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llama: update to commit 71e90e88 (#10192)
This commit is contained in:
75
llama/llama.cpp/common/common.h
vendored
75
llama/llama.cpp/common/common.h
vendored
@@ -110,9 +110,17 @@ enum common_conversation_mode {
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COMMON_CONVERSATION_MODE_AUTO = 2,
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};
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enum common_grammar_trigger_type {
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COMMON_GRAMMAR_TRIGGER_TYPE_TOKEN,
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COMMON_GRAMMAR_TRIGGER_TYPE_WORD,
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COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN,
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COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN_START,
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};
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struct common_grammar_trigger {
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std::string word;
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bool at_start;
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common_grammar_trigger_type type;
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std::string value;
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llama_token token = LLAMA_TOKEN_NULL;
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};
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// sampling parameters
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@@ -163,8 +171,7 @@ struct common_params_sampling {
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std::string grammar; // optional BNF-like grammar to constrain sampling
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bool grammar_lazy = false;
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std::vector<common_grammar_trigger> grammar_trigger_words; // optional trigger words to trigger lazy grammar
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std::vector<llama_token> grammar_trigger_tokens; // optional trigger tokens to trigger lazy grammar and print trigger special tokens.
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std::vector<common_grammar_trigger> grammar_triggers; // optional triggers (for lazy grammars)
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std::set<llama_token> preserved_tokens;
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std::vector<llama_logit_bias> logit_bias; // logit biases to apply
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@@ -173,6 +180,13 @@ struct common_params_sampling {
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std::string print() const;
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};
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struct common_params_model {
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std::string path = ""; // model local path // NOLINT
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std::string url = ""; // model url to download // NOLINT
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std::string hf_repo = ""; // HF repo // NOLINT
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std::string hf_file = ""; // HF file // NOLINT
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};
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struct common_params_speculative {
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std::vector<ggml_backend_dev_t> devices; // devices to use for offloading
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@@ -186,19 +200,13 @@ struct common_params_speculative {
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struct cpu_params cpuparams;
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struct cpu_params cpuparams_batch;
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std::string hf_repo = ""; // HF repo // NOLINT
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std::string hf_file = ""; // HF file // NOLINT
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std::string model = ""; // draft model for speculative decoding // NOLINT
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std::string model_url = ""; // model url to download // NOLINT
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struct common_params_model model;
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};
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struct common_params_vocoder {
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std::string hf_repo = ""; // HF repo // NOLINT
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std::string hf_file = ""; // HF file // NOLINT
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struct common_params_model model;
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std::string model = ""; // model path // NOLINT
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std::string model_url = ""; // model url to download // NOLINT
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std::string speaker_file = ""; // speaker file path // NOLINT
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bool use_guide_tokens = false; // enable guide tokens to improve TTS accuracy // NOLINT
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};
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@@ -254,13 +262,12 @@ struct common_params {
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struct common_params_speculative speculative;
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struct common_params_vocoder vocoder;
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std::string model = ""; // model path // NOLINT
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struct common_params_model model;
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std::string model_alias = ""; // model alias // NOLINT
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std::string model_url = ""; // model url to download // NOLINT
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std::string hf_token = ""; // HF token // NOLINT
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std::string hf_repo = ""; // HF repo // NOLINT
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std::string hf_file = ""; // HF file // NOLINT
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std::string prompt = ""; // NOLINT
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std::string system_prompt = ""; // NOLINT
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std::string prompt_file = ""; // store the external prompt file name // NOLINT
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std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state // NOLINT
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std::string input_prefix = ""; // string to prefix user inputs with // NOLINT
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@@ -272,6 +279,7 @@ struct common_params {
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std::vector<std::string> in_files; // all input files
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std::vector<std::string> antiprompt; // strings upon which more user input is prompted (a.k.a. reverse prompts)
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std::vector<llama_model_kv_override> kv_overrides;
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std::vector<llama_model_tensor_buft_override> tensor_buft_overrides;
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bool lora_init_without_apply = false; // only load lora to memory, but do not apply it to ctx (user can manually apply lora later using llama_adapter_lora_apply)
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std::vector<common_adapter_lora_info> lora_adapters; // lora adapter path with user defined scale
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@@ -325,13 +333,15 @@ struct common_params {
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bool warmup = true; // warmup run
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bool check_tensors = false; // validate tensor data
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bool single_turn = false; // single turn chat conversation
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ggml_type cache_type_k = GGML_TYPE_F16; // KV cache data type for the K
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ggml_type cache_type_v = GGML_TYPE_F16; // KV cache data type for the V
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common_conversation_mode conversation_mode = COMMON_CONVERSATION_MODE_AUTO;
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// multimodal models (see examples/llava)
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std::string mmproj = ""; // path to multimodal projector // NOLINT
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struct common_params_model mmproj;
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std::vector<std::string> image; // path to image file(s)
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// embedding
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@@ -391,8 +401,6 @@ struct common_params {
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int32_t i_pos = -1; // position of the passkey in the junk text
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// imatrix params
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std::string out_file = "imatrix.dat"; // save the resulting imatrix to this file
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int32_t n_out_freq = 10; // output the imatrix every n_out_freq iterations
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int32_t n_save_freq = 0; // save the imatrix every n_save_freq iterations
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int32_t i_chunk = 0; // start processing from this chunk
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@@ -404,16 +412,16 @@ struct common_params {
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int n_pca_batch = 100;
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int n_pca_iterations = 1000;
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dimre_method cvector_dimre_method = DIMRE_METHOD_PCA;
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std::string cvector_outfile = "control_vector.gguf";
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std::string cvector_positive_file = "examples/cvector-generator/positive.txt";
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std::string cvector_negative_file = "examples/cvector-generator/negative.txt";
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bool spm_infill = false; // suffix/prefix/middle pattern for infill
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std::string lora_outfile = "ggml-lora-merged-f16.gguf";
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// batched-bench params
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bool batched_bench_output_jsonl = false;
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// common params
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std::string out_file; // output filename for all example programs
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};
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// call once at the start of a program if it uses libcommon
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@@ -453,6 +461,8 @@ std::string string_repeat(const std::string & str, size_t n);
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void string_replace_all(std::string & s, const std::string & search, const std::string & replace);
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std::string regex_escape(const std::string & s);
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template<class T>
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static std::vector<T> string_split(const std::string & str, char delim) {
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static_assert(!std::is_same<T, std::string>::value, "Please use the specialized version for std::string");
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@@ -530,26 +540,11 @@ struct llama_model_params common_model_params_to_llama ( common_params
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struct llama_context_params common_context_params_to_llama(const common_params & params);
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struct ggml_threadpool_params ggml_threadpool_params_from_cpu_params(const cpu_params & params);
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struct llama_model * common_load_model_from_url(
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const std::string & model_url,
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const std::string & local_path,
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const std::string & hf_token,
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const struct llama_model_params & params);
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struct llama_model * common_load_model_from_hf(
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const std::string & repo,
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const std::string & remote_path,
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const std::string & local_path,
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const std::string & hf_token,
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const struct llama_model_params & params);
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std::pair<std::string, std::string> common_get_hf_file(
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const std::string & hf_repo_with_tag,
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const std::string & hf_token);
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// clear LoRA adapters from context, then apply new list of adapters
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void common_set_adapter_lora(struct llama_context * ctx, std::vector<common_adapter_lora_info> & lora);
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std::string get_model_endpoint();
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//
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// Batch utils
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//
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