check C++ code with -Wmissing-declarations (#3184)
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Cebtenzzre
GitHub
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69eb67e282
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3aefaab9e5
22 changed files with 247 additions and 243 deletions
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@ -115,7 +115,7 @@ struct TransformerWeights {
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}
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};
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void malloc_weights(TransformerWeights* w, Config* p, bool shared_weights) {
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static void malloc_weights(TransformerWeights* w, Config* p, bool shared_weights) {
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// we calloc instead of malloc to keep valgrind happy
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w->token_embedding_table = new float[p->vocab_size * p->dim]();
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printf("[%s:AK] Allocating [%d] x [%d] = [%d] float space for w->token_embedding_table\n",__func__,p->vocab_size , p->dim, p->vocab_size * p->dim);
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@ -158,7 +158,7 @@ void malloc_weights(TransformerWeights* w, Config* p, bool shared_weights) {
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}
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}
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int checkpoint_init_weights(TransformerWeights *w, Config* p, FILE* f, bool shared_weights) {
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static int checkpoint_init_weights(TransformerWeights *w, Config* p, FILE* f, bool shared_weights) {
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if (fread(w->token_embedding_table, sizeof(float), p->vocab_size * p->dim, f) != static_cast<size_t>(p->vocab_size * p->dim)) return 1;
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if (fread(w->rms_att_weight, sizeof(float), p->n_layers * p->dim, f) != static_cast<size_t>(p->n_layers * p->dim)) return 1;
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if (fread(w->wq, sizeof(float), p->n_layers * p->dim * p->dim, f) != static_cast<size_t>(p->n_layers * p->dim * p->dim)) return 1;
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@ -189,7 +189,7 @@ int checkpoint_init_weights(TransformerWeights *w, Config* p, FILE* f, bool shar
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return 0;
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}
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void print_sample_weights(TransformerWeights *w){
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static void print_sample_weights(TransformerWeights *w){
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printf("----- Quick print of first of the weight vales of all the variables\n");
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printf("%f\n", w->token_embedding_table[0]);
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printf("%f\n", w->rms_att_weight[0]);
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@ -324,7 +324,7 @@ struct train_params {
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int mem_compute1_gb;
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};
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void print_params(struct my_llama_hparams * params) {
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static void print_params(struct my_llama_hparams * params) {
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printf("%s: n_vocab: %d\n", __func__, params->n_vocab);
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printf("%s: n_ctx: %d\n", __func__, params->n_ctx);
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printf("%s: n_embd: %d\n", __func__, params->n_embd);
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@ -335,7 +335,7 @@ void print_params(struct my_llama_hparams * params) {
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printf("%s: n_rot: %d\n", __func__, params->n_rot);
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}
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void init_model(struct my_llama_model * model) {
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static void init_model(struct my_llama_model * model) {
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const auto & hparams = model->hparams;
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const uint32_t n_embd = hparams.n_embd;
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@ -408,17 +408,17 @@ void init_model(struct my_llama_model * model) {
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}
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}
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float get_f32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
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static float get_f32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
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float * ptr = (float *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
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return *ptr;
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}
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int32_t get_i32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
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static int32_t get_i32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) {
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int32_t * ptr = (int32_t *) ((char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1]);
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return *ptr;
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}
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void print_row(struct ggml_tensor * probs, int i) {
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static void print_row(struct ggml_tensor * probs, int i) {
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for (int k = 0; k < probs->ne[0]; ++k) {
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float p = get_f32_2d(probs, k, i);
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printf(" %f", p);
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@ -426,7 +426,7 @@ void print_row(struct ggml_tensor * probs, int i) {
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printf("\n");
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}
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void print_matrix(struct ggml_tensor * probs) {
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static void print_matrix(struct ggml_tensor * probs) {
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assert(probs->n_dims == 2);
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for (int i = 0; i < probs->ne[1]; ++i) {
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for (int k = 0; k < probs->ne[0]; ++k) {
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@ -531,7 +531,7 @@ struct llama_file {
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}
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};
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bool is_ggml_file(const char *filename) {
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static bool is_ggml_file(const char * filename) {
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llama_file file(filename, "rb");
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if (file.size < 4) {
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return false;
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@ -540,7 +540,7 @@ bool is_ggml_file(const char *filename) {
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return magic == GGUF_MAGIC;
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}
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static std::string llama_escape_whitespaces(const std::string& text) {
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static std::string llama_escape_whitespaces(const std::string & text) {
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std::ostringstream out;
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for (char c : text) {
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if (c == ' ') out << "\xe2\x96\x81";
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@ -549,7 +549,7 @@ static std::string llama_escape_whitespaces(const std::string& text) {
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return out.str();
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}
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void load_vocab(const char *filename, Config *config, struct llama_vocab *vocab) {
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static void load_vocab(const char *filename, Config *config, struct llama_vocab *vocab) {
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if (is_ggml_file(filename)) {
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struct ggml_context * ctx_data = NULL;
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@ -637,7 +637,7 @@ void load_vocab(const char *filename, Config *config, struct llama_vocab *vocab)
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}
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}
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void convert_weights_ak_to_gg(struct ggml_tensor * gg_weights, const float * karpathy_weights) {
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static void convert_weights_ak_to_gg(struct ggml_tensor * gg_weights, const float * karpathy_weights) {
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int ct;
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switch (gg_weights->n_dims){
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case 1:
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@ -673,7 +673,9 @@ void convert_weights_ak_to_gg(struct ggml_tensor * gg_weights, const float * kar
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}
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}
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void save_as_llama_model(struct llama_vocab * vocab, struct my_llama_model * model, TransformerWeights* w, const char * filename) {
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static void save_as_llama_model(
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struct llama_vocab * vocab, struct my_llama_model * model, TransformerWeights* w, const char * filename
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) {
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// convert AK weights into GG weights one by one.
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// w->token_embedding_table -> model->tok_embeddings
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// float* -> struct ggml_tensor
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@ -785,7 +787,7 @@ void save_as_llama_model(struct llama_vocab * vocab, struct my_llama_model * mod
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gguf_free(ctx);
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}
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struct train_params get_default_train_params() {
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static struct train_params get_default_train_params() {
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struct train_params params;
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params.fn_vocab_model = "models/7B/ggml-model-f16.gguf";
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params.fn_llama2c_output_model = "ak_llama_model.bin";
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@ -835,7 +837,7 @@ struct train_params get_default_train_params() {
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return params;
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}
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void print_usage(int /*argc*/, char ** argv, const struct train_params * params) {
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static void print_usage(int /*argc*/, char ** argv, const struct train_params * params) {
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fprintf(stderr, "usage: %s [options]\n", argv[0]);
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fprintf(stderr, "\n");
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fprintf(stderr, "options:\n");
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@ -846,7 +848,7 @@ void print_usage(int /*argc*/, char ** argv, const struct train_params * params)
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fprintf(stderr, "\n");
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}
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bool params_parse(int argc, char ** argv, struct train_params * params) {
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static bool params_parse(int argc, char ** argv, struct train_params * params) {
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bool invalid_param = false;
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bool reqd_param_found = false;
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std::string arg;
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@ -901,7 +903,7 @@ bool params_parse(int argc, char ** argv, struct train_params * params) {
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return true;
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}
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std::string basename(const std::string &path) {
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static std::string basename(const std::string &path) {
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size_t pos = path.find_last_of("/\\");
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if (pos == std::string::npos) {
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return path;
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