mirror of
https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2025-05-06 20:01:37 +08:00
feat: model embed author
This commit is contained in:
源文雨
parent
ccecac6133
commit
07c66d3676
567
infer-web.py
567
infer-web.py
@ -480,6 +480,7 @@ def click_train(
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if_cache_gpu17,
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if_save_every_weights18,
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version19,
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author,
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):
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# 生成filelist
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exp_dir = "%s/logs/%s" % (now_dir, exp_dir1)
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@ -548,8 +549,6 @@ def click_train(
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with open("%s/filelist.txt" % exp_dir, "w") as f:
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f.write("\n".join(opt))
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logger.debug("Write filelist done")
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# 生成config#无需生成config
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# cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e mi-test -sr 40k -f0 1 -bs 4 -g 0 -te 10 -se 5 -pg pretrained/f0G40k.pth -pd pretrained/f0D40k.pth -l 1 -c 0"
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logger.info("Use gpus: %s", str(gpus16))
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if pretrained_G14 == "":
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logger.info("No pretrained Generator")
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@ -570,45 +569,25 @@ def click_train(
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sort_keys=True,
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)
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f.write("\n")
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cmd = '"%s" infer/modules/train/train.py -e "%s" -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s -a "%s"' % (
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config.python_cmd,
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exp_dir1,
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sr2,
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1 if if_f0_3 else 0,
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batch_size12,
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total_epoch11,
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save_epoch10,
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'-pg "%s"' % pretrained_G14 if pretrained_G14 != "" else "",
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'-pd "%s"' % pretrained_D15 if pretrained_D15 != "" else "",
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1 if if_save_latest13 == i18n("是") else 0,
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1 if if_cache_gpu17 == i18n("是") else 0,
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1 if if_save_every_weights18 == i18n("是") else 0,
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version19,
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author
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)
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if gpus16:
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cmd = (
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'"%s" infer/modules/train/train.py -e "%s" -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
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% (
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config.python_cmd,
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exp_dir1,
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sr2,
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1 if if_f0_3 else 0,
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batch_size12,
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gpus16,
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total_epoch11,
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save_epoch10,
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"-pg %s" % pretrained_G14 if pretrained_G14 != "" else "",
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"-pd %s" % pretrained_D15 if pretrained_D15 != "" else "",
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1 if if_save_latest13 == i18n("是") else 0,
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1 if if_cache_gpu17 == i18n("是") else 0,
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1 if if_save_every_weights18 == i18n("是") else 0,
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version19,
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)
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)
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else:
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cmd = (
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'"%s" infer/modules/train/train.py -e "%s" -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
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% (
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config.python_cmd,
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exp_dir1,
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sr2,
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1 if if_f0_3 else 0,
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batch_size12,
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total_epoch11,
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save_epoch10,
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"-pg %s" % pretrained_G14 if pretrained_G14 != "" else "",
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"-pd %s" % pretrained_D15 if pretrained_D15 != "" else "",
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1 if if_save_latest13 == i18n("是") else 0,
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1 if if_cache_gpu17 == i18n("是") else 0,
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1 if if_save_every_weights18 == i18n("是") else 0,
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version19,
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)
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)
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cmd += '-g "%s"' % (gpus16)
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logger.info("Execute: " + cmd)
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p = Popen(cmd, shell=True, cwd=now_dir)
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p.wait()
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@ -734,6 +713,7 @@ def train1key(
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if_save_every_weights18,
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version19,
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gpus_rmvpe,
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author
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):
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infos = []
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@ -771,6 +751,7 @@ def train1key(
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if_cache_gpu17,
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if_save_every_weights18,
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version19,
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author
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)
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yield get_info_str(
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i18n("训练结束, 您可查看控制台训练日志或实验文件夹下的train.log")
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@ -837,7 +818,7 @@ with gr.Blocks(title="RVC WebUI") as app:
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clean_button.click(
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fn=clean, inputs=[], outputs=[sid0], api_name="infer_clean"
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)
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modelinfo = gr.Textbox(label=i18n("模型信息"))
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modelinfo = gr.Textbox(label=i18n("模型信息"), max_lines=8)
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with gr.TabItem(i18n("单次推理")):
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with gr.Group():
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with gr.Row():
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@ -1066,8 +1047,7 @@ with gr.Blocks(title="RVC WebUI") as app:
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interactive=True,
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)
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but1 = gr.Button(i18n("转换"), variant="primary")
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vc_output3 = gr.Textbox(label=i18n("输出信息"))
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vc_output3 = gr.Textbox(label=i18n("输出信息"))
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but1.click(
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vc.vc_multi,
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@ -1165,11 +1145,21 @@ with gr.Blocks(title="RVC WebUI") as app:
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with gr.TabItem(i18n("训练")):
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gr.Markdown(
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value=i18n(
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"step1: 填写实验配置. 实验数据放在logs下, 每个实验一个文件夹, 需手工输入实验名路径, 内含实验配置, 日志, 训练得到的模型文件. "
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"### 第一步 填写实验配置\n实验数据放在logs下, 每个实验一个文件夹, 需手工输入实验名路径, 内含实验配置, 日志, 训练得到的模型文件."
