Spaces:
Running
on
Zero
Running
on
Zero
File size: 2,635 Bytes
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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=8)
@spaces.GPU(duration=120)
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.",
examples=[
["trap, synthesizer, songstarters, dark, G# minor, 140 bpm", "./assets/kalhonaho.mp3"],
["upbeat, electronic, synth, dance, 120 bpm", None]
]
).launch() |