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from original import * |
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import shutil, glob |
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from easyfuncs import download_from_url, CachedModels |
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os.makedirs("dataset",exist_ok=True) |
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model_library = CachedModels() |
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from typing import Iterable |
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import gradio as gr |
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os.system("python tools/download_models.py") |
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from gradio.themes.base import Base |
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from gradio.themes.utils import colors, fonts, sizes |
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import time |
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class Applio(Base): |
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def __init__( |
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self, |
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*, |
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primary_hue: colors.Color | str = colors.neutral, |
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secondary_hue: colors.Color | str = colors.neutral, |
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neutral_hue: colors.Color | str = colors.neutral, |
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spacing_size: sizes.Size | str = sizes.spacing_md, |
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radius_size: sizes.Size | str = sizes.radius_md, |
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text_size: sizes.Size | str = sizes.text_lg, |
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font: fonts.Font | str | Iterable[fonts.Font | str] = ( |
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"Syne V", |
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fonts.GoogleFont("Syne"), |
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"ui-sans-serif", |
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"system-ui", |
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), |
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font_mono: fonts.Font | str | Iterable[fonts.Font | str] = ( |
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"ui-monospace", |
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fonts.GoogleFont("Nunito Sans"), |
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), |
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): |
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super().__init__( |
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primary_hue=primary_hue, |
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secondary_hue=secondary_hue, |
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neutral_hue=neutral_hue, |
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spacing_size=spacing_size, |
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radius_size=radius_size, |
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text_size=text_size, |
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font=font, |
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font_mono=font_mono, |
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) |
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self.name = ("Applio",) |
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self.secondary_100 = ("#dbeafe",) |
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self.secondary_200 = ("#bfdbfe",) |
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self.secondary_300 = ("#93c5fd",) |
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self.secondary_400 = ("#60a5fa",) |
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self.secondary_50 = ("#eff6ff",) |
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self.secondary_500 = ("#3b82f6",) |
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self.secondary_600 = ("#2563eb",) |
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self.secondary_700 = ("#1d4ed8",) |
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self.secondary_800 = ("#1e40af",) |
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self.secondary_900 = ("#1e3a8a",) |
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self.secondary_950 = ("#1d3660",) |
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super().set( |
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background_fill_primary="#110F0F", |
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background_fill_primary_dark="#110F0F", |
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background_fill_secondary="#110F0F", |
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background_fill_secondary_dark="#110F0F", |
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block_background_fill="*neutral_800", |
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block_background_fill_dark="*neutral_800", |
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block_border_color="*border_color_primary", |
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block_border_color_dark="*border_color_primary", |
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block_border_width="1px", |
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block_border_width_dark="1px", |
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block_info_text_color="*body_text_color_subdued", |
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block_info_text_color_dark="*body_text_color_subdued", |
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block_info_text_size="*text_sm", |
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block_info_text_weight="400", |
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block_label_background_fill="*background_fill_primary", |
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block_label_background_fill_dark="*background_fill_secondary", |
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block_label_border_color="*border_color_primary", |
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block_label_border_color_dark="*border_color_primary", |
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block_label_border_width="1px", |
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block_label_border_width_dark="1px", |