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)
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)
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with gr.Row():
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exp_dir1 = gr.Textbox(label=i18n("输入实验名"), value="mi-test")
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author = gr.Textbox(label=i18n("模型作者(可空)"))
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np7 = gr.Slider(
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minimum=0,
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maximum=config.n_cpu,
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step=1,
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label=i18n("提取音高和处理数据使用的CPU进程数"),
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value=int(np.ceil(config.n_cpu / 1.5)),
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interactive=True,
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)
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with gr.Row():
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sr2 = gr.Radio(
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label=i18n("目标采样率"),
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choices=["40k", "48k"],
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@ -1189,49 +1179,46 @@ with gr.Blocks(title="RVC WebUI") as app:
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interactive=True,
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visible=True,
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)
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np7 = gr.Slider(
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minimum=0,
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maximum=config.n_cpu,
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step=1,
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label=i18n("提取音高和处理数据使用的CPU进程数"),
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value=int(np.ceil(config.n_cpu / 1.5)),
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interactive=True,
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)
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with gr.Group(): # 暂时单人的, 后面支持最多4人的#数据处理
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gr.Markdown(
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value=i18n(
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"step2a: 自动遍历训练文件夹下所有可解码成音频的文件并进行切片归一化, 在实验目录下生成2个wav文件夹; 暂时只支持单人训练. "
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)
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)
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with gr.Row():
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trainset_dir4 = gr.Textbox(
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label=i18n("输入训练文件夹路径"),
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value=i18n("E:\\语音音频+标注\\米津玄师\\src"),
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)
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spk_id5 = gr.Slider(
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minimum=0,
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maximum=4,
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step=1,
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label=i18n("请指定说话人id"),
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value=0,
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interactive=True,
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)
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but1 = gr.Button(i18n("处理数据"), variant="primary")
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info1 = gr.Textbox(label=i18n("输出信息"), value="")
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but1.click(
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preprocess_dataset,
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[trainset_dir4, exp_dir1, sr2, np7],
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[info1],
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api_name="train_preprocess",
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)
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with gr.Group():
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gr.Markdown(
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value=i18n(
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"step2b: 使用CPU提取音高(如果模型带音高), 使用GPU提取特征(选择卡号)"
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"### 第二步 音频处理\n#### 1. 音频切片\n自动遍历训练文件夹下所有可解码成音频的文件并进行切片归一化, 在实验目录下生成2个wav文件夹; 暂时只支持单人训练."
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)
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)
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with gr.Row():
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with gr.Column():
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trainset_dir4 = gr.Textbox(
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label=i18n("输入训练文件夹路径"),
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value=i18n("E:\\语音音频+标注\\米津玄师\\src"),
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)
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spk_id5 = gr.Slider(
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minimum=0,
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maximum=4,
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step=1,
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label=i18n("请指定说话人id"),
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value=0,
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interactive=True,
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)
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but1 = gr.Button(i18n("处理数据"), variant="primary")
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with gr.Column():
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info1 = gr.Textbox(label=i18n("输出信息"), value="")
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but1.click(
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preprocess_dataset,
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[trainset_dir4, exp_dir1, sr2, np7],
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[info1],
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api_name="train_preprocess",
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)
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with gr.Group():
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gr.Markdown(
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value=i18n(
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"#### 2. 特征提取\n使用CPU提取音高(如果模型带音高), 使用GPU提取特征(选择卡号)."
