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import gradio as gr |
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TAG_PLACEHOLDER = "funk, pop, soul, rock, melodic, guitar, drums, bass, keyboard, percussion, 105 BPM, energetic, upbeat, groovy, vibrant, dynamic" |
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LYRIC_PLACEHOLDER = """[verse] |
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Neon lights they flicker bright |
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City hums in dead of night |
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Rhythms pulse through concrete veins |
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Lost in echoes of refrains |
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[verse] |
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Bassline groovin' in my chest |
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Heartbeats match the city's zest |
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Electric whispers fill the air |
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Synthesized dreams everywhere |
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[chorus] |
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Turn it up and let it flow |
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Feel the fire let it grow |
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In this rhythm we belong |
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Hear the night sing out our song |
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[verse] |
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Guitar strings they start to weep |
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Wake the soul from silent sleep |
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Every note a story told |
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In this night we’re bold and gold |
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[bridge] |
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Voices blend in harmony |
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Lost in pure cacophony |
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Timeless echoes timeless cries |
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Soulful shouts beneath the skies |
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[verse] |
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Keyboard dances on the keys |
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Melodies on evening breeze |
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Catch the tune and hold it tight |
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In this moment we take flight |
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""" |
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def create_output_ui(task_name="Text2Music"): |
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output_audio1 = gr.Audio(type="filepath", label=f"{task_name} Generated Audio 1") |
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with gr.Accordion(f"{task_name} Parameters", open=False): |
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input_params_json = gr.JSON(label=f"{task_name} Parameters") |
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outputs = [output_audio1] |
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return outputs, input_params_json |
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def dump_func(*args): |
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print(args) |
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return [] |
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def create_text2music_ui( |
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gr, |
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text2music_process_func, |
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sample_data_func=None, |
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): |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Row(equal_height=True): |
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audio_duration = gr.Slider(-1, 240.0, step=0.00001, value=180, label="Audio Duration", interactive=True, info="-1 means random duration (30 ~ 240).", scale=9) |
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sample_bnt = gr.Button("Sample", variant="primary", scale=1) |
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prompt = gr.Textbox(lines=2, label="Tags", max_lines=4, placeholder=TAG_PLACEHOLDER, info="Support tags, descriptions, and scene. Use commas to separate different tags.") |
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lyrics = gr.Textbox(lines=9, label="Lyrics", max_lines=13, placeholder=LYRIC_PLACEHOLDER, info="Support lyric structure tags like [verse], [chorus], and [bridge] to separate different parts of the lyrics.\nUse [instrumental] or [inst] to generate instrumental music. Not support genre structure tag in lyrics") |
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with gr.Accordion("Basic Settings", open=True): |
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infer_step = gr.Slider(minimum=1, maximum=1000, step=1, value=60, label="Infer Steps", interactive=True) |
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guidance_scale = gr.Slider(minimum=0.0, maximum=200.0, step=0.1, value=15.0, label="Guidance Scale", interactive=True, info="When guidance_scale_lyric > 1 and guidance_scale_text > 1, the guidance scale will not be applied.") |
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guidance_scale_text = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=5.0, label="Guidance Scale Text", interactive=True, info="Guidance scale for text condition. It can only apply to cfg. set guidance_scale_text=5.0, guidance_scale_lyric=1.5 for start") |
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guidance_scale_lyric = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=1.5, label="Guidance Scale Lyric", interactive=True) |
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manual_seeds = gr.Textbox(label="manual seeds (default None)", placeholder="1,2,3,4", value=None, info="Seed for the generation") |
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with gr.Accordion("Advanced Settings", open=False): |
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scheduler_type = gr.Radio(["euler", "heun"], value="euler", label="Scheduler Type", elem_id="scheduler_type", info="Scheduler type for the generation. euler is recommended. heun will take more time.") |
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cfg_type = gr.Radio(["cfg", "apg", "cfg_star"], value="apg", label="CFG Type", elem_id="cfg_type", info="CFG type for the generation. apg is recommended. cfg and cfg_star are almost the same.") |
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use_erg_tag = gr.Checkbox(label="use ERG for tag", value=True, info="Use Entropy Rectifying Guidance for tag. It will multiple a temperature to the attention to make a weaker tag condition and make better diversity.") |
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use_erg_lyric = gr.Checkbox(label="use ERG for lyric", value=True, info="The same but apply to lyric encoder's attention.") |
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use_erg_diffusion = gr.Checkbox(label="use ERG for diffusion", value=True, info="The same but apply to diffusion model's attention.") |
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omega_scale = gr.Slider(minimum=-100.0, maximum=100.0, step=0.1, value=10.0, label="Granularity Scale", interactive=True, info="Granularity scale for the generation. Higher values can reduce artifacts") |
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guidance_interval = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Guidance Interval", interactive=True, info="Guidance interval for the generation. 0.5 means only apply guidance in the middle steps (0.25 * infer_steps to 0.75 * infer_steps)") |
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guidance_interval_decay = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.0, label="Guidance Interval Decay", interactive=True, info="Guidance interval decay for the generation. Guidance scale will decay from guidance_scale to min_guidance_scale in the interval. 0.0 means no decay.") |
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min_guidance_scale = gr.Slider(minimum=0.0, maximum=200.0, step=0.1, value=3.0, label="Min Guidance Scale", interactive=True, info="Min guidance scale for guidance interval decay's end scale") |
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oss_steps = gr.Textbox(label="OSS Steps", placeholder="16, 29, 52, 96, 129, 158, 172, 183, 189, 200", value=None, info="Optimal Steps for the generation. But not test well") |
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text2music_bnt = gr.Button(variant="primary") |
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with gr.Column(): |
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outputs, input_params_json = create_output_ui() |
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with gr.Tab("retake"): |
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retake_variance = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.2, label="variance", info="Variance for the retake. 0.0 means no variance. 1.0 means full variance.") |
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retake_seeds = gr.Textbox(label="retake seeds (default None)", placeholder="", value=None, info="Seed for the retake.") |
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retake_bnt = gr.Button(variant="primary") |
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retake_outputs, retake_input_params_json = create_output_ui("Retake") |
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def retake_process_func(json_data, retake_variance, retake_seeds): |
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return text2music_process_func( |