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block_label_margin="0", |
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block_label_padding="*spacing_sm *spacing_lg", |
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block_label_radius="calc(*radius_lg - 1px) 0 calc(*radius_lg - 1px) 0", |
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block_label_right_radius="0 calc(*radius_lg - 1px) 0 calc(*radius_lg - 1px)", |
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block_label_shadow="*block_shadow", |
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block_label_text_color="*#110F0F", |
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block_label_text_color_dark="*#110F0F", |
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block_label_text_weight="400", |
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block_padding="*spacing_xl", |
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block_radius="*radius_md", |
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block_shadow="none", |
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block_shadow_dark="none", |
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block_title_background_fill="rgb(255,255,255)", |
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block_title_background_fill_dark="rgb(255,255,255)", |
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block_title_border_color="none", |
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block_title_border_color_dark="none", |
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block_title_border_width="0px", |
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block_title_padding="*block_label_padding", |
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block_title_radius="*block_label_radius", |
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block_title_text_color="#110F0F", |
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block_title_text_color_dark="#110F0F", |
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block_title_text_size="*text_md", |
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block_title_text_weight="600", |
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body_background_fill="#110F0F", |
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body_background_fill_dark="#110F0F", |
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body_text_color="white", |
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body_text_color_dark="white", |
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body_text_color_subdued="*neutral_400", |
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body_text_color_subdued_dark="*neutral_400", |
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body_text_size="*text_md", |
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body_text_weight="400", |
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border_color_accent="*neutral_600", |
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border_color_accent_dark="*neutral_600", |
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border_color_primary="*neutral_800", |
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border_color_primary_dark="*neutral_800", |
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button_border_width="*input_border_width", |
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button_border_width_dark="*input_border_width", |
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button_cancel_background_fill="*button_secondary_background_fill", |
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button_cancel_background_fill_dark="*button_secondary_background_fill", |
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button_cancel_background_fill_hover="*button_cancel_background_fill", |
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button_cancel_background_fill_hover_dark="*button_cancel_background_fill", |
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button_cancel_border_color="*button_secondary_border_color", |
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button_cancel_border_color_dark="*button_secondary_border_color", |
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button_cancel_border_color_hover="*button_cancel_border_color", |
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button_cancel_border_color_hover_dark="*button_cancel_border_color", |
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button_cancel_text_color="#110F0F", |
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button_cancel_text_color_dark="#110F0F", |
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button_cancel_text_color_hover="#110F0F", |
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button_cancel_text_color_hover_dark="#110F0F", |
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button_large_padding="*spacing_lg calc(2 * *spacing_lg)", |
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button_large_radius="*radius_lg", |
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button_large_text_size="*text_lg", |
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button_large_text_weight="600", |
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button_primary_background_fill="*primary_600", |
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button_primary_background_fill_dark="*primary_600", |
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button_primary_background_fill_hover="*primary_500", |
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button_primary_background_fill_hover_dark="*primary_500", |
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button_primary_border_color="*primary_500", |
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button_primary_border_color_dark="*primary_500", |
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button_primary_border_color_hover="*primary_400", |
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button_primary_border_color_hover_dark="*primary_400", |
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button_primary_text_color="white", |
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button_primary_text_color_dark="white", |
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button_primary_text_color_hover="#110F0F", |
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button_primary_text_color_hover_dark="#110F0F", |
