vbatts/llama.cpp
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refactor vocab loading into its own method

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Johannes Rudolph 2023-08-10 16:17:26 +02:00
parent aab15de466
commit d2b95e7e70
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1 changed files with 28 additions and 25 deletions
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53
examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp
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@ -491,6 +491,32 @@ void write_tensor(struct llama_file * file, struct ggml_tensor * tensor) {
file->write_raw(tensor->data, ggml_nbytes(tensor));
}
void load_vocab(const char *filename, struct llama_vocab *vocab) {
struct llama_context_params llama_params = llama_context_default_params();
llama_params.vocab_only = true;
struct llama_model * lmodel = llama_load_model_from_file(filename, llama_params);
struct llama_context * lctx = llama_new_context_with_model(lmodel, llama_params);
std::vector<const char *> strings;
std::vector<float> scores;
int n_vocab = llama_n_vocab(lctx);
strings.resize(n_vocab, NULL);
scores.resize(n_vocab, 0);
n_vocab = llama_get_vocab(lctx, strings.data(), scores.data(), n_vocab);
GGML_ASSERT(n_vocab == llama_n_vocab(lctx));
vocab->id_to_token.resize(n_vocab);
for (int i=0; i<n_vocab; ++i) {
std::string tok = std::string(strings[i]);
float score = scores[i];
vocab->id_to_token[i].tok = tok;
vocab->id_to_token[i].score = score;
vocab->token_to_id.emplace(tok, i);
}
llama_free(lctx);
llama_free_model(lmodel);
}
void stuff_karpathy_weights_into_gg(struct ggml_tensor * gg_weights, float * karpathy_weights){
int ct;
switch (gg_weights->n_dims){
@ -737,30 +763,9 @@ int main(int argc, char ** argv) {
fclose(file);
}
struct llama_context_params llama_params = llama_context_default_params();
llama_params.vocab_only = true;
struct llama_model * lmodel = llama_load_model_from_file(params.fn_vocab_model, llama_params);
struct llama_context * lctx = llama_new_context_with_model(lmodel, llama_params);
struct llama_vocab vocab;
{
std::vector<const char *> strings;
std::vector<float> scores;
int n_vocab = llama_n_vocab(lctx);
strings.resize(n_vocab, NULL);
scores.resize(n_vocab, 0);
n_vocab = llama_get_vocab(lctx, strings.data(), scores.data(), n_vocab);
GGML_ASSERT(n_vocab == llama_n_vocab(lctx));
vocab.id_to_token.resize(n_vocab);
for (int i=0; i<n_vocab; ++i) {
std::string tok = std::string(strings[i]);
float score = scores[i];
vocab.id_to_token[i].tok = tok;
vocab.id_to_token[i].score = score;
vocab.token_to_id.emplace(tok, i);
}
}
load_vocab(params.fn_vocab_model, &vocab);
struct my_llama_model model;
model.hparams.n_vocab = config.vocab_size; //llama_n_vocab(lctx);
model.hparams.n_ctx = params.n_ctx;
@ -782,8 +787,6 @@ int main(int argc, char ** argv) {
printf("Saving llama.c model file %s in ggml format at %s\n", params.fn_llama2c_model, params.fn_llama2c_output_model);
llama_free(lctx);
llama_free_model(lmodel);
ggml_free(model.ctx);
free_weights(&weights);
return 0;