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json_data["audio_duration"], |
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json_data["prompt"], |
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json_data["lyrics"], |
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json_data["infer_step"], |
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json_data["guidance_scale"], |
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json_data["scheduler_type"], |
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json_data["cfg_type"], |
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json_data["omega_scale"], |
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", ".join(map(str, json_data["actual_seeds"])), |
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json_data["guidance_interval"], |
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json_data["guidance_interval_decay"], |
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json_data["min_guidance_scale"], |
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json_data["use_erg_tag"], |
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json_data["use_erg_lyric"], |
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json_data["use_erg_diffusion"], |
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", ".join(map(str, json_data["oss_steps"])), |
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json_data["guidance_scale_text"] if "guidance_scale_text" in json_data else 0.0, |
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json_data["guidance_scale_lyric"] if "guidance_scale_lyric" in json_data else 0.0, |
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retake_seeds=retake_seeds, |
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retake_variance=retake_variance, |
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task="retake", |
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) |
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retake_bnt.click( |
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fn=retake_process_func, |
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inputs=[ |
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input_params_json, |
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retake_variance, |
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retake_seeds, |
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], |
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outputs=retake_outputs + [retake_input_params_json], |
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) |
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with gr.Tab("repainting"): |
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pass |
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with gr.Tab("edit"): |
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pass |
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def sample_data(): |
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json_data = sample_data_func() |
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return ( |
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json_data["audio_duration"], |
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json_data["prompt"], |
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json_data["lyrics"], |
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json_data["infer_step"], |
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json_data["guidance_scale"], |
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json_data["scheduler_type"], |
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json_data["cfg_type"], |
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json_data["omega_scale"], |
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", ".join(map(str, json_data["actual_seeds"])), |
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json_data["guidance_interval"], |
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json_data["guidance_interval_decay"], |
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json_data["min_guidance_scale"], |
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json_data["use_erg_tag"], |
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json_data["use_erg_lyric"], |
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json_data["use_erg_diffusion"], |
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", ".join(map(str, json_data["oss_steps"])), |
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json_data["guidance_scale_text"] if "guidance_scale_text" in json_data else 0.0, |
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json_data["guidance_scale_lyric"] if "guidance_scale_lyric" in json_data else 0.0, |
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) |
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sample_bnt.click( |
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sample_data, |
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outputs=[ |
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audio_duration, |
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prompt, |
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lyrics, |
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infer_step, |
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guidance_scale, |
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scheduler_type, |
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cfg_type, |
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omega_scale, |
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manual_seeds, |
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guidance_interval, |
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guidance_interval_decay, |
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min_guidance_scale, |
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use_erg_tag, |
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use_erg_lyric, |
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use_erg_diffusion, |
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oss_steps, |
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guidance_scale_text, |
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guidance_scale_lyric, |
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], |
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) |
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text2music_bnt.click( |
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fn=text2music_process_func, |
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inputs=[ |
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audio_duration, |
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prompt, |
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lyrics, |
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infer_step, |
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guidance_scale, |
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scheduler_type, |
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cfg_type, |
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omega_scale, |
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manual_seeds, |
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guidance_interval, |
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guidance_interval_decay, |
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min_guidance_scale, |
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use_erg_tag, |
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use_erg_lyric, |
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use_erg_diffusion, |
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oss_steps, |
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guidance_scale_text, |
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guidance_scale_lyric, |
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], outputs=outputs + [input_params_json] |
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) |
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def create_main_demo_ui( |
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text2music_process_func=dump_func, |
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sample_data_func=dump_func, |
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): |
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with gr.Blocks( |
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title="FusicModel 1.0 DEMO", |
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) as demo: |
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gr.Markdown( |
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""" |
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<h1 style="text-align: center;">FusicModel 1.0 DEMO</h1> |
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""" |
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) |
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with gr.Tab("text2music"): |
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create_text2music_ui( |
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gr=gr, |
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text2music_process_func=text2music_process_func, |
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sample_data_func=sample_data_func, |
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) |
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return demo |
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if __name__ == "__main__": |
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demo = create_main_demo_ui() |
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demo.launch( |
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server_name="0.0.0.0", |
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server_port=7860, |
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) |
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