diff options
author | Cebtenzzre <cebtenzzre@gmail.com> | 2023-09-15 15:38:27 -0400 |
---|---|---|
committer | GitHub <noreply@github.com> | 2023-09-15 15:38:27 -0400 |
commit | 3aefaab9e59335ebb07d5205dbc8633efd680e58 (patch) | |
tree | 1249b50bd748a1bdcc85d010f44feda0d884fef7 /llama.cpp | |
parent | 69eb67e28275cd2d57693405f768754a7b2245ad (diff) |
check C++ code with -Wmissing-declarations (#3184)
Diffstat (limited to 'llama.cpp')
-rw-r--r-- | llama.cpp | 19 |
1 files changed, 12 insertions, 7 deletions
@@ -1,3 +1,4 @@ +#define LLAMA_API_INTERNAL #include "llama.h" #include "ggml.h" @@ -108,7 +109,7 @@ static size_t utf8_len(char src) { return lookup[highbits]; } -void replace_all(std::string & s, const std::string & search, const std::string & replace) { +static void replace_all(std::string & s, const std::string & search, const std::string & replace) { std::string result; for (size_t pos = 0; ; pos += search.length()) { auto new_pos = s.find(search, pos); @@ -1589,7 +1590,7 @@ struct llama_model_loader { // load LLaMA models // -std::string llama_model_ftype_name(enum llama_ftype ftype) { +static std::string llama_model_ftype_name(enum llama_ftype ftype) { if (ftype & LLAMA_FTYPE_GUESSED) { return llama_model_ftype_name((enum llama_ftype) (ftype & ~LLAMA_FTYPE_GUESSED)) + " (guessed)"; } @@ -4295,7 +4296,7 @@ struct llama_grammar_candidate { // Decodes a UTF-8 string which may end in an incomplete sequence. Adds a terminating 0 for use as // pointer. If an invalid sequence is encountered, returns `llama_partial_utf8.n_remain == -1`. -std::pair<std::vector<uint32_t>, llama_partial_utf8> decode_utf8( +static std::pair<std::vector<uint32_t>, llama_partial_utf8> decode_utf8( const char * src, llama_partial_utf8 partial_start) { static const int lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 2, 2, 3, 4 }; @@ -5893,7 +5894,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s } // TODO: after the GGUF PR, this likely won't work and needs to be updated -int llama_apply_lora_from_file_internal(const struct llama_model & model, const char * path_lora, const char * path_base_model, int n_threads) { +static int llama_apply_lora_from_file_internal( + const struct llama_model & model, const char * path_lora, const char * path_base_model, int n_threads +) { LLAMA_LOG_INFO("%s: applying lora adapter from '%s' - please wait ...\n", __func__, path_lora); const int64_t t_start_lora_us = ggml_time_us(); @@ -6440,7 +6443,7 @@ struct llama_context * llama_new_context_with_model( return ctx; } -struct llama_context * llama_init_from_file( +static struct llama_context * llama_init_from_file( const char * path_model, struct llama_context_params params) { struct llama_model * model = llama_load_model_from_file(path_model, params); @@ -6645,7 +6648,7 @@ struct llama_data_file_context : llama_data_context { * llama_copy_state_data(ctx, &data_ctx); * */ -void llama_copy_state_data_internal(struct llama_context * ctx, llama_data_context * data_ctx) { +static void llama_copy_state_data_internal(struct llama_context * ctx, llama_data_context * data_ctx) { // copy rng { std::stringstream rng_ss; @@ -7183,7 +7186,9 @@ void llama_dump_timing_info_yaml(FILE * stream, const llama_context * ctx) { } // For internal test use -const std::vector<std::pair<std::string, struct ggml_tensor *>>& llama_internal_get_tensor_map(struct llama_context * ctx) { +const std::vector<std::pair<std::string, struct ggml_tensor *>> & llama_internal_get_tensor_map( + struct llama_context * ctx +) { return ctx->model.tensors_by_name; } |