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total_fea not needed now

total_fea not needed now
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RVC-Boss 2023-04-26 19:12:47 +08:00 committed by GitHub
parent 71e2733719
commit a21f7ec11f
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@ -126,7 +126,7 @@ def vc_single(
f0_file,
f0_method,
file_index,
file_big_npy,
# file_big_npy,
index_rate,
): # spk_item, input_audio0, vc_transform0,f0_file,f0method0
global tgt_sr, net_g, vc, hubert_model
@ -147,9 +147,9 @@ def vc_single(
.strip(" ")
.replace("trained", "added")
) # 防止小白写错,自动帮他替换掉
file_big_npy = (
file_big_npy.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
)
# file_big_npy = (
# file_big_npy.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
# )
audio_opt = vc.pipeline(
hubert_model,
net_g,
@ -159,7 +159,7 @@ def vc_single(
f0_up_key,
f0_method,
file_index,
file_big_npy,
# file_big_npy,
index_rate,
if_f0,
f0_file=f0_file,
@ -182,7 +182,7 @@ def vc_multi(
f0_up_key,
f0_method,
file_index,
file_big_npy,
# file_big_npy,
index_rate,
):
try:
@ -200,6 +200,14 @@ def vc_multi(
traceback.print_exc()
paths = [path.name for path in paths]
infos = []
file_index = (
file_index.strip(" ")
.strip('"')
.strip("\n")
.strip('"')
.strip(" ")
.replace("trained", "added")
) # 防止小白写错,自动帮他替换掉
for path in paths:
info, opt = vc_single(
sid,
@ -208,7 +216,7 @@ def vc_multi(
None,
f0_method,
file_index,
file_big_npy,
# file_big_npy,
index_rate,
)
if info == "Success":
@ -629,29 +637,29 @@ def train_index(exp_dir1):
phone = np.load("%s/%s" % (feature_dir, name))
npys.append(phone)
big_npy = np.concatenate(npys, 0)
np.save("%s/total_fea.npy" % exp_dir, big_npy)
n_ivf = big_npy.shape[0] // 39
infos = []
infos.append("%s,%s" % (big_npy.shape, n_ivf))
# np.save("%s/total_fea.npy" % exp_dir, big_npy)
# n_ivf = big_npy.shape[0] // 39
n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])),big_npy.shape[0]// 39)
infos=[]
infos.append("%s,%s"%(big_npy.shape,n_ivf))
yield "\n".join(infos)
index = faiss.index_factory(256, "IVF%s,Flat" % n_ivf)
index = faiss.index_factory(256, "IVF%s,Flat"%n_ivf)
# index = faiss.index_factory(256, "IVF%s,PQ128x4fs,RFlat"%n_ivf)
infos.append("training")
yield "\n".join(infos)
index_ivf = faiss.extract_index_ivf(index) #
index_ivf.nprobe = int(np.power(n_ivf, 0.3))
# index_ivf.nprobe = int(np.power(n_ivf,0.3))
index_ivf.nprobe = 1
index.train(big_npy)
faiss.write_index(
index,
"%s/trained_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe),
)
faiss.write_index(index, '%s/trained_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
# faiss.write_index(index, '%s/trained_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
infos.append("adding")
yield "\n".join(infos)
index.add(big_npy)
faiss.write_index(
index,
"%s/added_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe),
)
infos.append("成功构建索引, added_IVF%s_Flat_nprobe_%s.index" % (n_ivf, index_ivf.nprobe))
faiss.write_index(index, '%s/added_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
infos.append("成功构建索引added_IVF%s_Flat_nprobe_%s.index"%(n_ivf,index_ivf.nprobe))
# faiss.write_index(index, '%s/added_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
# infos.append("成功构建索引added_IVF%s_Flat_FastScan.index"%(n_ivf))
yield "\n".join(infos)
@ -842,13 +850,15 @@ def train1key(
phone = np.load("%s/%s" % (feature_dir, name))
npys.append(phone)
big_npy = np.concatenate(npys, 0)
np.save("%s/total_fea.npy" % exp_dir, big_npy)
n_ivf = big_npy.shape[0] // 39
# np.save("%s/total_fea.npy" % exp_dir, big_npy)
# n_ivf = big_npy.shape[0] // 39
n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])),big_npy.shape[0]// 39)
yield get_info_str("%s,%s" % (big_npy.shape, n_ivf))
index = faiss.index_factory(256, "IVF%s,Flat" % n_ivf)
yield get_info_str("training index")
index_ivf = faiss.extract_index_ivf(index) #
index_ivf.nprobe = int(np.power(n_ivf, 0.3))
# index_ivf.nprobe = int(np.power(n_ivf,0.3))
index_ivf.nprobe = 1
index.train(big_npy)
faiss.write_index(
index,
@ -1022,16 +1032,16 @@ with gr.Blocks() as app:
value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index",
interactive=True,
)
file_big_npy1 = gr.Textbox(
label=i18n("特征文件路径"),
value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
interactive=True,
)
# file_big_npy1 = gr.Textbox(
# label=i18n("特征文件路径"),
# value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
# interactive=True,
# )
index_rate1 = gr.Slider(
minimum=0,
maximum=1,
label="检索特征占比",
value=0.6,
value=0.65,
interactive=True,
)
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"))
@ -1048,7 +1058,7 @@ with gr.Blocks() as app:
f0_file,
f0method0,
file_index1,
file_big_npy1,
# file_big_npy1,
index_rate1,
],
[vc_output1, vc_output2],
@ -1075,11 +1085,11 @@ with gr.Blocks() as app:
value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index",
interactive=True,
)
file_big_npy2 = gr.Textbox(
label=i18n("特征文件路径"),
value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
interactive=True,
)
# file_big_npy2 = gr.Textbox(
# label=i18n("特征文件路径"),
# value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
# interactive=True,
# )
index_rate2 = gr.Slider(
minimum=0,
maximum=1,
@ -1107,7 +1117,7 @@ with gr.Blocks() as app:
vc_transform1,
f0method1,
file_index2,
file_big_npy2,
# file_big_npy2,
index_rate2,
],
[vc_output3],