WIP

embs_to_faiss.py

@@ -119,25 +119,55 @@ def gen_index_filename(config: FaissConfig, target_local_ds: str) -> str:
 
 
 def gen_faiss_index(config: FaissConfig, dim: str, use_gpu: bool):
-    flat_l2 = faiss.IndexFlatL2(dim)
+    if use_gpu and config.m > 48:
+        return gen_faiss_index_f16_lookup(config, dim, use_gpu)
+    # quantizer = faiss.IndexFlatL2(dim)
     if not config.quantization:
-        faiss_index = flat_l2
+        faiss_index = faiss.IndexFlatL2(dim)
     else:
+        # faiss_index = faiss.IndexHNSWSQ(dim, faiss.ScalarQuantizer.QT_8bit, 16)
+        # faiss_index.hnsw.efConstruction = 512
+        # index.hnsw.efSearch = 128
+        # quantizer = faiss.IndexHNSWFlat(dim, 32)
+        quantizer = faiss.IndexFlatL2(dim)
+
         faiss_index = faiss.IndexIVFPQ(
-            flat_l2,
+            quantizer,
             dim,
             config.nlist,
             config.m,
             config.mbit,
         )
-    if use_gpu:
-        gpu_res = faiss.StandardGpuResources()  # use a single GPU
+        # faiss_index = faiss.IndexIVFFlat(quantizer, dim, 16384)
+        # faiss_index.cp.min_points_per_centroid = 5  # quiet warning
+        # faiss_index.quantizer_trains_alone = 2
+    if use_gpu and getattr(faiss, "StandardGpuResources", None):
+        gpu_res = faiss.StandardGpuResources()
         faiss_index = faiss.index_cpu_to_gpu(gpu_res, 0, faiss_index)
         return faiss_index
     else:
         return faiss_index
 
 
+def gen_faiss_index_f16_lookup(config: FaissConfig, dim: str, use_gpu: bool):
+    # use float16 lookup tables
+    gpu_resource = faiss.StandardGpuResources()  # GPUリソースの初期化
+    gpu_index_config = faiss.GpuIndexIVFPQConfig()  # IVFPQインデックスの設定用オブジェクト
+    gpu_index_config.useFloat16LookupTables = True  # Float16ルックアップテーブルを使用する
+    quantizer = faiss.IndexFlatL2(dim)  # 量子化器の定義
+    index = faiss.GpuIndexIVFPQ(
+        gpu_resource,
+        # quantizer,
+        dim,
+        config.nlist,
+        config.m,
+        config.mbit,
+        faiss.METRIC_L2,
+        gpu_index_config,  # IVFPQインデックスの設定用オブジェクト
+    )  # GPU上のIVFPQインデックスの作成
+    return index
+
+
 output_faiss_path = Path(
     "/".join(
         [
@@ -160,30 +190,42 @@ if output_faiss_path.exists():
         exit(0)
 
 
-pbar = tqdm(total=len(input_embs_npz))
-emb_total = 0
-for idx, npz_file in enumerate(input_embs_npz):
+# pbar = tqdm(total=len(input_embs_npz))
+# emb_total = 0
+all_embs = []
+for idx, npz_file in enumerate(tqdm(input_embs_npz)):
     with np.load(npz_file) as data:
-        embs = data["embs"].astype("float32")
-        if idx == 0:
-            dim = embs.shape[1]
-            if faiss_config.nlist is None:
-                faiss_config.nlist = int(np.sqrt(len(embs) * (len(input_embs_npz)-1)))
-                if faiss_config.nlist < 1:
-                    faiss_config.nlist = 100
-            print(f"faiss_config: {faiss_config}")
-            if args.use_gpu:
-                print("use gpu for faiss index")
-            faiss_index = gen_faiss_index(faiss_config, dim, args.use_gpu)
-            faiss_index.train(embs)  # type: ignore
-        faiss_index.add(embs)  # type: ignore
-        pbar.update(1)
-        emb_total += len(embs)
-        pbar.set_description(f"added embs: {emb_total}")
-pbar.close()
+        e = data["embs"].astype("float16")
+    all_embs.append(e)
+embs: np.ndarray = np.concatenate(all_embs, axis=0, dtype="float32")
+del all_embs
+
+# if idx == 0:
+dim = embs.shape[1]
+if faiss_config.nlist is None:
+    faiss_config.nlist = int(np.sqrt(len(embs) * (len(input_embs_npz) - 1)))
+    if faiss_config.nlist < 1:
+        faiss_config.nlist = 100
+print(f"faiss_config: {faiss_config}")
+if args.use_gpu:
+    print("use gpu for faiss index")
+faiss_index = gen_faiss_index(faiss_config, dim, args.use_gpu)
+print(f"start training faiss index, shape: {embs.shape}")
+faiss_index.train(embs)  # type: ignore
+print(f"start adding embs to faiss index")
+faiss_index.add(embs)  # type: ignore
+# pbar.update(1)
+print(f"added embs: {embs.shape[0]}")
+# pbar.set_description(f"added embs: {emb_total}")
+# pbar.close()
 
 faiss_index.nprobe = 10  # type: ignore
 if args.use_gpu:
     faiss_index = faiss.index_gpu_to_cpu(faiss_index)  # type: ignore
 faiss.write_index(faiss_index, str(output_faiss_path))  # type: ignore
 print("output faiss index file:", output_faiss_path)
+# output_faiss_path のファイルサイズを MB で表示
+print(
+    "output faiss index file size (MB):",
+    int(output_faiss_path.stat().st_size / 1024 / 1024),
+)