|
import os |
|
import sys |
|
import faiss |
|
import logging |
|
import argparse |
|
import logging.handlers |
|
|
|
import numpy as np |
|
|
|
from multiprocessing import cpu_count |
|
from sklearn.cluster import MiniBatchKMeans |
|
|
|
|
|
now_dir = os.getcwd() |
|
sys.path.append(now_dir) |
|
|
|
from main.configs.config import Config |
|
|
|
translations = Config().translations |
|
|
|
|
|
def parse_arguments() -> tuple: |
|
parser = argparse.ArgumentParser() |
|
parser.add_argument("--model_name", type=str, required=True) |
|
parser.add_argument("--rvc_version", type=str, default="v2") |
|
parser.add_argument("--index_algorithm", type=str, default="Auto") |
|
|
|
args = parser.parse_args() |
|
return args |
|
|
|
|
|
def main(): |
|
args = parse_arguments() |
|
|
|
exp_dir = os.path.join("assets", "logs", args.model_name) |
|
version = args.rvc_version |
|
index_algorithm = args.index_algorithm |
|
|
|
log_file = os.path.join(exp_dir, "create_index.log") |
|
logger = logging.getLogger(__name__) |
|
|
|
|
|
if logger.hasHandlers(): logger.handlers.clear() |
|
else: |
|
console_handler = logging.StreamHandler() |
|
console_formatter = logging.Formatter(fmt="\n%(asctime)s.%(msecs)03d | %(levelname)s | %(module)s | %(message)s", datefmt="%Y-%m-%d %H:%M:%S") |
|
|
|
console_handler.setFormatter(console_formatter) |
|
console_handler.setLevel(logging.INFO) |
|
|
|
file_handler = logging.handlers.RotatingFileHandler(log_file, maxBytes=5*1024*1024, backupCount=3, encoding='utf-8') |
|
file_formatter = logging.Formatter(fmt="\n%(asctime)s.%(msecs)03d | %(levelname)s | %(module)s | %(message)s", datefmt="%Y-%m-%d %H:%M:%S") |
|
|
|
file_handler.setFormatter(file_formatter) |
|
file_handler.setLevel(logging.DEBUG) |
|
|
|
logger.addHandler(console_handler) |
|
logger.addHandler(file_handler) |
|
logger.setLevel(logging.DEBUG) |
|
|
|
logger.debug(f"{translations['modelname']}: {args.model_name}") |
|
logger.debug(f"{translations['model_path']}: {exp_dir}") |
|
logger.debug(f"{translations['training_version']}: {version}") |
|
logger.debug(f"{translations['index_algorithm_info']}: {index_algorithm}") |
|
|
|
|
|
try: |
|
feature_dir = os.path.join(exp_dir, f"{version}_extracted") |
|
model_name = os.path.basename(exp_dir) |
|
|
|
npys = [] |
|
listdir_res = sorted(os.listdir(feature_dir)) |
|
|
|
for name in listdir_res: |
|
file_path = os.path.join(feature_dir, name) |
|
phone = np.load(file_path) |
|
npys.append(phone) |
|
|
|
big_npy = np.concatenate(npys, axis=0) |
|
big_npy_idx = np.arange(big_npy.shape[0]) |
|
|
|
np.random.shuffle(big_npy_idx) |
|
|
|
big_npy = big_npy[big_npy_idx] |
|
|
|
if big_npy.shape[0] > 2e5 and (index_algorithm == "Auto" or index_algorithm == "KMeans"): big_npy = (MiniBatchKMeans(n_clusters=10000, verbose=True, batch_size=256 * cpu_count(), compute_labels=False, init="random").fit(big_npy).cluster_centers_) |
|
|
|
np.save(os.path.join(exp_dir, "total_fea.npy"), big_npy) |
|
|
|
n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])), big_npy.shape[0] // 39) |
|
|
|
index_trained = faiss.index_factory(256 if version == "v1" else 768, f"IVF{n_ivf},Flat") |
|
|
|
index_ivf_trained = faiss.extract_index_ivf(index_trained) |
|
index_ivf_trained.nprobe = 1 |
|
|
|
index_trained.train(big_npy) |
|
|
|
faiss.write_index(index_trained, os.path.join(exp_dir, f"trained_IVF{n_ivf}_Flat_nprobe_{index_ivf_trained.nprobe}_{model_name}_{version}.index")) |
|
|
|
index_added = faiss.index_factory(256 if version == "v1" else 768, f"IVF{n_ivf},Flat") |
|
index_ivf_added = faiss.extract_index_ivf(index_added) |
|
|
|
index_ivf_added.nprobe = 1 |
|
index_added.train(big_npy) |
|
|
|
batch_size_add = 8192 |
|
|
|
for i in range(0, big_npy.shape[0], batch_size_add): |
|
index_added.add(big_npy[i : i + batch_size_add]) |
|
|
|
index_filepath_added = os.path.join(exp_dir, f"added_IVF{n_ivf}_Flat_nprobe_{index_ivf_added.nprobe}_{model_name}_{version}.index") |
|
|
|
faiss.write_index(index_added, index_filepath_added) |
|
|
|
logger.info(f"{translations['save_index']} '{index_filepath_added}'") |
|
except Exception as e: |
|
logger.error(f"{translations['create_index_error']}: {e}") |
|
|
|
if __name__ == "__main__": main() |