Initial commit

packages/leann-backend-diskann/third_party/DiskANN/python/apps/insert-in-clustered-order.py

@@ -0,0 +1,103 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT license.
+
+import argparse
+
+import diskannpy
+import numpy as np
+import utils
+
+
+def insert_and_search(
+    dtype_str,
+    indexdata_file,
+    querydata_file,
+    Lb,
+    graph_degree,
+    num_clusters,
+    num_insert_threads,
+    K,
+    Ls,
+    num_search_threads,
+    gt_file,
+):
+    npts, ndims = utils.get_bin_metadata(indexdata_file)
+
+    if dtype_str == "float":
+        dtype = np.float32
+    elif dtype_str == "int8":
+        dtype = np.int8
+    elif dtype_str == "uint8":
+        dtype = np.uint8
+    else:
+        raise ValueError("data_type must be float, int8 or uint8")
+
+    index = diskannpy.DynamicMemoryIndex(
+        distance_metric="l2",
+        vector_dtype=dtype,
+        dimensions=ndims,
+        max_vectors=npts,
+        complexity=Lb,
+        graph_degree=graph_degree
+    )
+    queries = diskannpy.vectors_from_file(querydata_file, dtype)
+    data = diskannpy.vectors_from_file(indexdata_file, dtype)
+
+    offsets, permutation = utils.cluster_and_permute(
+        dtype_str, npts, ndims, data, num_clusters
+    )
+
+    i = 0
+    timer = utils.Timer()
+    for c in range(num_clusters):
+        cluster_index_range = range(offsets[c], offsets[c + 1])
+        cluster_indices = np.array(permutation[cluster_index_range], dtype=np.uint32)
+        cluster_data = data[cluster_indices, :]
+        index.batch_insert(cluster_data, cluster_indices + 1, num_insert_threads)
+        print('Inserted cluster', c, 'in', timer.elapsed(), 's')
+    tags, dists = index.batch_search(queries, K, Ls, num_search_threads)
+    print('Batch searched', queries.shape[0], 'queries in', timer.elapsed(), 's')
+    res_ids = tags - 1
+
+    if gt_file != "":
+        recall = utils.calculate_recall_from_gt_file(K, res_ids, gt_file)
+        print(f"recall@{K} is {recall}")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        prog="in-mem-dynamic",
+        description="Inserts points dynamically in a clustered order and search from vectors in a file.",
+    )
+
+    parser.add_argument("-d", "--data_type", required=True)
+    parser.add_argument("-i", "--indexdata_file", required=True)
+    parser.add_argument("-q", "--querydata_file", required=True)
+    parser.add_argument("-Lb", "--Lbuild", default=50, type=int)
+    parser.add_argument("-Ls", "--Lsearch", default=50, type=int)
+    parser.add_argument("-R", "--graph_degree", default=32, type=int)
+    parser.add_argument("-TI", "--num_insert_threads", default=8, type=int)
+    parser.add_argument("-TS", "--num_search_threads", default=8, type=int)
+    parser.add_argument("-C", "--num_clusters", default=32, type=int)
+    parser.add_argument("-K", default=10, type=int)
+    parser.add_argument("--gt_file", default="")
+    args = parser.parse_args()
+
+    insert_and_search(
+        args.data_type,
+        args.indexdata_file,
+        args.querydata_file,
+        args.Lbuild,
+        args.graph_degree,  # Build args
+        args.num_clusters,
+        args.num_insert_threads,
+        args.K,
+        args.Lsearch,
+        args.num_search_threads,  # search args
+        args.gt_file,
+    )
+
+# An ingest optimized example with SIFT1M
+# python3 ~/DiskANN/python/apps/insert-in-clustered-order.py -d float \
+# -i sift_base.fbin -q sift_query.fbin --gt_file  gt100_base \
+# -Lb 10 -R 30 -Ls 200 -C 32