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button_secondary_background_fill="transparent", |
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button_secondary_background_fill_dark="transparent", |
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button_secondary_background_fill_hover="*neutral_800", |
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button_secondary_background_fill_hover_dark="*neutral_800", |
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button_secondary_border_color="*neutral_700", |
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button_secondary_border_color_dark="*neutral_700", |
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button_secondary_border_color_hover="*neutral_600", |
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button_secondary_border_color_hover_dark="*neutral_600", |
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button_secondary_text_color="white", |
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button_secondary_text_color_dark="white", |
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button_secondary_text_color_hover="*button_secondary_text_color", |
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button_secondary_text_color_hover_dark="*button_secondary_text_color", |
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button_shadow="none", |
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button_shadow_active="*shadow_inset", |
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button_shadow_hover="none", |
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button_small_padding="*spacing_sm calc(2 * *spacing_sm)", |
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button_small_radius="*radius_lg", |
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button_small_text_size="*text_md", |
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button_small_text_weight="400", |
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button_transition="0.3s ease all", |
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checkbox_background_color="*neutral_700", |
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checkbox_background_color_dark="*neutral_700", |
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checkbox_background_color_focus="*checkbox_background_color", |
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checkbox_background_color_focus_dark="*checkbox_background_color", |
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checkbox_background_color_hover="*checkbox_background_color", |
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checkbox_background_color_hover_dark="*checkbox_background_color", |
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checkbox_background_color_selected="*secondary_600", |
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checkbox_background_color_selected_dark="*secondary_600", |
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checkbox_border_color="*neutral_700", |
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checkbox_border_color_dark="*neutral_700", |
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checkbox_border_color_focus="*secondary_500", |
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checkbox_border_color_focus_dark="*secondary_500", |
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checkbox_border_color_hover="*neutral_600", |
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checkbox_border_color_hover_dark="*neutral_600", |
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checkbox_border_color_selected="*secondary_600", |
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checkbox_border_color_selected_dark="*secondary_600", |
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checkbox_border_radius="*radius_sm", |
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checkbox_border_width="*input_border_width", |
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checkbox_border_width_dark="*input_border_width", |
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checkbox_check="url(\"data:image/svg+xml,%3csvg viewBox='0 0 16 16' fill='white' xmlns='http://www.w3.org/2000/svg'%3e%3cpath d='M12.207 4.793a1 1 0 010 1.414l-5 5a1 1 0 01-1.414 0l-2-2a1 1 0 011.414-1.414L6.5 9.086l4.293-4.293a1 1 0 011.414 0z'/%3e%3c/svg%3e\")", |
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checkbox_label_background_fill="transparent", |
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checkbox_label_background_fill_dark="transparent", |
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checkbox_label_background_fill_hover="transparent", |
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checkbox_label_background_fill_hover_dark="transparent", |
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checkbox_label_background_fill_selected="transparent", |
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checkbox_label_background_fill_selected_dark="transparent", |
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checkbox_label_border_color="transparent", |
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checkbox_label_border_color_dark="transparent", |
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checkbox_label_border_color_hover="transparent", |
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checkbox_label_border_color_hover_dark="transparent", |
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checkbox_label_border_width="transparent", |
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checkbox_label_border_width_dark="transparent", |
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checkbox_label_gap="*spacing_lg", |
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checkbox_label_padding="*spacing_md calc(2 * *spacing_md)", |
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checkbox_label_shadow="none", |
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checkbox_label_text_color="*body_text_color", |
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checkbox_label_text_color_dark="*body_text_color", |
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checkbox_label_text_color_selected="*checkbox_label_text_color", |
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checkbox_label_text_color_selected_dark="*checkbox_label_text_color", |
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checkbox_label_text_size="*text_md", |
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checkbox_label_text_weight="400", |
