jhqxxx
121 lines
4.5 KiB
Rust
121 lines
4.5 KiB
Rust
use std::time::Instant;
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use aha::{
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models::{
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GenerateModel,
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voxcpm::{generate::VoxCPMGenerate, tokenizer::SingleChineseTokenizer},
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},
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utils::audio_utils::{extract_and_save_audio_from_response, save_wav},
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};
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use aha_openai_dive::v1::resources::chat::ChatCompletionParameters;
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use anyhow::{Ok, Result};
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#[test]
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fn voxcpm_use_message_generate() -> Result<()> {
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// RUST_BACKTRACE=1 cargo test -F cuda voxcpm_use_message_generate -r -- --nocapture
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let save_dir =
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aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
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let model_path = format!("{}/OpenBMB/VoxCPM-0.5B/", save_dir);
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let message = r#"
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{
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"model": "voxcpm",
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"messages": [
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{
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"role": "user",
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"content": [
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{
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"type": "audio",
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"audio_url":
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{
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"url": "https://sis-sample-audio.obs.cn-north-1.myhuaweicloud.com/16k16bit.wav"
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}
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},
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{
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"type": "text",
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"text": "VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly realistic speech."
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}
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]
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}
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],
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"metadata": {"prompt_text": "华为致力于把数字世界带给每个人，每个家庭，每个组织，构建万物互联的智能世界。"}
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}
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"#;
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let mes: ChatCompletionParameters = serde_json::from_str(message)?;
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let i_start = Instant::now();
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let mut voxcpm_generate = VoxCPMGenerate::init(&model_path, None, None)?;
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let i_duration = i_start.elapsed();
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println!("Time elapsed in load model is: {:?}", i_duration);
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let i_start = Instant::now();
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let generate = voxcpm_generate.generate(mes)?;
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let save_path = extract_and_save_audio_from_response(&generate, "./")?;
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for path in save_path {
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println!("save audio: {}", path);
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}
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let i_duration = i_start.elapsed();
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println!("Time elapsed in generate is: {:?}", i_duration);
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// save_wav(&generate, "voxcpm.wav", 16000)?;
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Ok(())
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}
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#[test]
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fn voxcpm_generate() -> Result<()> {
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// RUST_BACKTRACE=1 cargo test -F cuda voxcpm_generate -r -- --nocapture
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let save_dir =
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aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
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let model_path = format!("{}/OpenBMB/VoxCPM-0.5B/", save_dir);
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let i_start = Instant::now();
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let mut voxcpm_generate = VoxCPMGenerate::init(&model_path, None, None)?;
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let i_duration = i_start.elapsed();
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println!("Time elapsed in load model is: {:?}", i_duration);
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let i_start = Instant::now();
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// let generate = voxcpm_generate.generate_simple("太阳当空照，花儿对我笑，小鸟说早早早".to_string())?;
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let generate = voxcpm_generate.inference(
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"VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly realistic speech.".to_string(),
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Some("啥子小师叔，打狗还要看主人，你再要继续，我，就是你的对手".to_string()),
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Some("file://./assets/audio/voice_01.wav".to_string()),
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// Some("一定被灰太狼给吃了，我已经为他准备好了花圈了".to_string()),
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// Some("file://./assets/audio/voice_05.wav".to_string()),
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2,
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100,
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10,
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2.0,
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// false,
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6.0,
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)?;
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// 创建prompt_cache
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// let _ = voxcpm_generate.build_prompt_cache(
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// "啥子小师叔，打狗还要看主人，你再要继续，我，就是你的对手".to_string(),
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// "file://./assets/audio/voice_01.wav".to_string(),
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// )?;
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// // 使用prompt_cache生成语音
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// let generate = voxcpm_generate.generate_use_prompt_cache(
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// "太阳当空照，花儿对我笑，小鸟说早早早".to_string(),
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// 2,
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// 100,
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// 10,
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// 2.0,
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// false,
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// 6.0,
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// )?;
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let i_duration = i_start.elapsed();
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println!("Time elapsed in generate is: {:?}", i_duration);
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save_wav(&generate, "voxcpm.wav", 16000)?;
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Ok(())
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}
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#[test]
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fn voxcpm_tokenizer() -> Result<()> {
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let save_dir =
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aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
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let model_path = format!("{}/OpenBMB/VoxCPM-0.5B/", save_dir);
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let tokenizer = SingleChineseTokenizer::new(&model_path)?;
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let ids = tokenizer.encode("你好啊，你吃饭了吗".to_string())?;
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println!("ids: {:?}", ids);
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Ok(())
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}
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