update index training script v2 (#643)
* update index training script v2 * Apply Code Formatter Change --------- Co-authored-by: gak123 <gak123@users.noreply.github.com>
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@ -2,9 +2,15 @@
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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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from sklearn.cluster import MiniBatchKMeans
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import traceback
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from multiprocessing import cpu_count
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# ###########如果是原始特征要先写save
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inp_root = r"./logs/nene/3_feature768"
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n_cpu = 0
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if n_cpu == 0:
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n_cpu = cpu_count()
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inp_root = r"./logs/anz/3_feature768"
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npys = []
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listdir_res = list(os.listdir(inp_root))
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for name in sorted(listdir_res):
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@ -15,7 +21,27 @@ big_npy_idx = np.arange(big_npy.shape[0])
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np.random.shuffle(big_npy_idx)
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big_npy = big_npy[big_npy_idx]
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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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if big_npy.shape[0] > 2e5:
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# if(1):
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info = "Trying doing kmeans %s shape to 10k centers." % big_npy.shape[0]
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print(info)
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try:
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big_npy = (
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MiniBatchKMeans(
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n_clusters=10000,
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verbose=True,
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batch_size=256 * n_cpu,
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compute_labels=False,
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init="random",
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)
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.fit(big_npy)
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.cluster_centers_
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)
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except:
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info = traceback.format_exc()
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print(info)
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np.save("tools/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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@ -26,13 +52,15 @@ index_ivf = faiss.extract_index_ivf(index) #
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index_ivf.nprobe = 1
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index.train(big_npy)
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faiss.write_index(
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index, "infer/trained_IVF%s_Flat_baseline_src_feat_v2.index" % (n_ivf)
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index, "tools/infer/trained_IVF%s_Flat_baseline_src_feat_v2.index" % (n_ivf)
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)
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print("adding")
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batch_size_add = 8192
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for i in range(0, big_npy.shape[0], batch_size_add):
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index.add(big_npy[i : i + batch_size_add])
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faiss.write_index(index, "infer/added_IVF%s_Flat_mi_baseline_src_feat.index" % (n_ivf))
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faiss.write_index(
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index, "tools/infer/added_IVF%s_Flat_mi_baseline_src_feat.index" % (n_ivf)
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)
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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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