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checkbox_shadow="*input_shadow", |
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color_accent="*primary_500", |
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color_accent_soft="*primary_50", |
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color_accent_soft_dark="*neutral_700", |
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container_radius="*radius_xl", |
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embed_radius="*radius_lg", |
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error_background_fill="*background_fill_primary", |
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error_background_fill_dark="*background_fill_primary", |
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error_border_color="*border_color_primary", |
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error_border_color_dark="*border_color_primary", |
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error_border_width="1px", |
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error_border_width_dark="1px", |
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error_text_color="#ef4444", |
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error_text_color_dark="#ef4444", |
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form_gap_width="0px", |
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input_background_fill="*neutral_900", |
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input_background_fill_dark="*neutral_900", |
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input_background_fill_focus="*secondary_600", |
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input_background_fill_focus_dark="*secondary_600", |
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input_background_fill_hover="*input_background_fill", |
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input_background_fill_hover_dark="*input_background_fill", |
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input_border_color="*neutral_700", |
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input_border_color_dark="*neutral_700", |
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input_border_color_focus="*secondary_600", |
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input_border_color_focus_dark="*primary_600", |
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input_border_color_hover="*input_border_color", |
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input_border_color_hover_dark="*input_border_color", |
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input_border_width="1px", |
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input_border_width_dark="1px", |
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input_padding="*spacing_xl", |
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input_placeholder_color="*neutral_500", |
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input_placeholder_color_dark="*neutral_500", |
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input_radius="*radius_lg", |
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input_shadow="none", |
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input_shadow_dark="none", |
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input_shadow_focus="*input_shadow", |
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input_shadow_focus_dark="*input_shadow", |
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input_text_size="*text_md", |
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input_text_weight="400", |
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layout_gap="*spacing_xxl", |
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link_text_color="*secondary_500", |
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link_text_color_active="*secondary_500", |
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link_text_color_active_dark="*secondary_500", |
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link_text_color_dark="*secondary_500", |
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link_text_color_hover="*secondary_400", |
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link_text_color_hover_dark="*secondary_400", |
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link_text_color_visited="*secondary_600", |
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link_text_color_visited_dark="*secondary_600", |
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loader_color="*color_accent", |
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loader_color_dark="*color_accent", |
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panel_background_fill="*background_fill_secondary", |
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panel_background_fill_dark="*background_fill_secondary", |
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panel_border_color="*border_color_primary", |
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panel_border_color_dark="*border_color_primary", |
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panel_border_width="1px", |
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panel_border_width_dark="1px", |
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prose_header_text_weight="600", |
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prose_text_size="*text_md", |
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prose_text_weight="400", |
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radio_circle="url(\"data:image/svg+xml,%3csvg viewBox='0 0 16 16' fill='white' xmlns='http://www.w3.org/2000/svg'%3e%3ccircle cx='8' cy='8' r='3'/%3e%3c/svg%3e\")", |
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section_header_text_size="*text_md", |
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section_header_text_weight="400", |
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shadow_drop="rgba(0,0,0,0.05) 0px 1px 2px 0px", |
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shadow_drop_lg="0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1)", |
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shadow_inset="rgba(0,0,0,0.05) 0px 2px 4px 0px inset", |
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shadow_spread="3px", |
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shadow_spread_dark="1px", |
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slider_color="#9E9E9E", |
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slider_color_dark="#9E9E9E", |
