add Qwen3VL model
This commit is contained in:
jhqxxx
@@ -0,0 +1,199 @@
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use anyhow::{Result, anyhow};
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use candle_core::{DType, Device, Tensor};
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use candle_nn::VarBuilder;
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use openai_dive::v1::resources::chat::{ChatCompletionChunkResponse, ChatCompletionParameters, ChatCompletionResponse};
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use rocket::futures::Stream;
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use rocket::async_stream::stream;
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use crate::{
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chat_template::ChatTemplate,
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models::{GenerateModel, qwen3vl::{
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config::{Qwen3VLConfig, Qwen3VLGenerationConfig},
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model::Qwen3VLModel,
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processor::Qwen3VLProcessor,
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}},
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tokenizer::TokenizerModel,
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utils::{
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build_completion_chunk_response, build_completion_response, find_type_files, get_device, get_dtype, get_logit_processor
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},
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};
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pub struct Qwen3VLGenerateModel<'a> {
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chat_template: ChatTemplate<'a>,
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tokenizer: TokenizerModel,
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pre_processor: Qwen3VLProcessor,
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qwen3_vl: Qwen3VLModel,
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device: Device,
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eos_token_id1: u32,
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eos_token_id2: u32,
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generation_config: Qwen3VLGenerationConfig,
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}
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impl<'a> Qwen3VLGenerateModel<'a> {
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pub fn init(path: &str, device: Option<&Device>, dtype: Option<DType>) -> Result<Self> {
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let chat_template = ChatTemplate::init(path)?;
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let tokenizer = TokenizerModel::init(path)?;
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let config_path = path.to_string() + "/config.json";
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let cfg: Qwen3VLConfig = serde_json::from_slice(&std::fs::read(config_path)?)?;
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let device = get_device(device);
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let cfg_dtype = cfg.text_config.dtype.as_str();
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let dtype = get_dtype(dtype, cfg_dtype);
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let pre_processor = Qwen3VLProcessor::new(path, &device, dtype)?;
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let model_list = find_type_files(path, "safetensors")?;
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let vb = unsafe { VarBuilder::from_mmaped_safetensors(&model_list, dtype, &device)? };
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let vb = vb.pp("model");
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let qwen3_vl = Qwen3VLModel::new(cfg, vb)?;
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let generation_config_path = path.to_string() + "/generation_config.json";
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let generation_config: Qwen3VLGenerationConfig =
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serde_json::from_slice(&std::fs::read(generation_config_path)?)?;
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Ok(Self {
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chat_template,
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tokenizer,
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pre_processor,
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qwen3_vl,
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device,
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eos_token_id1: generation_config.eos_token_id[0] as u32,
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eos_token_id2: generation_config.eos_token_id[1] as u32,
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generation_config,
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})
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}
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}
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impl<'a> GenerateModel for Qwen3VLGenerateModel<'a> {
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fn generate(&mut self, mes: ChatCompletionParameters) -> Result<ChatCompletionResponse> {
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let temperature = match mes.temperature {
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None => self.generation_config.temperature,
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Some(tem) => tem,
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};
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let top_p = match mes.top_p {
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None => self.generation_config.top_p,
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Some(top_p) => top_p,
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};
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let top_k = self.generation_config.top_k;
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let mut logit_processor = get_logit_processor(Some(temperature), Some(top_p), Some(top_k));
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let mes_render = self.chat_template.apply_chat_template(&mes)?;
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let input = self.pre_processor.process_info(&mes, &mes_render)?;
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let mut input_ids = self
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.tokenizer
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.text_encode(input.replace_text.clone(), &self.device)?;
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let mut seq_len = input_ids.dim(1)?;
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let mut seqlen_offset = 0;
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let mut pixel_values = input.pixel_values.as_ref();
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let image_grid_thw = input.image_grid_thw.as_ref();
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let mut pixel_values_video = input.pixel_values_video.as_ref();
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let video_grid_thw = input.video_grid_thw.as_ref();
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let mut cache_position = Tensor::arange(0u32, seq_len as u32, &self.device)?;
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let mut generate = Vec::new();
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let sample_len = mes.max_tokens.unwrap_or(1024);
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for _ in 0..sample_len {
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let logits = self.qwen3_vl.forward(
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&input_ids,
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pixel_values,
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image_grid_thw,
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pixel_values_video,
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video_grid_thw,
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Some(&cache_position),
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seqlen_offset,
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)?;
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let logits = logits.squeeze(0)?.squeeze(0)?.to_dtype(DType::F32)?;
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let next_token = logit_processor.sample(&logits)?;