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)
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)
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with gr.Row():
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with gr.Column():
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gpu_info9 = gr.Textbox(
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label=i18n("显卡信息"), value=gpu_info, visible=F0GPUVisible
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)
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gpus6 = gr.Textbox(
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label=i18n(
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"以-分隔输入使用的卡号, 例如 0-1-2 使用卡0和卡1和卡2"
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@ -1240,18 +1227,6 @@ with gr.Blocks(title="RVC WebUI") as app:
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interactive=True,
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visible=F0GPUVisible,
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)
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gpu_info9 = gr.Textbox(
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label=i18n("显卡信息"), value=gpu_info, visible=F0GPUVisible
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)
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with gr.Column():
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f0method8 = gr.Radio(
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label=i18n(
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"选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢,rmvpe效果最好且微吃CPU/GPU"
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),
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choices=["pm", "harvest", "dio", "rmvpe", "rmvpe_gpu"],
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value="rmvpe_gpu",
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interactive=True,
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)
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gpus_rmvpe = gr.Textbox(
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label=i18n(
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"rmvpe卡号配置：以-分隔输入使用的不同进程卡号,例如0-0-1使用在卡0上跑2个进程并在卡1上跑1个进程"
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@ -1260,8 +1235,17 @@ with gr.Blocks(title="RVC WebUI") as app:
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interactive=True,
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visible=F0GPUVisible,
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)
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but2 = gr.Button(i18n("特征提取"), variant="primary")
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info2 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
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f0method8 = gr.Radio(
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label=i18n(
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"选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢,rmvpe效果最好且微吃CPU/GPU"
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),
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choices=["pm", "harvest", "dio", "rmvpe", "rmvpe_gpu"],
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value="rmvpe_gpu",
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interactive=True,
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)
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with gr.Column():
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but2 = gr.Button(i18n("特征提取"), variant="primary")
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info2 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
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f0method8.change(
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fn=change_f0_method,
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inputs=[f0method8],
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@ -1282,90 +1266,93 @@ with gr.Blocks(title="RVC WebUI") as app:
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api_name="train_extract_f0_feature",
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)
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with gr.Group():
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gr.Markdown(value=i18n("step3: 填写训练设置, 开始训练模型和索引"))
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gr.Markdown(value=i18n("### 第三步 开始训练\n填写训练设置, 开始训练模型和索引."))