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stat_background_fill="*primary_500", |
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stat_background_fill_dark="*primary_500", |
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table_border_color="*neutral_700", |
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table_border_color_dark="*neutral_700", |
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table_even_background_fill="*neutral_950", |
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table_even_background_fill_dark="*neutral_950", |
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table_odd_background_fill="*neutral_900", |
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table_odd_background_fill_dark="*neutral_900", |
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table_radius="*radius_lg", |
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table_row_focus="*color_accent_soft", |
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table_row_focus_dark="*color_accent_soft", |
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) |
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theme = Applio() |
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with gr.Blocks(title="RVC V2",theme=theme) as app: |
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with gr.Row(): |
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gr.HTML("<img src='https://huggingface.co/spaces/Blane187/RVC_HF_V2/resolve/main/a.png' alt='image'>") |
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with gr.Tabs(): |
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with gr.TabItem("Inference"): |
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with gr.Row(): |
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voice_model = gr.Dropdown(label="Model Voice", choices=sorted(names), value=lambda:sorted(names)[0] if len(sorted(names)) > 0 else '', interactive=True) |
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refresh_button = gr.Button("Refresh", variant="primary") |
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spk_item = gr.Slider( |
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minimum=0, |
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maximum=2333, |
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step=1, |
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label="Speaker ID", |
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value=0, |
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visible=False, |
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interactive=True, |
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) |
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vc_transform0 = gr.Number(label="Pitch",value=0) |
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but0 = gr.Button(value="Convert", variant="primary") |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Row(): |
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dropbox = gr.Audio(label="your audio here.") |
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with gr.Column(): |
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with gr.Accordion("Change Index", open=False): |
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file_index2 = gr.Dropdown( |
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label="Change Index", |
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choices=sorted(index_paths), |
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interactive=True, |
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value=sorted(index_paths)[0] if len(sorted(index_paths)) > 0 else '' |
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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="Index Strength", |
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value=0.5, |
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interactive=True, |
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) |
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vc_output2 = gr.Audio(label="Output") |
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with gr.Accordion("General Settings", open=False): |
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f0method0 = gr.Radio( |
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label="Method", |
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choices=["pm", "harvest", "crepe", "rmvpe", "torchfcpe"] |
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if config.dml == False |
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else ["pm", "harvest", "rmvpe"], |
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value="rmvpe", |
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interactive=True, |
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) |
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filter_radius0 = gr.Slider( |
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minimum=0, |
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maximum=7, |
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label="Breathiness Reduction (Harvest only)", |
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value=3, |
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step=1, |
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interactive=True, |
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) |
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resample_sr0 = gr.Slider( |
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minimum=0, |
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maximum=48000, |
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label="Resample", |
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value=0, |
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step=1, |
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interactive=True, |
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visible=False |
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) |
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rms_mix_rate0 = gr.Slider( |
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minimum=0, |
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maximum=1, |
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label="Volume Normalization", |
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value=0, |
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interactive=True, |
