'''
格式：直接cid为自带的index位；aid放不下了，通过字典来查，反正就5w个
'''
import faiss,numpy as np,os

# ###########如果是原始特征要先写save
inp_root=r"E:\codes\py39\dataset\mi\2-co256"
npys=[]
for name in sorted(list(os.listdir(inp_root))):
    phone=np.load("%s/%s"%(inp_root,name))
    npys.append(phone)
big_npy=np.concatenate(npys,0)
print(big_npy.shape)#(6196072, 192)#fp32#4.43G
np.save("infer/big_src_feature_mi.npy",big_npy)

##################train+add
# big_npy=np.load("/bili-coeus/jupyter/jupyterhub-liujing04/vits_ch/inference_f0/big_src_feature_mi.npy")
print(big_npy.shape)
index = faiss.index_factory(256, "IVF512,Flat")#mi
print("training")
index_ivf = faiss.extract_index_ivf(index)#
index_ivf.nprobe = 9
index.train(big_npy)
faiss.write_index(index, 'infer/trained_IVF512_Flat_mi_baseline_src_feat.index')
print("adding")
index.add(big_npy)
faiss.write_index(index,"infer/added_IVF512_Flat_mi_baseline_src_feat.index")
'''
大小（都是FP32）
big_src_feature 2.95G
    (3098036, 256)
big_emb         4.43G
    (6196072, 192)
big_emb双倍是因为求特征要repeat后再加pitch

'''