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with gr.Row():
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save_epoch10 = gr.Slider(
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minimum=1,
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maximum=50,
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step=1,
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label=i18n("保存频率save_every_epoch"),
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value=5,
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interactive=True,
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)
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total_epoch11 = gr.Slider(
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minimum=2,
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maximum=1000,
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step=1,
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label=i18n("总训练轮数total_epoch"),
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value=20,
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interactive=True,
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)
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batch_size12 = gr.Slider(
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minimum=1,
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maximum=40,
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step=1,
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label=i18n("每张显卡的batch_size"),
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value=default_batch_size,
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interactive=True,
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)
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if_save_latest13 = gr.Radio(
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label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"),
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choices=[i18n("是"), i18n("否")],
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value=i18n("否"),
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interactive=True,
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)
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if_cache_gpu17 = gr.Radio(
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label=i18n(
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"是否缓存所有训练集至显存. 10min以下小数据可缓存以加速训练, 大数据缓存会炸显存也加不了多少速"
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),
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choices=[i18n("是"), i18n("否")],
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value=i18n("否"),
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interactive=True,
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)
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if_save_every_weights18 = gr.Radio(
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label=i18n(
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"是否在每次保存时间点将最终小模型保存至weights文件夹"
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),
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choices=[i18n("是"), i18n("否")],
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value=i18n("否"),
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interactive=True,
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)
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with gr.Column():
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save_epoch10 = gr.Slider(
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minimum=1,
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maximum=50,
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step=1,
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label=i18n("保存频率save_every_epoch"),
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value=5,
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interactive=True,
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)
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total_epoch11 = gr.Slider(
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minimum=2,
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maximum=1000,
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step=1,
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label=i18n("总训练轮数total_epoch"),
