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llama : add ability to cancel model loading (#4462)
* llama : Add ability to cancel model load Updated llama_progress_callback so that if it returns false, the model loading is aborted. * llama : Add test for model load cancellation * Fix bool return in llama_model_load, remove std::ignore use * Update llama.cpp Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * Fail test if model file is missing * Revert "Fail test if model file is missing" This reverts commit32ebd525bf
. * Add test-model-load-cancel to Makefile * Revert "Revert "Fail test if model file is missing"" This reverts commit2796953257
. * Simplify .gitignore for tests, clang-tidy fixes * Label all ctest tests * ci : ctest uses -L main * Attempt at writing ctest_with_model * ci : get ci/run.sh working with test-model-load-cancel * ci : restrict .github/workflows/build.yml ctest to -L main * update requirements.txt * Disable test-model-load-cancel in make * Remove venv before creation * Restructure requirements.txt Top-level now imports the specific additional requirements for each python file. Using `pip install -r requirements.txt` will fail if versions become mismatched in the per-file requirements. * Make per-python-script requirements work alone This doesn't break the main requirements.txt. * Add comment * Add convert-persimmon-to-gguf.py to new requirements.txt scheme * Add check-requirements.sh script and GitHub workflow * Remove shellcheck installation step from workflow * Add nocleanup special arg * Fix merge see: https://github.com/ggerganov/llama.cpp/pull/4462#discussion_r1434593573 * reset to upstream/master * Redo changes for cancelling model load --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
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llama.cpp
44
llama.cpp
@ -2372,7 +2372,8 @@ struct llama_model_loader {
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}
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}
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void load_all_data(struct ggml_context * ctx, llama_progress_callback progress_callback, void * progress_callback_user_data, ggml_backend_buffer_t buf_mmap, llama_mlock * lmlock) const {
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// Returns false if cancelled by progress_callback
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bool load_all_data(struct ggml_context * ctx, llama_progress_callback progress_callback, void * progress_callback_user_data, ggml_backend_buffer_t buf_mmap, llama_mlock * lmlock) const {
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size_t size_data = 0;
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for (int i = 0; i < gguf_get_n_tensors(ctx_gguf); i++) {
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@ -2404,7 +2405,9 @@ struct llama_model_loader {
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GGML_ASSERT(cur); // unused tensors should have been caught by load_data already
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if (progress_callback) {
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progress_callback((float) size_done / size_data, progress_callback_user_data);
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if (!progress_callback((float) size_done / size_data, progress_callback_user_data)) {
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return false;
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}
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}
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const size_t offs = file_offset(ggml_get_name(cur));
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@ -2466,8 +2469,11 @@ struct llama_model_loader {
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}
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if (progress_callback) {
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progress_callback(1.0f, progress_callback_user_data);
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// Even though the model is done loading, we still honor
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// cancellation since we need to free allocations.
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return progress_callback(1.0f, progress_callback_user_data);
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}
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return true;
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}
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};
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@ -3044,7 +3050,8 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
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if (vocab.linefeed_id != -1) { LLAMA_LOG_INFO( "%s: LF token = %d '%s'\n", __func__, vocab.linefeed_id, vocab.id_to_token[vocab.linefeed_id].text.c_str() ); }
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}
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static void llm_load_tensors(
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// Returns false if cancelled by progress_callback
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static bool llm_load_tensors(
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llama_model_loader & ml,
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llama_model & model,
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int n_gpu_layers,
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@ -3722,16 +3729,20 @@ static void llm_load_tensors(
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model.tensors_by_name.emplace_back(ggml_get_name(cur), cur);
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}
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ml.load_all_data(ctx, progress_callback, progress_callback_user_data, buf_mmap, use_mlock ? &model.mlock_mmap : NULL);
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if (!ml.load_all_data(ctx, progress_callback, progress_callback_user_data, buf_mmap, use_mlock ? &model.mlock_mmap : NULL)) {
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return false;
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}
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model.mapping = std::move(ml.mapping);
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// loading time will be recalculate after the first eval, so
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// we take page faults deferred by mmap() into consideration
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model.t_load_us = ggml_time_us() - model.t_start_us;
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return true;
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}
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static bool llama_model_load(const std::string & fname, llama_model & model, const llama_model_params & params) {
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// Returns 0 on success, -1 on error, and -2 on cancellation via llama_progress_callback
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static int llama_model_load(const std::string & fname, llama_model & model, const llama_model_params & params) {
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try {
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llama_model_loader ml(fname, params.use_mmap, params.kv_overrides);
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@ -3749,19 +3760,21 @@ static bool llama_model_load(const std::string & fname, llama_model & model, con
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if (params.vocab_only) {
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LLAMA_LOG_INFO("%s: vocab only - skipping tensors\n", __func__);
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return true;
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return 0;
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}
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llm_load_tensors(
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if (!llm_load_tensors(
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ml, model, params.n_gpu_layers, params.main_gpu, params.tensor_split, params.use_mlock,
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params.progress_callback, params.progress_callback_user_data
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);
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)) {
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return -2;
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}
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} catch (const std::exception & err) {
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LLAMA_LOG_ERROR("error loading model: %s\n", err.what());
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return false;
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return -1;
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}
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return true;
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return 0;
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}
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//
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@ -9141,11 +9154,18 @@ struct llama_model * llama_load_model_from_file(
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LLAMA_LOG_INFO("\n");
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}
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}
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return true;
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};
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}
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if (!llama_model_load(path_model, *model, params)) {
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int status = llama_model_load(path_model, *model, params);
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GGML_ASSERT(status <= 0);
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if (status < 0) {
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if (status == -1) {
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LLAMA_LOG_ERROR("%s: failed to load model\n", __func__);
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} else if (status == -2) {
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LLAMA_LOG_INFO("%s: cancelled model load\n", __func__);
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}
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delete model;
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return nullptr;
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}
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6
llama.h
6
llama.h
@ -127,7 +127,7 @@ extern "C" {
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bool sorted;
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} llama_token_data_array;
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typedef void (*llama_progress_callback)(float progress, void *ctx);
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typedef bool (*llama_progress_callback)(float progress, void *ctx);
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// Input data for llama_decode
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// A llama_batch object can contain input about one or many sequences
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@ -180,7 +180,9 @@ extern "C" {
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int32_t main_gpu; // the GPU that is used for scratch and small tensors
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const float * tensor_split; // how to split layers across multiple GPUs (size: LLAMA_MAX_DEVICES)
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// called with a progress value between 0 and 1, pass NULL to disable
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// Called with a progress value between 0.0 and 1.0. Pass NULL to disable.
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// If the provided progress_callback returns true, model loading continues.
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// If it returns false, model loading is immediately aborted.
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llama_progress_callback progress_callback;
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// context pointer passed to the progress callback
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