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https://github.com/ggerganov/llama.cpp.git
synced 2024-12-26 14:20:31 +01:00
minor : spacing
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2605c139a6
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@ -101,7 +101,7 @@ struct TransformerWeights {
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std::vector<float> wcls;
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};
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static void alloc_weights(TransformerWeights* w, const Config* p, bool shared_weights) {
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static void alloc_weights(TransformerWeights * w, const Config * p, bool shared_weights) {
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const int n_multiqueries = p->n_kv_heads <= 0 || p->n_kv_heads >= p->n_heads ? 1 : p->n_heads / p->n_kv_heads;
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try {
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w->token_embedding_table.resize(p->vocab_size * p->dim);
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@ -144,12 +144,12 @@ static void alloc_weights(TransformerWeights* w, const Config* p, bool shared_we
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LOG("%s: Allocating [%d] x [%d] = [%d] float space for w->wcls\n",__func__,p->vocab_size , p->dim, p->vocab_size * p->dim);
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}
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}
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catch (std::length_error&) {
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catch (std::length_error &) {
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die("Invalid configuration. Failed to allocate memory for weights");
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}
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}
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static int checkpoint_init_weights(TransformerWeights *w, const Config* p, FILE* f, bool shared_weights) {
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static int checkpoint_init_weights(TransformerWeights * w, const Config * p, FILE * f, bool shared_weights) {
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if (fread(w->token_embedding_table.data(), sizeof(float), w->token_embedding_table.size(), f) != w->token_embedding_table.size()) return 1;
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if (fread(w->rms_att_weight.data(), sizeof(float), w->rms_att_weight.size(), f) != w->rms_att_weight.size()) return 1;
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if (fread(w->wq.data(), sizeof(float), w->wq.size(), f) != w->wq.size()) return 1;
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@ -173,7 +173,7 @@ static int checkpoint_init_weights(TransformerWeights *w, const Config* p, FILE*
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fseek(f, 0, SEEK_END);
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auto end = ftell(f);
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if (curr != end) {
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LOG("%s: Error: failed to read the checkpoint file to the end (curr = %ld, end = %ld)\n",__func__, curr, end);
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LOG("%s: Error: failed to read the checkpoint file to the end (curr = %ld, end = %ld)\n", __func__, curr, end);
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return 1;
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}
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@ -225,6 +225,7 @@ struct my_llama_hparams {
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uint32_t n_head_kv = 32;
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uint32_t n_layer = 32;
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uint32_t n_rot = 64;
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bool operator!=(const my_llama_hparams& other) const {
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return memcmp(this, &other, sizeof(my_llama_hparams));
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}
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@ -523,9 +524,9 @@ 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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static void load_vocab(const char *filename, const Config *config, struct llama_vocab *vocab) {
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static void load_vocab(const char * filename, const Config * config, struct llama_vocab * vocab) {
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if (is_ggml_file(filename)) {
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LOG("%s: Loading vocabulary from gguf file %s\n",__func__,filename);
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LOG("%s: Loading vocabulary from gguf file %s\n", __func__, filename);
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struct ggml_context * ctx_data = NULL;
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struct gguf_init_params params = {
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@ -573,7 +574,7 @@ static void load_vocab(const char *filename, const Config *config, struct llama_
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gguf_free(ctx);
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} else {
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// assume llama2.c vocabulary
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LOG("%s: Assuming llama2.c vocabulary since %s is not a gguf file\n",__func__,filename);
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LOG("%s: Assuming llama2.c vocabulary since %s is not a gguf file\n", __func__, filename);
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llama_file file(filename, "rb");
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if (!file.fp) {
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die_fmt("%s: %s", strerror(errno), filename);
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@ -643,6 +644,7 @@ static void save_as_llama_model(
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// for rms-att-weight
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int row_length = model->hparams.n_embd;
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int n_ff = model->hparams.n_ff;
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const uint32_t n_multiqueries = model->hparams.n_head_kv <= 0 || model->hparams.n_head_kv >= model->hparams.n_head ? 1 : model->hparams.n_head / model->hparams.n_head_kv;
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for (uint32_t i = 0; i < model->hparams.n_layer; ++i){
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@ -877,17 +879,26 @@ int main(int argc, char ** argv) {
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Config config;
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TransformerWeights weights = {};
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{
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LOG("%s: Loading llama2c model from %s\n",__func__,params.fn_llama2c_model);
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LOG("%s: Loading llama2c model from %s\n", __func__, params.fn_llama2c_model);
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FILE *file = fopen(params.fn_llama2c_model, "r");
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if (!file) { LOG("%s: Unable to open the checkpoint file %s!\n",__func__,params.fn_llama2c_model); return 1; }
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if (!file) {
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LOG("%s: Unable to open the checkpoint file %s!\n", __func__, params.fn_llama2c_model);
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return 1;
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}
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// read in the config header
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if (fread(&config, sizeof(Config), 1, file) != 1) { LOG("%s: Unable to read llama2c config from %s!\n",__func__,params.fn_llama2c_model); return 1; }
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if (fread(&config, sizeof(Config), 1, file) != 1) {
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LOG("%s: Unable to read llama2c config from %s!\n",__func__,params.fn_llama2c_model);
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return 1;
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}
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auto shared_weights = config.vocab_size > 0;
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config.vocab_size = abs(config.vocab_size);
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// read in the Transformer weights
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alloc_weights(&weights, &config, shared_weights);
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if(checkpoint_init_weights(&weights, &config, file, shared_weights)) { LOG("%s: Unable to initialize transformer weights from %s!",__func__,params.fn_llama2c_model); return 1; }
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if (checkpoint_init_weights(&weights, &config, file, shared_weights)) {
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LOG("%s: Unable to initialize transformer weights from %s!",__func__,params.fn_llama2c_model);
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return 1;
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}
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fclose(file);
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}
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@ -904,7 +915,9 @@ int main(int argc, char ** argv) {
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model.hparams.n_head_kv = config.n_kv_heads;
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model.hparams.n_layer = config.n_layers; //params.n_layer;
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model.hparams.n_rot = std::min((uint32_t)params.n_rotmax, model.hparams.n_embd / model.hparams.n_head);
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print_params(&model.hparams);
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struct ggml_init_params lcparams;
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lcparams.mem_size = 1024ll*1024ll*1024ll*((size_t) params.mem_model_gb);
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lcparams.mem_buffer = NULL;
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@ -916,7 +929,7 @@ int main(int argc, char ** argv) {
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model.name = basename(params.fn_llama2c_model);
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save_as_llama_model(&vocab, &model, &weights, params.fn_llama2c_output_model);
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LOG("%s: Saving llama.c model file %s in ggml format at %s\n",__func__, params.fn_llama2c_model, params.fn_llama2c_output_model);
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LOG("%s: Saving llama.c model file %s in ggml format at %s\n", __func__, params.fn_llama2c_model, params.fn_llama2c_output_model);
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ggml_free(model.ctx);
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return 0;
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