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import torch
import torchaudio
from einops import rearrange
import gradio as gr
import spaces
# Importing the model-related functions
from stable_audio_tools import get_pretrained_model
from stable_audio_tools.inference.generation import generate_diffusion_cond
# Function to set up, generate, and process the audio
@spaces.GPU(duration=120) # Allocate GPU only when this function is called
def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7):
device = "cuda" if torch.cuda.is_available() else "cpu"
# Download and set up the model
model, model_config = get_pretrained_model("stabilityai/stable-audio-open-1.0")
sample_rate = model_config["sample_rate"]
sample_size = model_config["sample_size"]
model = model.to(device)
# Set up text and timing conditioning
conditioning = [{
"prompt": prompt,
"seconds_start": 0,
"seconds_total": seconds_total
}]
# Generate stereo audio
output = generate_diffusion_cond(
model,
steps=steps,
cfg_scale=cfg_scale,
conditioning=conditioning,
sample_size=sample_size,
sigma_min=0.3,
sigma_max=500,
sampler_type="dpmpp-3m-sde",
device=device
)
# Rearrange audio batch to a single sequence
output = rearrange(output, "b d n -> d (b n)")
# Peak normalize, clip, convert to int16
output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu()
# Save to file
torchaudio.save("output.wav", output, sample_rate)
# Return the path to the generated audio file
return "output.wav"
# Setting up the Gradio Interface
interface = gr.Interface(
fn=generate_audio,
inputs=[
gr.Textbox(label="Prompt", placeholder="Enter your text prompt here"),
gr.Slider(0, 47, value=30, label="Duration in Seconds"),
gr.Slider(10, 300, value=100, step=10, label="Number of Diffusion Steps"),
gr.Slider(1, 15, value=7, step=0.1, label="CFG Scale")
],
outputs=gr.Audio(type="filepath", label="Generated Audio"),
title="Stable Audio Generator",
description="Generate variable-length stereo audio at 44.1kHz from text prompts using Stable Audio Open 1.0."
)
# Launch the Interface
interface.launch()
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