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) |
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protect0 = gr.Slider( |
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minimum=0, |
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maximum=0.5, |
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label="Breathiness Protection (0 is enabled, 0.5 is disabled)", |
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value=0.33, |
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step=0.01, |
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interactive=True, |
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) |
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if voice_model != None: vc.get_vc(voice_model.value,protect0,protect0) |
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file_index1 = gr.Textbox( |
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label="Index Path", |
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interactive=True, |
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visible=False |
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) |
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refresh_button.click( |
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fn=change_choices, |
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inputs=[], |
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outputs=[voice_model, file_index2], |
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api_name="infer_refresh", |
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) |
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with gr.Row(): |
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f0_file = gr.File(label="F0 Path", visible=False) |
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with gr.Row(): |
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vc_output1 = gr.Textbox(label="Information", placeholder="Welcome!",visible=False) |
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but0.click( |
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vc.vc_single, |
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[ |
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spk_item, |
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dropbox, |
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vc_transform0, |
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f0_file, |
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f0method0, |
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file_index1, |
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file_index2, |
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index_rate1, |
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filter_radius0, |
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resample_sr0, |
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rms_mix_rate0, |
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protect0, |
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], |
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[vc_output1, vc_output2], |
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api_name="infer_convert", |
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) |
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voice_model.change( |
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fn=vc.get_vc, |
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inputs=[voice_model, protect0, protect0], |
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outputs=[spk_item, protect0, protect0, file_index2, file_index2], |
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api_name="infer_change_voice", |
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) |
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with gr.TabItem("Download Models"): |
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with gr.Row(): |
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url_input = gr.Textbox(label="URL to model", value="",placeholder="https://...", scale=6) |
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name_output = gr.Textbox(label="Save as", value="",placeholder="MyModel",scale=2) |
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url_download = gr.Button(value="Download Model",scale=2) |
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url_download.click( |
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inputs=[url_input,name_output], |
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outputs=[url_input], |
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fn=download_from_url, |
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) |
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with gr.Row(): |
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model_browser = gr.Dropdown(choices=list(model_library.models.keys()),label="OR Search Models (Quality UNKNOWN)",scale=5) |
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download_from_browser = gr.Button(value="Get",scale=2) |
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download_from_browser.click( |
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inputs=[model_browser], |
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outputs=[model_browser], |
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fn=lambda model: download_from_url(model_library.models[model],model), |
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) |
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|
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with gr.TabItem("read this"): |
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gr.Markdown(f"This Spaces Using CPU dude\n may inference take long time\n and Train tab is disable :)") |
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|
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with gr.TabItem("Train", visible=False): |
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with gr.Row(): |
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with gr.Column(): |
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training_name = gr.Textbox(label="Name your model", value="My-Voice",placeholder="My-Voice") |
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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="Number of CPU processes used to extract pitch features", |
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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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sr2 = gr.Radio( |
