Spaces:
Running
Running
TheStinger
commited on
Commit
•
2387ecd
1
Parent(s):
c922820
Update app.py
Browse files
app.py
CHANGED
@@ -1872,244 +1872,12 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
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files_in_folder = os.listdir(pretrained_folder)
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num_files = len(files_in_folder)
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return num_files >= 2
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exp_dir1 = gr.Textbox(label="Voice Name:", value="My-Voice")
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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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value="40k",
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interactive=True,
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visible=False
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)
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if_f0_3 = gr.Radio(
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label=i18n("模型是否带音高指导(唱歌一定要, 语音可以不要)"),
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choices=[True, False],
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value=True,
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interactive=True,
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visible=False
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)
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version19 = gr.Radio(
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label="RVC version",
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choices=["v1", "v2"],
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value="v2",
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interactive=True,
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visible=False,
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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="# of CPUs for data processing (Leave as it is)",
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value=config.n_cpu,
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interactive=True,
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visible=True
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)
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trainset_dir4 = gr.Textbox(label="Path to your dataset (audios, not zip):", value="./dataset")
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easy_uploader = gr.Files(label='OR Drop your audios here. They will be uploaded in your dataset path above.',file_types=['audio'])
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but1 = gr.Button("1. Process The Dataset", variant="primary")
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info1 = gr.Textbox(label="Status (wait until it says 'end preprocess'):", value="")
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easy_uploader.upload(fn=upload_to_dataset, inputs=[easy_uploader, trainset_dir4], outputs=[info1])
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but1.click(
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preprocess_dataset, [trainset_dir4, exp_dir1, sr2, np7], [info1]
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)
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with gr.Column():
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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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visible=False
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)
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with gr.Accordion('GPU Settings', open=False, visible=False):
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gpus6 = gr.Textbox(
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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"),
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value=gpus,
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interactive=True,
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visible=False
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)
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gpu_info9 = gr.Textbox(label=i18n("显卡信息"), value=gpu_info)
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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"
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),
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choices=["harvest","crepe", "mangio-crepe", "rmvpe"], # Fork feature: Crepe on f0 extraction for training.
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value="rmvpe",
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interactive=True,
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)
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extraction_crepe_hop_length = gr.Slider(
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minimum=1,
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maximum=512,
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step=1,
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label=i18n("crepe_hop_length"),
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value=128,
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interactive=True,
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visible=False,
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)
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f0method8.change(fn=whethercrepeornah, inputs=[f0method8], outputs=[extraction_crepe_hop_length])
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but2 = gr.Button("2. Pitch Extraction", variant="primary")
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info2 = gr.Textbox(label="Status(Check the Colab Notebook's cell output):", value="", max_lines=8)
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but2.click(
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extract_f0_feature,
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[gpus6, np7, f0method8, if_f0_3, exp_dir1, version19, extraction_crepe_hop_length],
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[info2],
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)
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with gr.Row():
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with gr.Column():
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total_epoch11 = gr.Slider(
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minimum=1,
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maximum=5000,
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step=10,
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label="Total # of training epochs (IF you choose a value too high, your model will sound horribly overtrained.):",
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value=250,
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interactive=True,
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)
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butstop = gr.Button(
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"Stop Training",
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variant='primary',
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visible=False,
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)
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but3 = gr.Button("3. Train Model", variant="primary", visible=True)
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but3.click(fn=stoptraining, inputs=[gr.Number(value=0, visible=False)], outputs=[but3, butstop])
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butstop.click(fn=stoptraining, inputs=[gr.Number(value=1, visible=False)], outputs=[butstop, but3])
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-
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but4 = gr.Button("4.Train Index", variant="primary")
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info3 = gr.Textbox(label="Status(Check the Colab Notebook's cell output):", value="", max_lines=10)
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with gr.Accordion("Training Preferences (You can leave these as they are)", open=False):
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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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with gr.Column():
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save_epoch10 = gr.Slider(
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minimum=1,
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maximum=200,
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step=1,
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label="Backup every X amount of epochs:",
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value=10,
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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="Batch Size (LEAVE IT unless you know what you're doing!):",
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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.Checkbox(
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label="Save only the latest '.ckpt' file to save disk space.",
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value=True,
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interactive=True,
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)
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if_cache_gpu17 = gr.Checkbox(
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label="Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training, but caching large datasets will consume a lot of GPU memory and may not provide much speed improvement.",
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value=False,
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interactive=True,
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)
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if_save_every_weights18 = gr.Checkbox(
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label="Save a small final model to the 'weights' folder at each save point.",
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value=True,
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interactive=True,
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)
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zip_model = gr.Button('5. Download Model')
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zipped_model = gr.Files(label='Your Model and Index file can be downloaded here:')
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zip_model.click(fn=zip_downloader, inputs=[exp_dir1], outputs=[zipped_model, info3])
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with gr.Group():
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with gr.Accordion("Base Model Locations:", open=False, visible=False):
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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="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="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("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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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, version19],
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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],
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)
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if_f0_3.change(
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change_f0,
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[if_f0_3, sr2, version19],
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[f0method8, pretrained_G14, pretrained_D15],
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)
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but5 = gr.Button(i18n("一键训练"), variant="primary", visible=False)
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but3.click(
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click_train,
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[
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exp_dir1,
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sr2,
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if_f0_3,
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spk_id5,
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save_epoch10,
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total_epoch11,
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batch_size12,
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if_save_latest13,
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pretrained_G14,
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pretrained_D15,
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gpus16,
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if_cache_gpu17,
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if_save_every_weights18,
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version19,
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],
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[
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info3,
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butstop,
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but3,
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],
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)
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but4.click(train_index, [exp_dir1, version19], info3)
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but5.click(
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train1key,
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[
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exp_dir1,
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sr2,
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if_f0_3,
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trainset_dir4,
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spk_id5,
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np7,
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f0method8,
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save_epoch10,
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total_epoch11,
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batch_size12,
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if_save_latest13,
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pretrained_G14,
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pretrained_D15,
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gpus16,
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if_cache_gpu17,
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if_save_every_weights18,
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version19,
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extraction_crepe_hop_length
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],
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info3,
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)
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else:
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print(
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"Pretrained weights not downloaded. Disabling training tab.\n"
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"Wondering how to train a voice? Join AI HUB Discord Server! https://discord.gg/aihub\n"
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"-------------------------------\n"
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)
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app.launch(share=False, quiet=False, max_threads=1022)
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#endpain
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files_in_folder = os.listdir(pretrained_folder)
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num_files = len(files_in_folder)
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return num_files >= 2
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print(
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"=" * 50,
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"Disabling Training, as ZeroGPU only supports a running time of 120 seconds.",
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"Please use a local machine, or colab for training.",
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"=" * 50,
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)
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app.launch(share=False, quiet=False, max_threads=1022)
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#endpain
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