36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
'''
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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
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'''
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import faiss,numpy as np,os
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# ###########如果是原始特征要先写save
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inp_root=r"E:\codes\py39\dataset\mi\2-co256"
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npys=[]
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for name in sorted(list(os.listdir(inp_root))):
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phone=np.load("%s/%s"%(inp_root,name))
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npys.append(phone)
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big_npy=np.concatenate(npys,0)
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print(big_npy.shape)#(6196072, 192)#fp32#4.43G
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np.save("infer/big_src_feature_mi.npy",big_npy)
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##################train+add
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# big_npy=np.load("/bili-coeus/jupyter/jupyterhub-liujing04/vits_ch/inference_f0/big_src_feature_mi.npy")
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print(big_npy.shape)
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index = faiss.index_factory(256, "IVF512,Flat")#mi
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print("training")
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index_ivf = faiss.extract_index_ivf(index)#
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index_ivf.nprobe = 9
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index.train(big_npy)
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faiss.write_index(index, 'infer/trained_IVF512_Flat_mi_baseline_src_feat.index')
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print("adding")
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index.add(big_npy)
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faiss.write_index(index,"infer/added_IVF512_Flat_mi_baseline_src_feat.index")
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'''
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大小（都是FP32）
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big_src_feature 2.95G
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(3098036, 256)
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big_emb 4.43G
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(6196072, 192)
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big_emb双倍是因为求特征要repeat后再加pitch
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''' |