Spaces:
Running
on
Zero
Running
on
Zero
Upload app.py
Browse files
app.py
CHANGED
@@ -197,9 +197,12 @@ def forward(tokens, voice, speed, device='cpu'):
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def forward_gpu(tokens, voice, speed):
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return forward(tokens, voice, speed, device='cuda')
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def generate(text, voice, ps=None, speed=1, reduce_noise=0.5, opening_cut=4000, closing_cut=2000, ease_in=3000, ease_out=1000, pad_before=5000, pad_after=5000, use_gpu=None):
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if voice not in VOICES:
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-
# Ensure stability for https://huggingface.co/spaces/Pendrokar/TTS-Spaces-Arena
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voice = 'af'
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ps = ps or phonemize(text, voice)
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tokens = tokenize(ps)
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@@ -274,8 +277,8 @@ with gr.Blocks() as basic_tts:
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ease_in = gr.Slider(minimum=0, maximum=24000, value=3000, step=1000, label='🎢 Ease In', info='Ease in samples, after opening cut')
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with gr.Column():
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ease_out = gr.Slider(minimum=0, maximum=24000, value=1000, step=1000, label='🛝 Ease Out', info='Ease out samples, before closing cut')
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text.submit(
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generate_btn.click(
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@torch.no_grad()
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def lf_forward(token_lists, voice, speed, device='cpu'):
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def forward_gpu(tokens, voice, speed):
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return forward(tokens, voice, speed, device='cuda')
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# Must be backwards compatible with https://huggingface.co/spaces/Pendrokar/TTS-Spaces-Arena
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def generate(text, voice, ps=None, speed=1, reduce_noise=0.5, opening_cut=4000, closing_cut=2000, ease_in=3000, ease_out=1000, pad_before=5000, pad_after=5000, use_gpu=None):
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return _generate(text, voice, ps, speed, opening_cut, closing_cut, ease_in, ease_out, use_gpu)
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def _generate(text, voice, ps, speed, opening_cut, closing_cut, ease_in, ease_out, use_gpu):
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if voice not in VOICES:
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voice = 'af'
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ps = ps or phonemize(text, voice)
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tokens = tokenize(ps)
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ease_in = gr.Slider(minimum=0, maximum=24000, value=3000, step=1000, label='🎢 Ease In', info='Ease in samples, after opening cut')
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with gr.Column():
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ease_out = gr.Slider(minimum=0, maximum=24000, value=1000, step=1000, label='🛝 Ease Out', info='Ease out samples, before closing cut')
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text.submit(_generate, inputs=[text, voice, in_ps, speed, opening_cut, closing_cut, ease_in, ease_out, use_gpu], outputs=[audio, out_ps])
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generate_btn.click(_generate, inputs=[text, voice, in_ps, speed, opening_cut, closing_cut, ease_in, ease_out, use_gpu], outputs=[audio, out_ps])
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@torch.no_grad()
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def lf_forward(token_lists, voice, speed, device='cpu'):
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