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https://github.com/huggingface/text-generation-inference.git
synced 2025-06-19 15:52:08 +00:00
Thanks clippy
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
This commit is contained in:
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@ -38,7 +38,7 @@ impl FromStr for LlamacppSplitMode {
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"row" => Ok(LlamacppSplitMode::Row),
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_ => match s.parse::<usize>() {
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Ok(n) => Ok(LlamacppSplitMode::GPU(n)),
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Err(_) => Err(format!("Choose a GPU number or `layer` or `row`")),
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Err(_) => Err("Choose a GPU number or `layer` or `row`".to_string()),
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}
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}
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}
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@ -176,8 +176,7 @@ impl LlamacppRequest {
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from: &ValidGenerateRequest,
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tx: UnboundedSender<Result<InferStreamResponse, InferError>>,
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) -> Option<Self>{
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if let Some(input_ids) = from.input_ids.as_ref() {
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Some(LlamacppRequest {
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from.input_ids.as_ref().map(|input_ids| LlamacppRequest {
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input_ids: input_ids.iter().map(|&x| x as i32).collect(),
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top_k: from.parameters.top_k as _,
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top_p: from.parameters.top_p as _,
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@ -190,12 +189,9 @@ impl LlamacppRequest {
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penalty_freq: from.parameters.frequency_penalty as _,
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penalty_present: 0.0, // disabled
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max_new_tokens: from.stopping_parameters.max_new_tokens as _,
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tx: tx,
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tx,
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time: Instant::now(),
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})
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} else {
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None
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}
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}
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}
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@ -404,7 +400,7 @@ impl LlamacppSampler {
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for (token, logprob) in llamacpp.logprobs.iter_mut().enumerate() {
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*logprob = llamacpp::llama_token_data {
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id: token as _,
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logit: unsafe { *logits.offset(token as _) },
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logit: unsafe { *logits.add(token) },
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p: 0.0,
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};
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}
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@ -484,7 +480,7 @@ impl LlamacppBackend {
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Ok(Some(request)) => {
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let n_tokens_to_add = request.input_ids.len();
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if n_tokens + n_tokens_to_add > conf.max_batch_total_tokens as usize {
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if n_tokens + n_tokens_to_add > conf.max_batch_total_tokens {
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flush(&mut requests, &mut n_tokens);
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}
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n_tokens += n_tokens_to_add;
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@ -511,7 +507,7 @@ impl LlamacppBackend {
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let _ = status_tx.send(true);
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while let Ok(requests) = sync_rx.recv() {
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if shutdown_rx.borrow().clone() {
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if *shutdown_rx.borrow() {
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break;
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}
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let start_time = Instant::now();
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@ -521,7 +517,7 @@ impl LlamacppBackend {
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for (seq_id, request) in requests.iter().enumerate() {
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debug!("Request: {:?}", request);
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// TODO remove this
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let sampler = match LlamacppSampler::new(&request) {
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let sampler = match LlamacppSampler::new(request) {
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Some(sampler) => sampler,
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_ => {
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let _ = request.tx.send(Err(InferError::IncompleteGeneration));
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@ -543,7 +539,7 @@ impl LlamacppBackend {
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batch_pos: llamacpp.batch.n_tokens as usize - 1,
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token: llamacpp::LLAMA_TOKEN_NULL,
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pos: last_pos as llamacpp::llama_pos + 1,
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sampler: sampler,
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sampler,
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text: String::with_capacity(1024),
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n_new_tokens: 0,
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running: true,
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@ -584,8 +580,8 @@ impl LlamacppBackend {
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let token = Token {
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id: next as _,
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text: piece,
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logprob: logprob,
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special: special,
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logprob,
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special,
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};
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let finish: Option<FinishReason> = {
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if unsafe { llamacpp::vocab_is_eog(llamacpp.vocab, next) } {
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@ -598,7 +594,7 @@ impl LlamacppBackend {
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};
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if let Some(reason) = finish {
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let _ = requests[seq.id].tx.send(Ok(InferStreamResponse::End {
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token: token,
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token,
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top_tokens: vec![],
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generated_text: GeneratedText {
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text: seq.text.clone(),
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@ -613,7 +609,7 @@ impl LlamacppBackend {
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continue;
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}
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let _ = requests[seq.id].tx.send(Ok(InferStreamResponse::Intermediate {
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token: token,
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token,
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top_tokens: vec![],
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}));
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}
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@ -215,7 +215,7 @@ async fn main() -> Result<(), RouterError> {
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.ok();
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let params = FromPretrainedParameters {
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revision: args.revision.clone(),
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token: token,
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token,
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..Default::default()
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};
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Tokenizer::from_pretrained(
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@ -227,8 +227,8 @@ async fn main() -> Result<(), RouterError> {
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let (backend, ok, shutdown) = LlamacppBackend::new(
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LlamacppConfig {
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model_gguf: args.model_gguf,
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n_threads: n_threads,
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n_threads_batch: n_threads_batch,
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n_threads,
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n_threads_batch,
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n_gpu_layers: args.n_gpu_layers,
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split_mode: args.split_mode,
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defrag_threshold: args.defrag_threshold,
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@ -239,9 +239,9 @@ async fn main() -> Result<(), RouterError> {
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type_k: args.type_k,
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type_v: args.type_v,
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offload_kqv: args.offload_kqv,
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max_batch_total_tokens: max_batch_total_tokens,
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max_physical_batch_total_tokens: max_physical_batch_total_tokens,
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max_batch_size: max_batch_size,
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max_batch_total_tokens,
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max_physical_batch_total_tokens,
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max_batch_size,
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batch_timeout: tokio::time::Duration::from_millis(5),
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},
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tokenizer,
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