RVC-Boss
GitHub
parent
71e2733719
commit
a21f7ec11f
86
infer-web.py
86
infer-web.py
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@ -126,7 +126,7 @@ def vc_single(
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f0_file,
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f0_method,
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file_index,
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file_big_npy,
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# file_big_npy,
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index_rate,
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): # spk_item, input_audio0, vc_transform0,f0_file,f0method0
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global tgt_sr, net_g, vc, hubert_model
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@ -147,9 +147,9 @@ def vc_single(
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.strip(" ")
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.replace("trained", "added")
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) # 防止小白写错，自动帮他替换掉
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file_big_npy = (
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file_big_npy.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
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)
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# file_big_npy = (
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# file_big_npy.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
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# )
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audio_opt = vc.pipeline(
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hubert_model,
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net_g,
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@ -159,7 +159,7 @@ def vc_single(
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f0_up_key,
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f0_method,
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file_index,
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file_big_npy,
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# file_big_npy,
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index_rate,
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if_f0,
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f0_file=f0_file,
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@ -182,7 +182,7 @@ def vc_multi(
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f0_up_key,
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f0_method,
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file_index,
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file_big_npy,
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# file_big_npy,
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index_rate,
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):
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try:
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@ -200,6 +200,14 @@ def vc_multi(
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traceback.print_exc()
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paths = [path.name for path in paths]
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infos = []
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file_index = (
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file_index.strip(" ")
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.strip('"')
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.strip("\n")
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.strip('"')
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.strip(" ")
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.replace("trained", "added")
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) # 防止小白写错，自动帮他替换掉
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for path in paths:
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info, opt = vc_single(
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sid,
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@ -208,7 +216,7 @@ def vc_multi(
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None,
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f0_method,
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file_index,
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file_big_npy,
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# file_big_npy,
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index_rate,
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)
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if info == "Success":
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@ -629,29 +637,29 @@ def train_index(exp_dir1):
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phone = np.load("%s/%s" % (feature_dir, name))
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npys.append(phone)
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big_npy = np.concatenate(npys, 0)
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np.save("%s/total_fea.npy" % exp_dir, big_npy)
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n_ivf = big_npy.shape[0] // 39
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infos = []
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infos.append("%s,%s" % (big_npy.shape, n_ivf))
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# np.save("%s/total_fea.npy" % exp_dir, big_npy)
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# n_ivf = big_npy.shape[0] // 39
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n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])),big_npy.shape[0]// 39)
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infos=[]
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infos.append("%s,%s"%(big_npy.shape,n_ivf))
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yield "\n".join(infos)
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index = faiss.index_factory(256, "IVF%s,Flat" % n_ivf)
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index = faiss.index_factory(256, "IVF%s,Flat"%n_ivf)
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# index = faiss.index_factory(256, "IVF%s,PQ128x4fs,RFlat"%n_ivf)
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infos.append("training")
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yield "\n".join(infos)
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index_ivf = faiss.extract_index_ivf(index) #
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index_ivf.nprobe = int(np.power(n_ivf, 0.3))
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# index_ivf.nprobe = int(np.power(n_ivf,0.3))
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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,
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"%s/trained_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe),
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)
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faiss.write_index(index, '%s/trained_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
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# faiss.write_index(index, '%s/trained_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
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infos.append("adding")
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yield "\n".join(infos)
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index.add(big_npy)
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faiss.write_index(
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index,
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"%s/added_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe),
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)
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infos.append("成功构建索引, added_IVF%s_Flat_nprobe_%s.index" % (n_ivf, index_ivf.nprobe))
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faiss.write_index(index, '%s/added_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
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infos.append("成功构建索引，added_IVF%s_Flat_nprobe_%s.index"%(n_ivf,index_ivf.nprobe))
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# faiss.write_index(index, '%s/added_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
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# infos.append("成功构建索引，added_IVF%s_Flat_FastScan.index"%(n_ivf))
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yield "\n".join(infos)
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@ -842,13 +850,15 @@ def train1key(
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phone = np.load("%s/%s" % (feature_dir, name))
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npys.append(phone)
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big_npy = np.concatenate(npys, 0)
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np.save("%s/total_fea.npy" % exp_dir, big_npy)
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n_ivf = big_npy.shape[0] // 39
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# np.save("%s/total_fea.npy" % exp_dir, big_npy)
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# n_ivf = big_npy.shape[0] // 39
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n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])),big_npy.shape[0]// 39)
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yield get_info_str("%s,%s" % (big_npy.shape, n_ivf))
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index = faiss.index_factory(256, "IVF%s,Flat" % n_ivf)
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yield get_info_str("training index")
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index_ivf = faiss.extract_index_ivf(index) #
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index_ivf.nprobe = int(np.power(n_ivf, 0.3))
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# index_ivf.nprobe = int(np.power(n_ivf,0.3))
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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,
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@ -1022,16 +1032,16 @@ with gr.Blocks() as app:
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value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index",
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interactive=True,
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)
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file_big_npy1 = gr.Textbox(
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label=i18n("特征文件路径"),
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value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
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interactive=True,
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)
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# file_big_npy1 = gr.Textbox(
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# label=i18n("特征文件路径"),
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# value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
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# interactive=True,
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# )
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index_rate1 = gr.Slider(
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minimum=0,
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maximum=1,
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label="检索特征占比",
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value=0.6,
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value=0.65,
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interactive=True,
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)
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f0_file = gr.File(label=i18n("F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调"))
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@ -1048,7 +1058,7 @@ with gr.Blocks() as app:
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f0_file,
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f0method0,
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file_index1,
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file_big_npy1,
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# file_big_npy1,
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index_rate1,
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],
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[vc_output1, vc_output2],
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@ -1075,11 +1085,11 @@ with gr.Blocks() as app:
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value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index",
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interactive=True,
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)
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file_big_npy2 = gr.Textbox(
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label=i18n("特征文件路径"),
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value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
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interactive=True,
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)
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# file_big_npy2 = gr.Textbox(
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# label=i18n("特征文件路径"),
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# value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
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# interactive=True,
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# )
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index_rate2 = gr.Slider(
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minimum=0,
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maximum=1,
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@ -1107,7 +1117,7 @@ with gr.Blocks() as app:
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vc_transform1,
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f0method1,
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file_index2,
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file_big_npy2,
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# file_big_npy2,
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index_rate2,
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],
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[vc_output3],
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