vbatts/llama.cpp
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only activate pp_threads for main for now

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This commit is contained in:
netrunnereve 2023-08-06 00:22:14 -04:00
parent 590feeac1d
commit 215e2f21d0
7 changed files with 11 additions and 11 deletions
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4
examples/embd-input/embd-input-lib.cpp
View file

@ -83,7 +83,7 @@ bool eval_float(void * model, float * input, int N){
if (n_eval > n_batch) {
n_eval = n_batch;
}
if (llama_eval_embd(ctx, (input+i*n_emb), n_eval, n_past, params.n_threads, params.pp_threads)) {
if (llama_eval_embd(ctx, (input+i*n_emb), n_eval, n_past, params.n_threads, params.n_threads)) {
fprintf(stderr, "%s : failed to eval\n", __func__);
return false;
}
@ -104,7 +104,7 @@ bool eval_tokens(void * model, std::vector<llama_token> tokens) {
if (n_eval > params.n_batch) {
n_eval = params.n_batch;
}
if (llama_eval(ctx, &tokens[i], n_eval, n_past, params.n_threads, params.pp_threads)) {
if (llama_eval(ctx, &tokens[i], n_eval, n_past, params.n_threads, params.n_threads)) {
fprintf(stderr, "%s : failed to eval\n", __func__);
return false;
}

2
examples/embedding/embedding.cpp
View file

@ -74,7 +74,7 @@ int main(int argc, char ** argv) {
if (params.embedding){
if (embd_inp.size() > 0) {
if (llama_eval(ctx, embd_inp.data(), embd_inp.size(), n_past, params.n_threads, params.pp_threads)) {
if (llama_eval(ctx, embd_inp.data(), embd_inp.size(), n_past, params.n_threads, params.n_threads)) {
fprintf(stderr, "%s : failed to eval\n", __func__);
return 1;
}

4
examples/perplexity/perplexity.cpp
View file

@ -66,7 +66,7 @@ void perplexity(llama_context * ctx, const gpt_params & params) {
tokens[batch_start] = llama_token_bos();
}
if (llama_eval(ctx, tokens.data() + batch_start, batch_size, j * n_batch, params.n_threads, params.pp_threads)) {
if (llama_eval(ctx, tokens.data() + batch_start, batch_size, j * n_batch, params.n_threads, params.n_threads)) {
fprintf(stderr, "%s : failed to eval\n", __func__);
return;
}
@ -233,7 +233,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
}
// Evaluate the query
if (llama_eval(ctx, query_embd.data(), query_embd.size(), 0, params.n_threads, params.pp_threads)) {
if (llama_eval(ctx, query_embd.data(), query_embd.size(), 0, params.n_threads, params.n_threads)) {
fprintf(stderr, "%s : failed to eval\n", __func__);
return;
}

6
examples/save-load-state/save-load-state.cpp
View file

@ -56,7 +56,7 @@ int main(int argc, char ** argv) {
}
// evaluate prompt
llama_eval(ctx, tokens.data(), n_prompt_tokens, n_past, params.n_threads, params.pp_threads);
llama_eval(ctx, tokens.data(), n_prompt_tokens, n_past, params.n_threads, params.n_threads);
last_n_tokens_data.insert(last_n_tokens_data.end(), tokens.data(), tokens.data() + n_prompt_tokens);
n_past += n_prompt_tokens;
@ -93,7 +93,7 @@ int main(int argc, char ** argv) {
last_n_tokens_data.push_back(next_token);
printf("%s", next_token_str);
if (llama_eval(ctx, &next_token, 1, n_past, params.n_threads, params.pp_threads)) {
if (llama_eval(ctx, &next_token, 1, n_past, params.n_threads, params.n_threads)) {
fprintf(stderr, "\n%s : failed to evaluate\n", __func__);
llama_free(ctx);
llama_free_model(model);
@ -153,7 +153,7 @@ int main(int argc, char ** argv) {
last_n_tokens_data.push_back(next_token);
printf("%s", next_token_str);
if (llama_eval(ctx2, &next_token, 1, n_past, params.n_threads, params.pp_threads)) {
if (llama_eval(ctx2, &next_token, 1, n_past, params.n_threads, params.n_threads)) {
fprintf(stderr, "\n%s : failed to evaluate\n", __func__);
llama_free(ctx2);
llama_free_model(model);

2
examples/server/server.cpp
View file

@ -350,7 +350,7 @@ struct llama_server_context
{
n_eval = params.n_batch;
}
if (llama_eval(ctx, &embd[n_past], n_eval, n_past, params.n_threads, params.pp_threads))
if (llama_eval(ctx, &embd[n_past], n_eval, n_past, params.n_threads, params.n_threads))
{
LOG_ERROR("failed to eval", {
{"n_eval", n_eval},

2
examples/simple/simple.cpp
View file

@ -123,7 +123,7 @@ int main(int argc, char ** argv)
// Evaluate the tokens :
//---------------------------------
if ( llama_eval( ctx , tokens_list.data() , int(tokens_list.size()) , llama_get_kv_cache_token_count( ctx ) , params.n_threads , params.pp_threads ) )
if ( llama_eval( ctx , tokens_list.data() , int(tokens_list.size()) , llama_get_kv_cache_token_count( ctx ) , params.n_threads , params.n_threads ) )
{
fprintf( stderr, "%s : failed to eval\n" , __func__ );
return 1;