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| import gradio as gr | |
| import torchaudio | |
| from audiocraft.models import MusicGen | |
| from audiocraft.data.audio import audio_write | |
| import spaces | |
| import logging | |
| import os | |
| import uuid | |
| from torch.cuda.amp import autocast | |
| import torch | |
| ZERO_GPU_PATCH_TORCH_DEVICE = 1 | |
| # Configura o logging | |
| logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') | |
| logging.info("Carregando o modelo pré-treinado.") | |
| model = MusicGen.get_pretrained('nateraw/musicgen-songstarter-v0.2') | |
| model.set_generation_params(duration=30) | |
| def generate_music(description, melody_audio): | |
| with autocast(): | |
| logging.info("Iniciando a geração de música.") | |
| if description: | |
| description = [description] | |
| if melody_audio: | |
| logging.info(f"Carregando a melodia de áudio de: {melody_audio}") | |
| melody, sr = torchaudio.load(melody_audio) | |
| logging.info("Gerando música com descrição e melodia.") | |
| wav = model.generate_with_chroma(description, melody[None], sr) | |
| else: | |
| logging.info("Gerando música apenas com descrição.") | |
| wav = model.generate(description) | |
| else: | |
| logging.info("Gerando música de forma incondicional.") | |
| wav = model.generate_unconditional(1) | |
| filename = f'{str(uuid.uuid4())}' | |
| logging.info(f"Salvando a música gerada com o nome: {filename}") | |
| path = audio_write(filename, wav[0].cpu().to(torch.float32), model.sample_rate, strategy="loudness", loudness_compressor=True) | |
| print("Música salva em", path, ".") | |
| # Verifica a forma do tensor de áudio e se foi salvo corretamente | |
| logging.info(f"A forma do tensor de áudio gerado: {wav[0].shape}") | |
| logging.info("Música gerada e salva com sucesso.") | |
| if not os.path.exists(path): | |
| raise ValueError(f'Failed to save audio to {path}') | |
| return path | |
| # Define a interface Gradio | |
| description = gr.Textbox(label="Description", placeholder="acoustic, guitar, melody, trap, d minor, 90 bpm") | |
| melody_audio = gr.Audio(label="Melody Audio (optional)", type="filepath") | |
| output_path = gr.Audio(label="Generated Music", type="filepath") | |
| gr.Interface( | |
| fn=generate_music, | |
| inputs=[description, melody_audio], | |
| outputs=output_path, | |
| title="MusicGen Demo", | |
| description="Generate music using the MusicGen model by Nateraw.\n\n" | |
| "Model: musicgen-songstarter-v0.2\n" | |
| "Download the model [here](https://huggingface.co/nateraw/musicgen-songstarter-v0.2).\n\n" | |
| "musicgen-songstarter-v0.2 is a musicgen-stereo-melody-large fine-tuned on a dataset of melody loops from Nateraw's Splice sample library. " | |
| "It's intended to be used to generate song ideas that are useful for music producers. It generates stereo audio in 32khz.\n\n" | |
| "Compared to musicgen-songstarter-v0.1, this new version:\n" | |
| "- Was trained on 3x more unique, manually-curated samples that Nateraw painstakingly purchased on Splice\n" | |
| "- Is twice the size, bumped up from size medium ➡️ large transformer LM\n\n" | |
| "If you find this model interesting, please consider:\n" | |
| "- Following Nateraw on [GitHub](https://github.com/nateraw)\n" | |
| "- Following Nateraw on [Twitter](https://twitter.com/nateraw)\n\n" | |
| "Space created by [artificialguybr](https://twitter.com/artificialguybr) on Twitter.", | |
| examples=[ | |
| ["trap, synthesizer, songstarters, dark, G# minor, 140 bpm", "./assets/kalhonaho.mp3"], | |
| ["upbeat, electronic, synth, dance, 120 bpm", None] | |
| ] | |
| ).launch() |