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Running
on
T4
| """ | |
| Copyright (c) Meta Platforms, Inc. and affiliates. | |
| All rights reserved. | |
| This source code is licensed under the license found in the | |
| LICENSE file in the root directory of this source tree. | |
| """ | |
| import torch | |
| import gradio as gr | |
| from hf_loading import get_pretrained | |
| MODEL = None | |
| def load_model(version): | |
| print("Loading model", version) | |
| return get_pretrained(version) | |
| def predict(model, text, melody, duration, topk, topp, temperature, cfg_coef): | |
| global MODEL | |
| topk = int(topk) | |
| if MODEL is None or MODEL.name != model: | |
| MODEL = load_model(model) | |
| if duration > MODEL.lm.cfg.dataset.segment_duration: | |
| raise gr.Error("MusicGen currently supports durations of up to 30 seconds!") | |
| MODEL.set_generation_params( | |
| use_sampling=True, | |
| top_k=topk, | |
| top_p=topp, | |
| temperature=temperature, | |
| cfg_coef=cfg_coef, | |
| duration=duration, | |
| ) | |
| if melody: | |
| sr, melody = melody[0], torch.from_numpy(melody[1]).to(MODEL.device).float().t().unsqueeze(0) | |
| print(melody.shape) | |
| if melody.dim() == 2: | |
| melody = melody[None] | |
| melody = melody[..., :int(sr * MODEL.lm.cfg.dataset.segment_duration)] | |
| output = MODEL.generate_with_chroma( | |
| descriptions=[text], | |
| melody_wavs=melody, | |
| melody_sample_rate=sr, | |
| progress=False | |
| ) | |
| else: | |
| output = MODEL.generate(descriptions=[text], progress=False) | |
| output = output.detach().cpu().numpy() | |
| return MODEL.sample_rate, output | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| """ | |
| # MusicGen | |
| This is the demo for MusicGen, a simple and controllable model for music generation presented at: "Simple and Controllable Music Generation". | |
| Below we present 3 model variations: | |
| 1. Melody -- a music generation model capable of generating music condition on text and melody inputs. **Note**, you can also use text only. | |
| 2. Small -- a 300M transformer decoder conditioned on text only. | |
| 3. Medium -- a 1.5B transformer decoder conditioned on text only. | |
| See [github.com/facebookresearch/audiocraft](https://github.com/facebookresearch/audiocraft) | |
| for more details. | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Row(): | |
| text = gr.Text(label="Input Text", interactive=True) | |
| melody = gr.Audio(source="upload", type="numpy", label="Melody Condition (optional)", interactive=True) | |
| with gr.Row(): | |
| submit = gr.Button("Submit") | |
| with gr.Row(): | |
| model = gr.Radio(["melody", "medium", "small"], label="Model", value="melody", interactive=True) | |
| with gr.Row(): | |
| duration = gr.Slider(minimum=1, maximum=30, value=10, label="Duration", interactive=True) | |
| with gr.Row(): | |
| topk = gr.Number(label="Top-k", value=250, interactive=True) | |
| topp = gr.Number(label="Top-p", value=0, interactive=True) | |
| temperature = gr.Number(label="Temperature", value=1.0, interactive=True) | |
| cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True) | |
| with gr.Column(): | |
| output = gr.Audio(label="Generated Music", type="numpy") | |
| submit.click(predict, inputs=[model, text, melody, duration, topk, topp, temperature, cfg_coef], outputs=[output]) | |
| gr.Examples( | |
| fn=predict, | |
| examples=[ | |
| [ | |
| "An 80s driving pop song with heavy drums and synth pads in the background", | |
| "./assets/bach.mp3", | |
| "melody" | |
| ], | |
| [ | |
| "90s rock song with electric guitar and heavy drums", | |
| None, | |
| "medium" | |
| ], | |
| [ | |
| "a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions", | |
| "./assets/bach.mp3", | |
| "melody" | |
| ] | |
| ], | |
| inputs=[text, melody, model], | |
| outputs=[output] | |
| ) | |
| demo.launch() | |