From dc6435e3a58decb93d6d06c6d03052be4eb57411 Mon Sep 17 00:00:00 2001 From: Morgan Funtowicz Date: Thu, 28 Nov 2024 23:57:08 +0100 Subject: [PATCH] feat(backend): create llama_context_params with default factory --- backends/llamacpp/csrc/ffi.hpp | 11 ++++++++++- backends/llamacpp/offline/main.cpp | 25 +++++++++++++++++++------ 2 files changed, 29 insertions(+), 7 deletions(-) diff --git a/backends/llamacpp/csrc/ffi.hpp b/backends/llamacpp/csrc/ffi.hpp index 36455263..99679fdb 100644 --- a/backends/llamacpp/csrc/ffi.hpp +++ b/backends/llamacpp/csrc/ffi.hpp @@ -43,6 +43,15 @@ namespace huggingface::tgi::backends::llamacpp { return std::shared_ptr(model, llama_model_deleter); }; + auto get_llama_context_params = [](size_t num_threads) { + auto params = llama_context_default_params(); + params.n_threads = num_threads; + params.n_threads_batch = num_threads; + params.flash_attn = true; + params.no_perf = false; + return params; + }; + /** * llama.cpp backend specific exception mapped from `backend_exception_t` to throw at the FFI level and * allow automatic implementation of Result<_, Exception> from C++ to Rust @@ -64,7 +73,7 @@ namespace huggingface::tgi::backends::llamacpp { * @param num_threads The number of threads the worker is allowed to spawn accross for its threadpool */ explicit llama_cpp_worker_frontend_t(llama_model *model, int32_t num_threads): - model_{ make_shared_llama_model(model) }, worker_(model_, {.n_ubatch = 1, .n_threads = num_threads, .no_perf = true}) {} + model_{ make_shared_llama_model(model) }, worker_(model_, get_llama_context_params(num_threads)) {} /** * Generate a new set of tokens from the provided `input_tokens`, streaming each individual token generated diff --git a/backends/llamacpp/offline/main.cpp b/backends/llamacpp/offline/main.cpp index e5c70e77..fad97b3a 100644 --- a/backends/llamacpp/offline/main.cpp +++ b/backends/llamacpp/offline/main.cpp @@ -27,24 +27,37 @@ int main(int argc, char **argv) { llama_model_deleter ); - auto prompt = "My name is Morgan"; - auto tokens = std::vector(16); - const auto nb_tokens = llama_tokenize(model.get(), prompt, sizeof(prompt), tokens.data(), tokens.size(), true, + auto prompt = std::string("My name is Morgan"); + auto tokens = std::vector(128); + const auto nb_tokens = llama_tokenize(model.get(), prompt.c_str(), prompt.size(), tokens.data(), tokens.size(), + true, false); tokens.resize(nb_tokens); - auto backend = worker_t(std::move(model), {.n_batch = 1, .n_threads = 4}); + llama_numa_init(ggml_numa_strategy::GGML_NUMA_STRATEGY_DISTRIBUTE); + auto backend = worker_t(model, llama_context_default_params()); fmt::println("Tokenized: {}", tokens); // generate auto generated_tokens = std::vector(32); const auto n_generated_tokens = backend.generate( - {{.max_new_tokens = 32}, {.top_k = 40}, tokens}, + {{.max_new_tokens = 32}, {.top_k = 40, .top_p = 0.95, .temperature = 0.8}, + tokens}, [&generated_tokens](llama_token new_token_id, float_t logit, bool is_eos, size_t step) -> bool { generated_tokens.emplace(generated_tokens.begin() + (step - 1), new_token_id); return false; } ); generated_tokens.resize(n_generated_tokens.value()); - fmt::println("Generated {} tokens", generated_tokens); + + std::string decoded = std::string(256, 'a'); + const size_t length = llama_detokenize(model.get(), + generated_tokens.data(), + generated_tokens.size(), + decoded.data(), + decoded.size(), + false, false); + decoded.resize(std::min(length, decoded.size())); + fmt::println("Generated tokens: {}", generated_tokens); + fmt::println("Generated text: {}", decoded); }