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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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