forked from mrq/ai-voice-cloning
fixes
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9d2c7fb942
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@ -49,6 +49,7 @@ WHISPER_BACKENDS = ["openai/whisper", "lightmare/whispercpp"]
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VOCODERS = ['univnet', 'bigvgan_base_24khz_100band', 'bigvgan_24khz_100band']
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TTSES = ['tortoise']
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INFERENCING = False
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GENERATE_SETTINGS_ARGS = None
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LEARNING_RATE_SCHEMES = {"Multistep": "MultiStepLR", "Cos. Annealing": "CosineAnnealingLR_Restart"}
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@ -320,6 +321,7 @@ def generate(**kwargs):
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return info
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INFERENCING = True
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for line, cut_text in enumerate(texts):
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if parameters['emotion'] == "Custom":
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if parameters['prompt'] and parameters['prompt'].strip() != "":
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@ -371,6 +373,7 @@ def generate(**kwargs):
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del gen
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do_gc()
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INFERENCING = False
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for k in audio_cache:
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audio = audio_cache[k]['audio']
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@ -486,7 +489,11 @@ def generate(**kwargs):
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)
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def cancel_generate():
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if not INFERENCING:
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return
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import tortoise.api
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tortoise.api.STOP_SIGNAL = True
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def hash_file(path, algo="md5", buffer_size=0):
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12
src/webui.py
12
src/webui.py
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@ -155,6 +155,16 @@ def import_generate_settings_proxy( file=None ):
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return tuple(res)
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def reset_generate_settings_proxy( file=None ):
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global GENERATE_SETTINGS_ARGS
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settings = reset_generate_settings( file )
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res = []
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for k in GENERATE_SETTINGS_ARGS:
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res.append(settings[k] if k in settings else None)
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return tuple(res)
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def compute_latents_proxy(voice, voice_latents_chunks, progress=gr.Progress(track_tqdm=True)):
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compute_latents( voice=voice, voice_latents_chunks=voice_latents_chunks, progress=progress )
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return voice
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@ -688,7 +698,7 @@ def setup_gradio():
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)
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reset_generation_settings_button.click(
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fn=reset_generation_settings,
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fn=reset_generation_settings_proxy,
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inputs=None,
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outputs=generate_settings
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)
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