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Update app.py
Browse files
app.py
CHANGED
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@@ -477,9 +477,9 @@ def doloudnorm(path):
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loudness = meter.integrated_loudness(data)
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loudness_normalized_audio = pyln.normalize.loudness(data, loudness, -12.0)
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sf.write(path, loudness_normalized_audio, rate)
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# 2x speedup (hopefully)
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def synthandreturn(text):
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text = text.strip()
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@@ -488,6 +488,7 @@ def synthandreturn(text):
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if len(text) < MIN_SAMPLE_TXT_LENGTH:
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raise gr.Error(f'Not enough text')
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if (toxicity.predict(text)['toxicity'] > 0.5):
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raise gr.Error('Your text failed the toxicity test')
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if not text:
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raise gr.Error(f'You did not enter any text')
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@@ -496,7 +497,7 @@ def synthandreturn(text):
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log_text(text)
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print("[debug] Using", mdl1, mdl2)
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def predict_and_update_result(text, model, result_storage):
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result = router.predict(text, AVAILABLE_MODELS[model], api_name="/synthesize")
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doloudnorm(result)
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result_storage[model] = result
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results = {}
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loudness = meter.integrated_loudness(data)
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loudness_normalized_audio = pyln.normalize.loudness(data, loudness, -12.0)
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sf.write(path, loudness_normalized_audio, rate)
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##########################
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# 2x speedup (hopefully) #
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##########################
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def synthandreturn(text):
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text = text.strip()
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if len(text) < MIN_SAMPLE_TXT_LENGTH:
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raise gr.Error(f'Not enough text')
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if (toxicity.predict(text)['toxicity'] > 0.5):
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print(f'Detected toxic content! "{text}"')
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raise gr.Error('Your text failed the toxicity test')
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if not text:
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raise gr.Error(f'You did not enter any text')
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log_text(text)
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print("[debug] Using", mdl1, mdl2)
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def predict_and_update_result(text, model, result_storage):
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result = router.predict(text, AVAILABLE_MODELS[model].lower(), api_name="/synthesize")
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doloudnorm(result)
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result_storage[model] = result
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results = {}
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