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generate.push(next_token);
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if next_token == self.eos_token_id1 || next_token == self.eos_token_id2 {
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break;
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}
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seqlen_offset += seq_len;
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seq_len = 1;
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input_ids = Tensor::from_vec(vec![next_token], (1, 1), &self.device)?;
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cache_position = Tensor::from_vec(vec![seqlen_offset as u32], 1, &self.device)?;
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pixel_values = None;
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pixel_values_video = None;
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}
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let res = self.tokenizer.token_decode(generate)?;
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self.qwen3_vl.clear_kv_cache();
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let response = build_completion_response(res, "qwen3vl");
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Ok(response)
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}
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fn generate_stream(
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&mut self,
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mes: ChatCompletionParameters,
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) -> Result<impl Stream<Item = Result<ChatCompletionChunkResponse, anyhow::Error>>> {
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let temperature = match mes.temperature {
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None => self.generation_config.temperature,
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Some(tem) => tem,
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};
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let top_p = match mes.top_p {
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None => self.generation_config.top_p,
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Some(top_p) => top_p,
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};
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let top_k = self.generation_config.top_k;
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let mut logit_processor = get_logit_processor(Some(temperature), Some(top_p), Some(top_k));
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let mes_render = self.chat_template.apply_chat_template(&mes)?;
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let input = self.pre_processor.process_info(&mes, &mes_render)?;
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let mut input_ids = self
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.tokenizer
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.text_encode(input.replace_text.clone(), &self.device)?;
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let mut seq_len = input_ids.dim(1)?;
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let mut seqlen_offset = 0;
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let pixel_values = input.pixel_values.clone();
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let image_grid_thw = input.image_grid_thw.clone();
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let pixel_values_video = input.pixel_values_video.clone();
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let video_grid_thw = input.video_grid_thw.clone();
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let mut cache_position = Tensor::arange(0u32, seq_len as u32, &self.device)?;
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let sample_len = mes.max_tokens.unwrap_or(1024);
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let stream = stream! {
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let mut error_tokens = Vec::new();
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let mut pixel_values = pixel_values.as_ref();
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let image_grid_thw = image_grid_thw.as_ref();
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let mut pixel_values_video = pixel_values_video.as_ref();
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let video_grid_thw = video_grid_thw.as_ref();
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for _ in 0..sample_len {
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let logits = self.qwen3_vl.forward(
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&input_ids,
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pixel_values,
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image_grid_thw,
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pixel_values_video,
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video_grid_thw,
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Some(&cache_position),
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seqlen_offset,
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)?;
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let logits = logits.squeeze(0)?.squeeze(0)?.to_dtype(DType::F32)?;
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let next_token = logit_processor.sample(&logits)?;
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let mut decode_ids = Vec::new();
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if !error_tokens.is_empty() {
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decode_ids.extend_from_slice(&error_tokens);
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}
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decode_ids.push(next_token);
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let decoded_token = self.tokenizer.token_decode(decode_ids).map_err(|e| anyhow!(format!("stream decode error{}", e)))?;
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if decoded_token.contains("�") {
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error_tokens.push(next_token);
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if error_tokens.len() > 3 {
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error_tokens.clear();
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}
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seqlen_offset += seq_len;
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seq_len = 1;
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input_ids = Tensor::from_vec(vec![next_token], (1, 1), &self.device)?;
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cache_position = Tensor::from_vec(vec![seqlen_offset as u32], 1, &self.device)?;
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pixel_values = None;
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pixel_values_video = None;
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continue;
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}
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error_tokens.clear();
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let chunk = build_completion_chunk_response(decoded_token, "qwen3vl", None, None);
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yield Ok(chunk);
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if next_token == self.eos_token_id1 || next_token == self.eos_token_id2 {
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break;
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}
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seqlen_offset += seq_len;
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seq_len = 1;
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input_ids = Tensor::from_vec(vec![next_token], (1, 1), &self.device)?;
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cache_position = Tensor::from_vec(vec![seqlen_offset as u32], 1, &self.device)?;
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pixel_values = None;
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pixel_values_video = None;
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}
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self.qwen3_vl.clear_kv_cache();
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};
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Ok(stream)
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}
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}
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