto index = std::unique_ptr((glass::Builder *)new glass::HNSW(dim, "L2")); + + index->Build(data_load, points_num); + + // index->GetGraph().save("sift.hsnw"); + + // std::cout << "Build HNSW Over" << std::endl; + + const std::string metric = "L2"; + int level = 3; + auto searcher = std::unique_ptr(glass::create_searcher(index->GetGraph(), metric, level)); + searcher->SetEf(ef); + + searcher->SetData(data_load, points_num, dim); + + searcher->Optimize(96); + + std::cout << "create searcher" << std::endl; + + // std::vector> candidate_pool(query_num, maxPQIFCS(topk)); + std::vector> tmp_id(query_num, std::vector(ef)); + std::vector> res_pool(query_num, glass::searcher::LPool(rerank_k)); + + Timer timer; + + timer.reset(); + // #pragma omp parallel for schedule(dynamic) + for (size_t q = 0; q < query_num; ++q) { + auto &ids = tmp_id[q]; + auto cur_query = query_load + q * query_dim; + searcher->Search(cur_query, ef, ids.data()); + + for (size_t i = 0; i < rerank_k; ++i) { + res_pool[q].insert_back(ids[i], glass::L2SqrRef(cur_query, data_load + ids[i] * dim, dim)); + } + res_pool[q].sorted(); + for (size_t i = rerank_k; i < ef; ++i) { + res_pool[q].emplace_insert(ids[i], glass::L2SqrRef(cur_query, data_load + ids[i] * dim, dim)); + } + } + timer.end(); + // std::cout << "Time: " << timer.getElapsedTime() << std::endl; + fmt::println("Search Time: {}", timer.getElapsedTime()); + + // for (int i = 0; i < 10; ++i) { + // printf("search res: \n"); + // for (int j = 0; j < topk; ++j) { + // printf("%d, ", tmp_id[i][j]); + // } + // printf("\n"); + // std::set S = {}; + // for (int j = 0; j < topk; ++j) { + // printf("%d, ", answers[i * kk + j]); + // S.insert(answers[i * kk + j]); + // } + // printf("\n"); + + // int hit_cou = 0; + // for (int j = 0; j < topk; ++j) { + // if (S.find(tmp_id[i][j]) != S.end()) hit_cou++; + // } + // printf("hit count: %d\n", hit_cou); + // // for (int j=0; j +#include +#include +#include + +#include + +#include + +#include "glass/builder.hpp" +#include "glass/hnsw/hnsw.hpp" +#include "glass/nsg/nsg.hpp" +#include "glass/searcher.hpp" + +namespace py = pybind11; +using namespace pybind11::literals; // needed to bring in _a literal + +inline void get_input_array_shapes(const py::buffer_info &buffer, size_t *rows, + size_t *features) { + if (buffer.ndim != 2 && buffer.ndim != 1) { + char msg[256]; + snprintf(msg, sizeof(msg), + "Input vector data wrong shape. Number of dimensions %d. Data " + "must be a 1D or 2D array.", + buffer.ndim); + } + if (buffer.ndim == 2) { + *rows = buffer.shape[0]; + *features = buffer.shape[1]; + } else { + *rows = 1; + *features = buffer.shape[0]; + } +} + +void set_num_threads(int num_threads) { omp_set_num_threads(num_threads); } + +struct Graph { + glass::Graph graph; + + Graph() = default; + + explicit Graph(const Graph &rhs) : graph(rhs.graph) {} + + explicit Graph(const std::string &filename) { graph.load(filename); } + + explicit Graph(const glass::Graph &graph) : graph(graph) {} + + void save(const std::string &filename) { graph.save(filename); } + + void load(const std::string &filename) { graph.load(filename); } +}; + +struct Index { + std::unique_ptr index = nullptr; + + Index(const std::string &index_type, int dim, const std::string &metric, + int R = 32, int L = 200) { + if (index_type == "NSG") { + index = std::unique_ptr( + (glass::Builder *)new glass::NSG(dim, metric, R, L)); + } else if (index_type == "HNSW") { + index = std::unique_ptr( + (glass::Builder *)new glass::HNSW(dim, metric, R, L)); + } else { + printf("Index type [%s] not supported\n", index_type.c_str()); + } + } + + Graph build(py::object input) { + py::array_t items(input); + auto buffer = items.request(); + size_t rows, features; + get_input_array_shapes(buffer, &rows, &features); + float *vector_data = (float *)items.data(0); + index->Build(vector_data, rows); + return Graph(index->GetGraph()); + } +}; + +struct Searcher { + + std::unique_ptr searcher; + + Searcher(const Graph &graph, py::object input, const std::string &metric, + int level) + : searcher(std::unique_ptr( + glass::create_searcher(graph.graph, metric, level))) { + py::array_t items(input); + auto buffer = items.request(); + size_t rows, features; + get_input_array_shapes(buffer, &rows, &features); + float *vector_data = (float *)items.data(0); + searcher->SetData(vector_data, rows, features); + } + + py::object search(py::object query, int k) { + py::array_t items(query); + int *ids; + ids = new int[k]; + searcher->Search(items.data(0), k, ids); + py::capsule free_when_done(ids, [](void *f) { delete[] f; }); + return py::array_t({k}, {sizeof(int)}, ids, free_when_done); + } + + py::object batch_search(py::object query, int k, int num_threads = 