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5f1f473
1
Parent(s):
70e4553
Update app.py
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app.py
CHANGED
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@@ -13,6 +13,8 @@ import gradio as gr
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MODEL_NAMES = [
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"Fastspeech2 + Melgan",
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"Tacotron2 + Melgan",
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]
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fastspeech = TFAutoModel.from_pretrained("tensorspeech/tts-fastspeech-ljspeech-en", name="fastspeech")
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@@ -34,7 +36,7 @@ def inference(input_text, model_type):
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processor = AutoProcessor.from_pretrained("tensorspeech/tts-tacotron2-ljspeech-en")
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input_ids = processor.text_to_sequence(input_text)
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if text2mel_name == "
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_, mel_outputs, stop_token_prediction, alignment_history = text2mel_model.inference(
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tf.expand_dims(tf.convert_to_tensor(input_ids, dtype=tf.int32), 0),
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tf.convert_to_tensor([len(input_ids)], tf.int32),
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MODEL_NAMES = [
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"Fastspeech2 + Melgan",
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"Tacotron2 + Melgan",
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"Tacotron2 + MB-Melgan",
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"Fastspeech2 + MB-Melgan"
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]
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fastspeech = TFAutoModel.from_pretrained("tensorspeech/tts-fastspeech-ljspeech-en", name="fastspeech")
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processor = AutoProcessor.from_pretrained("tensorspeech/tts-tacotron2-ljspeech-en")
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input_ids = processor.text_to_sequence(input_text)
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if text2mel_name == "Tacotron2":
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_, mel_outputs, stop_token_prediction, alignment_history = text2mel_model.inference(
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tf.expand_dims(tf.convert_to_tensor(input_ids, dtype=tf.int32), 0),
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tf.convert_to_tensor([len(input_ids)], tf.int32),
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