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label="Sampling Rate", |
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choices=["40k", "32k"], |
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value="32k", |
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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="Will your model be used for singing? If not, you can ignore this.", |
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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="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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dataset_folder = gr.Textbox( |
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label="dataset folder", value='dataset' |
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) |
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easy_uploader = gr.Files(label="Drop your audio files here",file_types=['audio']) |
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but1 = gr.Button("1. Process", variant="primary") |
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info1 = gr.Textbox(label="Information", value="",visible=True) |
|
easy_uploader.upload(inputs=[dataset_folder],outputs=[],fn=lambda folder:os.makedirs(folder,exist_ok=True)) |
|
easy_uploader.upload( |
|
fn=lambda files,folder: [shutil.copy2(f.name,os.path.join(folder,os.path.split(f.name)[1])) for f in files] if folder != "" else gr.Warning('Please enter a folder name for your dataset'), |
|
inputs=[easy_uploader, dataset_folder], |
|
outputs=[]) |
|
gpus6 = gr.Textbox( |
|
label="Enter the GPU numbers to use separated by -, (e.g. 0-1-2)", |
|
value=gpus, |
|
interactive=True, |
|
visible=F0GPUVisible, |
|
) |
|
gpu_info9 = gr.Textbox( |
|
label="GPU Info", value=gpu_info, visible=F0GPUVisible |
|
) |
|
spk_id5 = gr.Slider( |
|
minimum=0, |
|
maximum=4, |
|
step=1, |
|
label="Speaker ID", |
|
value=0, |
|
interactive=True, |
|
visible=False |
|
) |
|
but1.click( |
|
preprocess_dataset, |
|
[dataset_folder, training_name, sr2, np7], |
|
[info1], |
|
api_name="train_preprocess", |
|
) |
|
with gr.Column(): |
|
f0method8 = gr.Radio( |
|
label="F0 extraction method", |
|
choices=["pm", "harvest", "dio", "rmvpe", "rmvpe_gpu"], |
|
value="rmvpe_gpu", |
|
interactive=True, |
|
) |
|
gpus_rmvpe = gr.Textbox( |
|
label="GPU numbers to use separated by -, (e.g. 0-1-2)", |
|
value="%s-%s" % (gpus, gpus), |
|
interactive=True, |
|
visible=F0GPUVisible, |
|
) |
|
but2 = gr.Button("2. Extract Features", variant="primary") |
|
info2 = gr.Textbox(label="Information", value="", max_lines=8) |
|
f0method8.change( |
|
fn=change_f0_method, |
|
inputs=[f0method8], |
|
outputs=[gpus_rmvpe], |
|
) |
|
but2.click( |
|
extract_f0_feature, |
|
[ |
|
gpus6, |
|
np7, |
|
f0method8, |
|
if_f0_3, |
|
training_name, |
|
version19, |
|
gpus_rmvpe, |
|
], |
|
[info2], |
|
api_name="train_extract_f0_feature", |
|
) |
|
with gr.Column(): |
|
total_epoch11 = gr.Slider( |
|
minimum=2, |
|
maximum=1000, |
|
step=1, |
|
label="Epochs (more epochs may improve quality but takes longer)", |
|
value=150, |
|
interactive=True, |
|
) |
|
but4 = gr.Button("3. Train Index", variant="primary") |
|
but3 = gr.Button("4. Train Model", variant="primary") |
|
info3 = gr.Textbox(label="Information", value="", max_lines=10) |
|
with gr.Accordion(label="General Settings", open=False): |
|
gpus16 = gr.Textbox( |
|
label="GPUs separated by -, (e.g. 0-1-2)", |
|
value="0", |
|
interactive=True, |
|
visible=True |
|
) |
|
save_epoch10 = gr.Slider( |
|
minimum=1, |
|
maximum=50, |
|
step=1, |
|
label="Weight Saving Frequency", |
|
value=25, |
|
interactive=True, |
|
) |
|
batch_size12 = gr.Slider( |
|
minimum=1, |
|
maximum=40, |
|
step=1, |
|
label="Batch Size", |
|
value=default_batch_size, |
|
interactive=True, |
|
) |
|
if_save_latest13 = gr.Radio( |
|
label="Only save the latest model", |
|
choices=["yes", "no"], |
|
value="yes", |
|
interactive=True, |
|
visible=False |
|
) |
|
if_cache_gpu17 = gr.Radio( |
|
label="If your dataset is UNDER 10 minutes, cache it to train faster", |
|
choices=["yes", "no"], |
|
value="no", |
|
interactive=True, |
|
) |
|
if_save_every_weights18 = gr.Radio( |
|
label="Save small model at every save point", |
|
choices=["yes", "no"], |
|
value="yes", |
|
interactive=True, |
|
) |
|
with gr.Accordion(label="Change pretrains", open=False): |
|
pretrained = lambda sr, letter: [os.path.abspath(os.path.join('assets/pretrained_v2', file)) for file in os.listdir('assets/pretrained_v2') if file.endswith('.pth') and sr in file and letter in file] |
|
pretrained_G14 = gr.Dropdown( |
|
label="pretrained G", |
|
|
|
choices = pretrained(sr2.value, 'G'), |
|
value=pretrained(sr2.value, 'G')[0] if len(pretrained(sr2.value, 'G')) > 0 else '', |
|
interactive=True, |
|
visible=True |
|
) |
|
pretrained_D15 = gr.Dropdown( |
|
label="pretrained D", |
|
choices = pretrained(sr2.value, 'D'), |
|
value= pretrained(sr2.value, 'D')[0] if len(pretrained(sr2.value, 'G')) > 0 else '', |
|
visible=True, |
|
interactive=True |
|
) |
|
with gr.Row(): |
|
download_model = gr.Button('5.Download Model') |
|
with gr.Row(): |
|
model_files = gr.Files(label='Your Model and Index file can be downloaded here:') |
|
download_model.click( |
|
fn=lambda name: os.listdir(f'assets/weights/{name}') + glob.glob(f'logs/{name.split(".")[0]}/added_*.index'), |
|
inputs=[training_name], |
|
outputs=[model_files, info3]) |
|
with gr.Row(): |
|
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, pretrained_G14, pretrained_D15], |
|
) |
|
with gr.Row(): |
|
but5 = gr.Button("1 Click Training", variant="primary", visible=False) |
|
but3.click( |
|
click_train, |
|
[ |
|
training_name, |
|
sr2, |
|
if_f0_3, |
|
spk_id5, |
|
save_epoch10, |
|
total_epoch11, |
|
batch_size12, |
|
if_save_latest13, |
|
pretrained_G14, |
|
pretrained_D15, |
|
gpus16, |
|
if_cache_gpu17, |
|
if_save_every_weights18, |
|
version19, |
|
], |
|
info3, |
|
api_name="train_start", |
|
) |
|
but4.click(train_index, [training_name, version19], info3) |
|
but5.click( |
|
train1key, |
|
[ |
|
training_name, |
|
sr2, |
|
if_f0_3, |
|
dataset_folder, |
|
spk_id5, |
|
np7, |
|
f0method8, |
|
save_epoch10, |
|
total_epoch11, |
|
batch_size12, |
|
if_save_latest13, |
|
pretrained_G14, |
|
pretrained_D15, |
|
gpus16, |
|
if_cache_gpu17, |
|
if_save_every_weights18, |
|
version19, |
|
gpus_rmvpe, |
|
], |
|
info3, |
|
api_name="train_start_all", |
|
) |
|
|
|
app.launch(share=True) |
|
|