0) { + py::array_t items(query); + auto buffer = items.request(); + int *ids; + size_t nq, dim; + { + py::gil_scoped_release l; + get_input_array_shapes(buffer, &nq, &dim); + ids = new int[nq * k]; + if (num_threads != 0) { + omp_set_num_threads(num_threads); + } +#pragma omp parallel for schedule(dynamic) + for (int i = 0; i < nq; ++i) { + searcher->Search(items.data(i), k, ids + i * k); + } + } + py::capsule free_when_done(ids, [](void *f) { delete[] f; }); + return py::array_t({nq * k}, {sizeof(int)}, ids, free_when_done); + } + + void set_ef(int ef) { searcher->SetEf(ef); } + + void optimize(int num_threads = 0) { searcher->Optimize(num_threads); } +}; + +PYBIND11_PLUGIN(glassppy) { + py::module m("glassppy"); + + m.def("set_num_threads", &set_num_threads, py::arg("num_threads")); + + py::class_(m, "Graph") + .def(py::init<>()) + .def(py::init(), py::arg("filename")) + .def("save", &Graph::save, py::arg("filename")) + .def("load", &Graph::load, py::arg("filename")); + + py::class_(m, "Index") + .def(py::init(), + py::arg("index_type"), py::arg("dim"), py::arg("metric"), + py::arg("R") = 32, py::arg("L") = 0) + .def("build", &Index::build, py::arg("data")); + + py::class_(m, "Searcher") + .def(py::init(), + py::arg("graph"), py::arg("data"), py::arg("metric"), + py::arg("level")) + .def("set_ef", &Searcher::set_ef, py::arg("ef")) + .def("search", &Searcher::search, py::arg("query"), py::arg("k")) + .def("batch_search", &Searcher::batch_search, py::arg("query"), + py::arg("k"), py::arg("num_threads") = 0) + .def("optimize", &Searcher::optimize, py::arg("num_threads") = 0); + + return m.ptr(); +} diff --git a/ann_benchmarks/algorithms/alaya/pyglass/python/setup.py b/ann_benchmarks/algorithms/alaya/pyglass/python/setup.py new file mode 100644 index 00000000..9ef59dbe --- /dev/null +++ b/ann_benchmarks/algorithms/alaya/pyglass/python/setup.py @@ -0,0 +1,117 @@ +import os +import sys +import platform + +import numpy as np +import pybind11 +import setuptools +from setuptools import Extension, setup +from setuptools.command.build_ext import build_ext + +__version__ = '1.0.3' + + +include_dirs = [ + pybind11.get_include(), + np.get_include(), +] + +# compatibility when run in python_bindings +bindings_dir = 'python' +if bindings_dir in os.path.basename(os.getcwd()): + source_files = ['./bindings.cc'] + include_dirs.extend(['../']) +else: + source_files = ['./python/bindings.cc'] + include_dirs.extend(['./']) + + +libraries = [] +extra_objects = [] + + +ext_modules = [ + Extension( + 'glassppy', + source_files, + include_dirs=include_dirs, + libraries=libraries, + language='c++', + extra_objects=extra_objects, + ), +] + + +def has_flag(compiler, flagname): + """Return a boolean indicating whether a flag name is supported on + the specified compiler. + """ + import tempfile + with tempfile.NamedTemporaryFile('w', suffix='.cpp') as f: + f.write('int main (int argc, char **argv) { return 0; }') + try: + compiler.compile([f.name], extra_postargs=[flagname]) + except setuptools.distutils.errors.CompileError: + return False + return True + + +def cpp_flag(compiler): + """Return the -std=c++[11/14/17/20] compiler flag. + """ + if has_flag(compiler, '-std=c++17'): + return '-std=c++17' + elif has_flag(compiler, '-std=c++14'): + return '-std=c++14' + elif has_flag(compiler, '-std=c++11'): + return '-std=c++11' + else: + raise RuntimeError('Unsupported compiler -- at least C++11 support ' + 'is needed!') + +class BuildExt(build_ext): + """A custom build extension for adding compiler-specific options.""" + c_opts = { + 'unix': "-Ofast -lrt -march=native -fpic -fopenmp -ftree-vectorize -ftree-vectorizer-verbose=0".split() + } + + link_opts = { + 'unix': [], + } + + c_opts['unix'].append("-fopenmp") + link_opts['unix'].extend(['-fopenmp', '-pthread']) + + def build_extensions(self): + ct = self.compiler.compiler_type + opts = self.c_opts.get(ct, []) + if ct == 'unix': + opts.append('-DVERSION_INFO="%s"' % + self.distribution.get_version()) + opts.append(cpp_flag(self.compiler)) + if has_flag(self.compiler, '-fvisibility=hidden'): + opts.append('-fvisibility=hidden') + elif ct == 'msvc': + opts.append('/DVERSION_INFO=\\"%s\\"' % + self.distribution.get_version()) + + for ext in self.extensions: + ext.extra_compile_args.extend(opts) + ext.extra_link_args.extend(self.link_opts.get(ct, [])) + + build_ext.build_extensions(self) + + +setup( + name='glassppy', + version=__version__, + description='Graph Library for Approximate Similarity Search', + author='', + long_description="""Graph Library for Approximate Similarity Search""", + ext_modules=ext_modules, + install_requires=['numpy'], + packages=['ann_dataset'], + cmdclass={'build_ext': BuildExt}, + zip_safe=False, +) +