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value=20,
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interactive=True,
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)
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batch_size12 = gr.Slider(
|
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minimum=1,
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maximum=40,
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step=1,
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label=i18n("每张显卡的batch_size"),
|
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value=default_batch_size,
|
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interactive=True,
|
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)
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if_save_latest13 = gr.Radio(
|
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label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"),
|
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choices=[i18n("是"), i18n("否")],
|
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value=i18n("否"),
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interactive=True,
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)
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if_cache_gpu17 = gr.Radio(
|
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label=i18n(
|
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"是否缓存所有训练集至显存. 10min以下小数据可缓存以加速训练, 大数据缓存会炸显存也加不了多少速"
|
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),
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choices=[i18n("是"), i18n("否")],
|
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value=i18n("否"),
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interactive=True,
|
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)
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if_save_every_weights18 = gr.Radio(
|
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label=i18n(
|
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"是否在每次保存时间点将最终小模型保存至weights文件夹"
|
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),
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choices=[i18n("是"), i18n("否")],
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value=i18n("否"),
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interactive=True,
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)
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with gr.Column():
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pretrained_G14 = gr.Textbox(
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label=i18n("加载预训练底模G路径"),
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value="assets/pretrained_v2/f0G40k.pth",
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interactive=True,
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)
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pretrained_D15 = gr.Textbox(
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label=i18n("加载预训练底模D路径"),
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value="assets/pretrained_v2/f0D40k.pth",
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interactive=True,
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)
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gpus16 = gr.Textbox(
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label=i18n(
|
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"以-分隔输入使用的卡号, 例如 0-1-2 使用卡0和卡1和卡2"
|
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),
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value=gpus,
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interactive=True,
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)
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sr2.change(
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change_sr2,
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[sr2, if_f0_3, version19],
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[pretrained_G14, pretrained_D15],
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)
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version19.change(
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change_version19,
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[sr2, if_f0_3, version19],
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[pretrained_G14, pretrained_D15, sr2],
|
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)
