jhqxxx
110 lines
3.8 KiB
Rust
110 lines
3.8 KiB
Rust
use std::{pin::pin, time::Instant};
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use aha::{
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chat::ChatCompletionParameters,
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models::{GenerateModel, lfm2vl::generate::Lfm2VLGenerateModel},
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};
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use anyhow::Result;
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use rocket::futures::StreamExt;
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#[test]
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fn lfm2vl_generate() -> Result<()> {
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// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda --test test_lfm2vl lfm2vl_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!("{}/LiquidAI/LFM2.5-VL-1.6B/", save_dir);
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let model_path = format!("{}/LiquidAI/LFM2-VL-1.6B/", save_dir);
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let message = r#"
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{
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"model": "lfm2vl",
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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": "image",
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"image_url":
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{
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"url": "file://./assets/img/ocr_test1.png"
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}
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},
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{
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"type": "text",
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"text": "图片里面是什么"
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}
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]
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}
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]
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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 model = Lfm2VLGenerateModel::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 result = model.generate(mes)?;
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let i_duration = i_start.elapsed();
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println!("generate: \n {:?}", result);
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if let Some(usage) = &result.usage {
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let num_token = usage.total_tokens;
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let duration_secs = i_duration.as_secs_f64();
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let tps = num_token as f64 / duration_secs;
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println!("Tokens per second (TPS): {:.2}", tps);
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}
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println!("Time elapsed in generate is: {:?}", i_duration);
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Ok(())
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}
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#[tokio::test]
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async fn lfm2vl_stream() -> Result<()> {
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// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda --test test_lfm2vl lfm2vl_stream -r -- --nocapture
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// test with cuda+flash-attn: RUST_BACKTRACE=1 cargo test -F cuda,flash-attn qwen3_0_6b_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!("{}/LiquidAI/LFM2-1.2B/", save_dir);
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let model_path = format!("{}/LiquidAI/LFM2.5-VL-1.6B/", save_dir);
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let message = r#"
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{
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"model": "lfm2vl",
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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": "image",
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"image_url":
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{
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"url": "file://./assets/img/ocr_test1.png"
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}
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},
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{
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"type": "text",
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"text": "请分析图片并提取所有可见文本内容，按从左到右、从上到下的布局，返回纯文本"
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}
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]
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}
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]
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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 model = Lfm2VLGenerateModel::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 result = model.generate(mes)?;
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let mut stream = pin!(model.generate_stream(mes)?);
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let i_duration = i_start.elapsed();
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while let Some(token) = stream.next().await {
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println!("generate: \n {:?}", token);
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}
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println!("Time elapsed in generate is: {:?}", i_duration);
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Ok(())
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}
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