vbatts/llama.cpp
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common : use common_ prefix for common library functions (#9805)

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* common : use common_ prefix for common library functions

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Diego Devesa 2024-10-10 22:57:42 +02:00 • committed by GitHub
parent 0e9f760eb1
commit 7eee341bee
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GPG key ID: B5690EEEBB952194
45 changed files with 1284 additions and 1284 deletions
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28
examples/batched/batched.cpp
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@ -15,16 +15,16 @@ static void print_usage(int, char ** argv) {
}
int main(int argc, char ** argv) {
gpt_params params;
common_params params;
params.prompt = "Hello my name is";
params.n_predict = 32;
if (!gpt_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON, print_usage)) {
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON, print_usage)) {
return 1;
}
gpt_init();
common_init();
// number of parallel batches
int n_parallel = params.n_parallel;
@ -39,7 +39,7 @@ int main(int argc, char ** argv) {
// initialize the model
llama_model_params model_params = llama_model_params_from_gpt_params(params);
llama_model_params model_params = common_model_params_to_llama(params);
llama_model * model = llama_load_model_from_file(params.model.c_str(), model_params);
@ -51,13 +51,13 @@ int main(int argc, char ** argv) {
// tokenize the prompt
std::vector<llama_token> tokens_list;
tokens_list = ::llama_tokenize(model, params.prompt, true);
tokens_list = common_tokenize(model, params.prompt, true);
const int n_kv_req = tokens_list.size() + (n_predict - tokens_list.size())*n_parallel;
// initialize the context
llama_context_params ctx_params = llama_context_params_from_gpt_params(params);
llama_context_params ctx_params = common_context_params_to_llama(params);
ctx_params.n_ctx = n_kv_req;
ctx_params.n_batch = std::max(n_predict, n_parallel);
@ -94,7 +94,7 @@ int main(int argc, char ** argv) {
LOG("\n");
for (auto id : tokens_list) {
LOG("%s", llama_token_to_piece(ctx, id).c_str());
LOG("%s", common_token_to_piece(ctx, id).c_str());
}
// create a llama_batch
@ -108,7 +108,7 @@ int main(int argc, char ** argv) {
// evaluate the initial prompt
for (size_t i = 0; i < tokens_list.size(); ++i) {
llama_batch_add(batch, tokens_list[i], i, seq_ids, false);
common_batch_add(batch, tokens_list[i], i, seq_ids, false);
}
GGML_ASSERT(batch.n_tokens == (int) tokens_list.size());
@ -123,8 +123,8 @@ int main(int argc, char ** argv) {
decoder_start_token_id = llama_token_bos(model);
}
llama_batch_clear(batch);
llama_batch_add(batch, decoder_start_token_id, 0, seq_ids, false);
common_batch_clear(batch);
common_batch_add(batch, decoder_start_token_id, 0, seq_ids, false);
}
// llama_decode will output logits only for the last token of the prompt
@ -161,7 +161,7 @@ int main(int argc, char ** argv) {
while (n_cur <= n_predict) {
// prepare the next batch
llama_batch_clear(batch);
common_batch_clear(batch);
// sample the next token for each parallel sequence / stream
for (int32_t i = 0; i < n_parallel; ++i) {
@ -185,15 +185,15 @@ int main(int argc, char ** argv) {
// if there is only one stream, we print immediately to stdout
if (n_parallel == 1) {
LOG("%s", llama_token_to_piece(ctx, new_token_id).c_str());
LOG("%s", common_token_to_piece(ctx, new_token_id).c_str());
}
streams[i] += llama_token_to_piece(ctx, new_token_id);
streams[i] += common_token_to_piece(ctx, new_token_id);
i_batch[i] = batch.n_tokens;
// push this new token for next evaluation
llama_batch_add(batch, new_token_id, n_cur, { i }, true);
common_batch_add(batch, new_token_id, n_cur, { i }, true);
n_decode += 1;
}