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if_f0_3.change(
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change_f0,
|
||||
[if_f0_3, sr2, version19],
|
||||
[f0method8, gpus_rmvpe, pretrained_G14, pretrained_D15],
|
||||
)
|
||||
|
||||
but3 = gr.Button(i18n("训练模型"), variant="primary")
|
||||
but4 = gr.Button(i18n("训练特征索引"), variant="primary")
|
||||
but5 = gr.Button(i18n("一键训练"), variant="primary")
|
||||
with gr.Row():
|
||||
pretrained_G14 = gr.Textbox(
|
||||
label=i18n("加载预训练底模G路径"),
|
||||
value="assets/pretrained_v2/f0G40k.pth",
|
||||
interactive=True,
|
||||
)
|
||||
pretrained_D15 = gr.Textbox(
|
||||
label=i18n("加载预训练底模D路径"),
|
||||
value="assets/pretrained_v2/f0D40k.pth",
|
||||
interactive=True,
|
||||
)
|
||||
sr2.change(
|
||||
change_sr2,
|
||||
[sr2, if_f0_3, version19],
|
||||
[pretrained_G14, pretrained_D15],
|
||||
)
|
||||
version19.change(
|
||||
change_version19,
|
||||
[sr2, if_f0_3, version19],
|
||||
[pretrained_G14, pretrained_D15, sr2],
|
||||
)
|
||||
if_f0_3.change(
|
||||
change_f0,
|
||||
[if_f0_3, sr2, version19],
|
||||
[f0method8, gpus_rmvpe, pretrained_G14, pretrained_D15],
|
||||
)
|
||||
gpus16 = gr.Textbox(
|
||||
label=i18n(
|
||||
"以-分隔输入使用的卡号, 例如 0-1-2 使用卡0和卡1和卡2"
|
||||
),
|
||||
value=gpus,
|
||||
interactive=True,
|
||||
)
|
||||
but3 = gr.Button(i18n("训练模型"), variant="primary")
|
||||
but4 = gr.Button(i18n("训练特征索引"), variant="primary")
|
||||
but5 = gr.Button(i18n("一键训练"), variant="primary")
|
||||
info3 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=10)
|
||||
but3.click(
|
||||
click_train,
|
||||
@ -1384,6 +1371,7 @@ with gr.Blocks(title="RVC WebUI") as app:
|
||||
if_cache_gpu17,
|
||||
if_save_every_weights18,
|
||||
version19,
|
||||
author,
|
||||
],
|
||||
info3,
|
||||
api_name="train_start",
|
||||
@ -1410,6 +1398,7 @@ with gr.Blocks(title="RVC WebUI") as app:
|
||||
if_save_every_weights18,
|
||||
version19,
|
||||
gpus_rmvpe,
|
||||
author,
|
||||
],
|
||||
info3,
|
||||
api_name="train_start_all",
|
||||
@ -1443,52 +1432,54 @@ with gr.Blocks(title="RVC WebUI") as app:
|
||||
with gr.Group():
|
||||
gr.Markdown(value=i18n("### 模型融合\n可用于测试音色融合"))
|
||||
with gr.Row():
|
||||
ckpt_a = gr.Textbox(
|
||||
label=i18n("A模型路径"), value="", interactive=True
|
||||
)
|
||||
ckpt_b = gr.Textbox(
|
||||
label=i18n("B模型路径"), value="", interactive=True
|
||||
)
|
||||
alpha_a = gr.Slider(
|
||||
minimum=0,
|
||||
maximum=1,
|
||||
label=i18n("A模型权重"),
|
||||
value=0.5,
|
||||
interactive=True,
|
||||
)
|
||||
with gr.Column():
|
||||
ckpt_a = gr.Textbox(
|
||||
label=i18n("A模型路径"), value="", interactive=True
|
||||
)
|
||||
ckpt_b = gr.Textbox(
|
||||
label=i18n("B模型路径"), value="", interactive=True
|
||||
)
|
||||
alpha_a = gr.Slider(
|
||||
minimum=0,
|
||||
maximum=1,
|
||||
label=i18n("A模型权重"),
|
||||
value=0.5,
|
||||
interactive=True,
|
||||
)
|
||||
with gr.Column():
|
||||
sr_ = gr.Radio(
|
||||
label=i18n("目标采样率"),
|
||||
choices=["40k", "48k"],
|
||||
value="40k",
|
||||
interactive=True,
|
||||
)
|
||||
if_f0_ = gr.Radio(
|
||||
label=i18n("模型是否带音高指导"),
|
||||
choices=[i18n("是"), i18n("否")],
|
||||
value=i18n("是"),
|
||||
interactive=True,
|
||||
)
|
||||
info__ = gr.Textbox(
|
||||
label=i18n("要置入的模型信息"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
with gr.Column():
|
||||
name_to_save0 = gr.Textbox(
|
||||
label=i18n("保存的模型名不带后缀"),
|
||||
value="",
|
||||
max_lines=1,
|
||||
interactive=True,
|
||||
)
|
||||
version_2 = gr.Radio(
|
||||
label=i18n("模型版本型号"),
|
||||
choices=["v1", "v2"],
|
||||
value="v1",
|
||||
interactive=True,
|
||||
)
|
||||
but6 = gr.Button(i18n("融合"), variant="primary")
|
||||
with gr.Row():
|
||||
sr_ = gr.Radio(
|
||||
label=i18n("目标采样率"),
|
||||
choices=["40k", "48k"],
|
||||
value="40k",
|
||||
interactive=True,
|
||||
)
|
||||
if_f0_ = gr.Radio(
|
||||
label=i18n("模型是否带音高指导"),
|
||||
choices=[i18n("是"), i18n("否")],
|
||||
value=i18n("是"),
|
||||
interactive=True,
|
||||
)
|
||||
info__ = gr.Textbox(
|
||||
label=i18n("要置入的模型信息"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
name_to_save0 = gr.Textbox(
|
||||
label=i18n("保存的模型名不带后缀"),
|
||||
value="",
|
||||
max_lines=1,
|
||||
interactive=True,
|
||||
)
|
||||
version_2 = gr.Radio(
|
||||
label=i18n("模型版本型号"),
|
||||
choices=["v1", "v2"],
|
||||
value="v1",
|
||||
interactive=True,
|
||||
)
|
||||
with gr.Row():
|
||||
