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Merge branch 'master' into compilade/refactor-kv-cache

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This commit is contained in:
Francis Couture-Harpin
2024-09-14 16:08:52 -04:00
parent 4bb4b22a58 822b6322de
commit 63ac36b271
144 changed files with 11344 additions and 6693 deletions
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24
examples/parallel/parallel.cpp
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@@ -1,7 +1,9 @@
// A basic application simulating a server with multiple clients.
// The clients submit requests to the server and they are processed in parallel.
#include "arg.h"
#include "common.h"
#include "sampling.h"
#include "llama.h"
#include <cmath>
@@ -50,8 +52,8 @@ static std::vector<std::string> k_prompts = {
struct client {
~client() {
if (ctx_sampling) {
llama_sampling_free(ctx_sampling);
if (smpl) {
gpt_sampler_free(smpl);
}
}
@@ -72,7 +74,7 @@ struct client {
std::string prompt;
std::string response;
struct llama_sampling_context * ctx_sampling = nullptr;
struct gpt_sampler * smpl = nullptr;
};
static void print_date_time() {
@@ -100,8 +102,7 @@ int main(int argc, char ** argv) {
gpt_params params;
if (!gpt_params_parse(argc, argv, params)) {
gpt_params_print_usage(argc, argv, params);
if (!gpt_params_parse(argc, argv, params, LLAMA_EXAMPLE_PARALLEL)) {
return 1;
}
@@ -161,7 +162,7 @@ int main(int argc, char ** argv) {
for (size_t i = 0; i < clients.size(); ++i) {
auto & client = clients[i];
client.id = i;
client.ctx_sampling = llama_sampling_init(params.sparams);
client.smpl = gpt_sampler_init(model, params.sparams);
}
std::vector<llama_token> tokens_system;
@@ -253,7 +254,7 @@ int main(int argc, char ** argv) {
client.prompt = client.input + "\nAssistant:";
client.response = "";
llama_sampling_reset(client.ctx_sampling);
gpt_sampler_reset(client.smpl);
// do not prepend BOS because we have a system prompt!
std::vector<llama_token> tokens_prompt;
@@ -341,9 +342,9 @@ int main(int argc, char ** argv) {
//printf("client %d, seq %d, token %d, pos %d, batch %d\n",
// client.id, client.seq_id, client.sampled, client.n_decoded, client.i_batch);
const llama_token id = llama_sampling_sample(client.ctx_sampling, ctx, NULL, client.i_batch - i);
const llama_token id = gpt_sampler_sample(client.smpl, ctx, client.i_batch - i);
llama_sampling_accept(client.ctx_sampling, ctx, id, true);
gpt_sampler_accept(client.smpl, id, true);
if (client.n_decoded == 1) {
// start measuring generation time after the first token to make sure all concurrent clients
@@ -371,7 +372,7 @@ int main(int argc, char ** argv) {
}
// delete only the generated part of the sequence, i.e. keep the system prompt in the cache
llama_past_seq_rm(ctx, client.id + 1, -1, -1);
llama_past_seq_rm(ctx, client.id + 1, -1, -1);
llama_past_seq_cp(ctx, 0, client.id + 1, -1, -1);
const auto t_main_end = ggml_time_us();
@@ -413,7 +414,8 @@ int main(int argc, char ** argv) {
LOG_TEE("\n");
llama_print_timings(ctx);
// TODO: print sampling/grammar timings for all clients
llama_perf_context_print(ctx);
llama_batch_free(batch);