remove trailing whitespace
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pgosar
parent
9ce26becea
commit
9148e6020e
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@ -90,7 +90,7 @@ def load_models(whisper_backend_name, whisper_model_name, alignment_model_name,
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if align_model is None:
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raise gr.Error("Align model required for whisperx backend")
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transcribe_model = WhisperxModel(whisper_model_name, align_model)
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voicecraft_name = f"{voicecraft_model_name}.pth"
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ckpt_fn = f"./pretrained_models/{voicecraft_name}"
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encodec_fn = "./pretrained_models/encodec_4cb2048_giga.th"
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@ -132,7 +132,7 @@ def transcribe(seed, audio_path):
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if transcribe_model is None:
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raise gr.Error("Transcription model not loaded")
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seed_everything(seed)
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segments = transcribe_model.transcribe(audio_path)
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state = get_transcribe_state(segments)
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@ -234,7 +234,7 @@ def run(seed, left_margin, right_margin, codec_audio_sr, codec_sr, top_k, top_p,
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if mode != "Edit":
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from inference_tts_scale import inference_one_sample
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if smart_transcript:
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if smart_transcript:
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target_transcript = ""
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for word in transcribe_state["words_info"]:
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if word["end"] < prompt_end_time:
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@ -281,7 +281,7 @@ def run(seed, left_margin, right_margin, codec_audio_sr, codec_sr, top_k, top_p,
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morphed_span = (max(edit_start_time - left_margin, 1 / codec_sr), min(edit_end_time + right_margin, audio_dur))
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mask_interval = [[round(morphed_span[0]*codec_sr), round(morphed_span[1]*codec_sr)]]
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mask_interval = torch.LongTensor(mask_interval)
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_, gen_audio = inference_one_sample(voicecraft_model["model"],
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voicecraft_model["ckpt"]["config"],
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voicecraft_model["ckpt"]["phn2num"],
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@ -300,12 +300,12 @@ def run(seed, left_margin, right_margin, codec_audio_sr, codec_sr, top_k, top_p,
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output_audio = get_output_audio(previous_audio_tensors, codec_audio_sr)
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sentence_audio = get_output_audio(audio_tensors, codec_audio_sr)
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return output_audio, inference_transcript, sentence_audio, previous_audio_tensors
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def update_input_audio(audio_path):
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if audio_path is None:
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return 0, 0, 0
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info = torchaudio.info(audio_path)
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max_time = round(info.num_frames / info.sample_rate, 2)
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return [
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@ -314,7 +314,7 @@ def update_input_audio(audio_path):
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gr.Slider(maximum=max_time, value=max_time),
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]
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def change_mode(mode):
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tts_mode_controls, edit_mode_controls, edit_word_mode, split_text, long_tts_sentence_editor
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return [
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@ -416,7 +416,7 @@ demo_words_info = [
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def update_demo(mode, smart_transcript, edit_word_mode, transcript, edit_from_word, edit_to_word):
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if transcript not in all_demo_texts:
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return transcript, edit_from_word, edit_to_word
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replace_half = edit_word_mode == "Replace half"
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change_edit_from_word = edit_from_word == demo_words[2] or edit_from_word == demo_words[3]
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change_edit_to_word = edit_to_word == demo_words[11] or edit_to_word == demo_words[12]
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@ -456,7 +456,7 @@ with gr.Blocks() as app:
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transcribe_btn = gr.Button(value="Transcribe")
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align_btn = gr.Button(value="Align")
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with gr.Column(scale=3):
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with gr.Group():
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transcript = gr.Textbox(label="Text", lines=7, value=demo_text["TTS"]["smart"])
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@ -471,7 +471,7 @@ with gr.Blocks() as app:
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info="Split text into parts and run TTS for each part.", visible=False)
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edit_word_mode = gr.Radio(label="Edit word mode", choices=["Replace half", "Replace all"], value="Replace half",
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info="What to do with first and last word", visible=False)
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with gr.Group() as tts_mode_controls:
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prompt_to_word = gr.Dropdown(label="Last word in prompt", choices=demo_words, value=demo_words[10], interactive=True)
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prompt_end_time = gr.Slider(label="Prompt end time", minimum=0, maximum=7.93, step=0.001, value=3.016)
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@ -517,11 +517,11 @@ with gr.Blocks() as app:
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codec_sr = gr.Number(label="codec_sr", value=50, info='encodec specific, Do not change')
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silence_tokens = gr.Textbox(label="silence tokens", value="[1388,1898,131]", info="encodec specific, do not change")
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audio_tensors = gr.State()
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transcribe_state = gr.State(value={"words_info": demo_words_info})
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mode.change(fn=update_demo,
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inputs=[mode, smart_transcript, edit_word_mode, transcript, edit_from_word, edit_to_word],
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outputs=[transcript, edit_from_word, edit_to_word])
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@ -531,11 +531,11 @@ with gr.Blocks() as app:
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smart_transcript.change(fn=update_demo,
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inputs=[mode, smart_transcript, edit_word_mode, transcript, edit_from_word, edit_to_word],
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outputs=[transcript, edit_from_word, edit_to_word])
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load_models_btn.click(fn=load_models,
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inputs=[whisper_backend_choice, whisper_model_choice, align_model_choice, voicecraft_model_choice],
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outputs=[models_selector])
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input_audio.upload(fn=update_input_audio,
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inputs=[input_audio],
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outputs=[prompt_end_time, edit_start_time, edit_end_time])
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@ -564,7 +564,7 @@ with gr.Blocks() as app:
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split_text, sentence_selector, audio_tensors
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],
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outputs=[output_audio, inference_transcript, sentence_selector, audio_tensors])
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sentence_selector.change(fn=load_sentence,
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inputs=[sentence_selector, codec_audio_sr, audio_tensors],
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outputs=[sentence_audio])
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@ -580,7 +580,7 @@ with gr.Blocks() as app:
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split_text, sentence_selector, audio_tensors
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],
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outputs=[output_audio, inference_transcript, sentence_audio, audio_tensors])
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prompt_to_word.change(fn=update_bound_word,
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inputs=[gr.State(False), prompt_to_word, gr.State("Replace all")],
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outputs=[prompt_end_time])
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