but6 = gr.Button(i18n("融合"), variant="primary")
|
||||
info4 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
|
||||
but6.click(
|
||||
merge,
|
||||
@ -1512,24 +1503,25 @@ with gr.Blocks(title="RVC WebUI") as app:
|
||||
)
|
||||
)
|
||||
with gr.Row():
|
||||
ckpt_path0 = gr.Textbox(
|
||||
label=i18n("模型路径"), value="", interactive=True
|
||||
)
|
||||
info_ = gr.Textbox(
|
||||
label=i18n("要改的模型信息"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
name_to_save1 = gr.Textbox(
|
||||
label=i18n("保存的文件名, 默认空为和源文件同名"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
with gr.Row():
|
||||
but7 = gr.Button(i18n("修改"), variant="primary")
|
||||
info5 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
|
||||
with gr.Column():
|
||||
ckpt_path0 = gr.Textbox(
|
||||
label=i18n("模型路径"), value="", interactive=True
|
||||
)
|
||||
info_ = gr.Textbox(
|
||||
label=i18n("要改的模型信息"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
name_to_save1 = gr.Textbox(
|
||||
label=i18n("保存的文件名, 默认空为和源文件同名"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
with gr.Column():
|
||||
but7 = gr.Button(i18n("修改"), variant="primary")
|
||||
info5 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
|
||||
but7.click(
|
||||
change_info,
|
||||
[ckpt_path0, info_, name_to_save1],
|
||||
@ -1543,11 +1535,13 @@ with gr.Blocks(title="RVC WebUI") as app:
|
||||
)
|
||||
)
|
||||
with gr.Row():
|
||||
ckpt_path1 = gr.Textbox(
|
||||
label=i18n("模型路径"), value="", interactive=True
|
||||
)
|
||||
but8 = gr.Button(i18n("查看"), variant="primary")
|
||||
info6 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
|
||||
with gr.Column():
|
||||
ckpt_path1 = gr.Textbox(
|
||||
label=i18n("模型路径"), value="", interactive=True
|
||||
)
|
||||
but8 = gr.Button(i18n("查看"), variant="primary")
|
||||
with gr.Column():
|
||||
info6 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
|
||||
but8.click(show_info, [ckpt_path1], info6, api_name="ckpt_show")
|
||||
with gr.Group():
|
||||
gr.Markdown(
|
||||
@ -1556,46 +1550,55 @@ with gr.Blocks(title="RVC WebUI") as app:
|
||||
)
|
||||
)
|
||||
with gr.Row():
|
||||
ckpt_path2 = gr.Textbox(
|
||||
label=i18n("模型路径"),
|
||||
value="E:\\codes\\py39\\logs\\mi-test_f0_48k\\G_23333.pth",
|
||||
interactive=True,
|
||||
)
|
||||
save_name = gr.Textbox(
|
||||
label=i18n("保存名"), value="", interactive=True
|
||||
)
|
||||
sr__ = gr.Radio(
|
||||
label=i18n("目标采样率"),
|
||||
choices=["32k", "40k", "48k"],
|
||||
value="40k",
|
||||
interactive=True,
|
||||
)
|
||||
if_f0__ = gr.Radio(
|
||||
label=i18n("模型是否带音高指导,1是0否"),
|
||||
choices=["1", "0"],
|
||||
value="1",
|
||||
interactive=True,
|
||||
)
|
||||
version_1 = gr.Radio(
|
||||
label=i18n("模型版本型号"),
|
||||
choices=["v1", "v2"],
|
||||
value="v2",
|
||||
interactive=True,
|
||||
)
|
||||
info___ = gr.Textbox(
|
||||
label=i18n("要置入的模型信息"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
but9 = gr.Button(i18n("提取"), variant="primary")
|
||||
info7 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
|
||||
ckpt_path2.change(
|
||||
change_info_, [ckpt_path2], [sr__, if_f0__, version_1]
|
||||
)
|
||||
with gr.Column():
|
||||
ckpt_path2 = gr.Textbox(
|
||||
label=i18n("模型路径"),
|
||||
value="E:\\codes\\py39\\logs\\mi-test_f0_48k\\G_23333.pth",
|
||||
interactive=True,
|
||||
)
|
||||
save_name = gr.Textbox(
|
||||
label=i18n("保存名"), value="", interactive=True
|
||||
)
|
||||
with gr.Row():
|
||||
sr__ = gr.Radio(
|
||||
label=i18n("目标采样率"),
|
||||
choices=["32k", "40k", "48k"],
|
||||
value="40k",
|
||||
interactive=True,
|
||||
)
|
||||
if_f0__ = gr.Radio(
|
||||
label=i18n("模型是否带音高指导,1是0否"),
|
||||
choices=["1", "0"],
|
||||
value="1",
|
||||
interactive=True,
|
||||
)
|
||||
version_1 = gr.Radio(
|
||||
label=i18n("模型版本型号"),
|
||||
choices=["v1", "v2"],
|
||||
value="v2",
|
||||
interactive=True,
|
||||
)
|
||||
info___ = gr.Textbox(
|
||||
label=i18n("要置入的模型信息"),
|
||||
value="",
|
||||
max_lines=8,
|
||||
interactive=True,
|
||||
)
|
||||
extauthor = gr.Textbox(
|
||||
label=i18n("模型作者"),
|
||||
value="",
|
||||
max_lines=1,
|
||||
interactive=True,
|
||||
)
|
||||
with gr.Column():
|
||||
but9 = gr.Button(i18n("提取"), variant="primary")
|
||||
info7 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
|
||||
ckpt_path2.change(
|
||||
change_info_, [ckpt_path2], [sr__, if_f0__, version_1]
|
||||
)
|
||||
but9.click(
|
||||
extract_small_model,
|
||||
[ckpt_path2, save_name, sr__, if_f0__, info___, version_1],
|
||||
[ckpt_path2, save_name, extauthor, sr__, if_f0__, info___, version_1],
|
||||
info7,
|
||||
api_name="ckpt_extract",
|
||||
)
|
||||
|
||||
@ -43,6 +43,7 @@ def save_small_model(ckpt, sr, if_f0, name, epoch, version, hps):
|
||||
opt["info"] = "%sepoch" % epoch
|
||||
opt["name"] = name
|
||||
opt["timestamp"] = int(time())
|
||||
if hps.author: opt["author"] = hps.author
|
||||
opt["sr"] = sr
|
||||
opt["f0"] = if_f0
|
||||
opt["version"] = version
|
||||
@ -55,7 +56,7 @@ def save_small_model(ckpt, sr, if_f0, name, epoch, version, hps):
|
||||
return traceback.format_exc()
|
||||
|
||||
|
||||
def extract_small_model(path, name, sr, if_f0, info, version):
|
||||
def extract_small_model(path, name, author, sr, if_f0, info, version):
|
||||
try:
|
||||
ckpt = torch.load(path, map_location="cpu")
|
||||
if "model" in ckpt:
|
||||
@ -178,6 +179,7 @@ def extract_small_model(path, name, sr, if_f0, info, version):
|
||||
opt["info"] = info
|
||||
opt["name"] = name
|
||||
opt["timestamp"] = int(time())
|
||||
if author: opt["author"] = author
|
||||
opt["version"] = version
|
||||
opt["sr"] = sr
|
||||
opt["f0"] = int(if_f0)
|
||||
@ -214,6 +216,13 @@ def merge(path1, path2, alpha1, sr, f0, info, name, version):
|
||||
continue
|
||||
opt["weight"][key] = a[key]
|
||||
return opt
|
||||
|
||||
def authors(c1, c2):
|
||||
a1, a2 = c1.get("author", ""), c2.get("author", "")
|
||||
if a1 == a2: return a1
|
||||
if not a1: a1 = "Unknown"
|
||||
if not a2: a2 = "Unknown"
|
||||
return f"{a1} & {a2}"
|
||||
|
||||
ckpt1 = torch.load(path1, map_location="cpu")
|
||||
ckpt2 = torch.load(path2, map_location="cpu")
|
||||
@ -242,8 +251,7 @@ def merge(path1, path2, alpha1, sr, f0, info, name, version):
|
||||
opt["weight"][key] = (
|
||||
alpha1 * (ckpt1[key].float()) + (1 - alpha1) * (ckpt2[key].float())
|
||||
).half()
|
||||
# except:
|
||||
# pdb.set_trace()
|
||||
author = authors(ckpt1, ckpt2)
|
||||
opt["config"] = cfg
|
||||
"""
|
||||
if(sr=="40k"):opt["config"] = [1025, 32, 192, 192, 768, 2, 6, 3, 0, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10, 10, 2, 2], 512, [16, 16, 4, 4,4], 109, 256, 40000]
|
||||
@ -252,6 +260,7 @@ def merge(path1, path2, alpha1, sr, f0, info, name, version):
|
||||
"""
|
||||
opt["name"] = name
|
||||
opt["timestamp"] = int(time())
|
||||
if author: opt["author"] = author
|
||||
opt["sr"] = sr
|
||||
opt["f0"] = 1 if f0 == i18n("是") else 0
|
||||
opt["version"] = version
|
||||
|
||||
@ -358,6 +358,9 @@ def get_hparams(init=True):
|
||||
required=True,
|
||||
help="if caching the dataset in GPU memory, 1 or 0",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-a", "--author", type=str, default="", help="Model author"
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
name = args.experiment_dir
|
||||
@ -383,9 +386,10 @@ def get_hparams(init=True):
|
||||
hparams.save_every_weights = args.save_every_weights
|
||||
hparams.if_cache_data_in_gpu = args.if_cache_data_in_gpu
|
||||
hparams.data.training_files = "%s/filelist.txt" % experiment_dir
|
||||
hparams.author = args.author
|
||||
return hparams
|
||||
|
||||
|
||||
"""
|
||||
def get_hparams_from_dir(model_dir):
|
||||
config_save_path = os.path.join(model_dir, "config.json")
|
||||
with open(config_save_path, "r") as f:
|
||||
@ -429,7 +433,7 @@ def check_git_hash(model_dir):
|
||||
)
|
||||
else:
|
||||
open(path, "w").write(cur_hash)
|
||||
|
||||
"""
|
||||
|
||||
def get_logger(model_dir, filename="train.log"):
|
||||
global logger
|
||||
|
||||
@ -38,18 +38,20 @@ def show_model_info(cpt, show_long_id=False):
|
||||
)
|
||||
txt = f"""{i18n("模型名")}: %s
|
||||
{i18n("封装时间")}: %s
|
||||
{i18n("模型作者")}: %s
|
||||
{i18n("信息")}: %s
|
||||
{i18n("采样率")}: %s
|
||||
{i18n("音高引导(f0)")}: %s
|
||||
{i18n("版本")}: %s
|
||||
{i18n("ID(短)")}: %s
|
||||
{i18n("ID(长)")}: %s""" % (
|
||||
cpt.get("name", "None"),
|
||||
cpt.get("name", i18n("Unknown")),
|
||||
datetime.fromtimestamp(float(cpt.get("timestamp", 0))),
|
||||
cpt.get("info", "None"),
|
||||
cpt.get("sr", "None"),
|
||||
cpt.get("author", i18n("Unknown")),
|
||||
cpt.get("info", i18n("None")),
|
||||
cpt.get("sr", i18n("Unknown")),
|
||||
i18n("有") if cpt.get("f0", 0) == 1 else i18n("无"),
|
||||
cpt.get("version", "None"),
|
||||
cpt.get("version", i18n("None")),
|
||||
id,
|
||||
h,
|
||||
)
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user