ikawrakow/ik_llama.cpp
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Fix compiler warnings (#963)

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* Fix changes meaning warnings

* A couple of more warnings and formatting

---------

Co-authored-by: firecoperana <firecoperana>
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
This commit is contained in:
firecoperana
2025-11-15 05:07:15 +00:00
committed by GitHub
parent bb358223cd
commit 5ec0def0ef
1 changed files with 40 additions and 40 deletions
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80
examples/server/server.cpp
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@@ -581,7 +581,7 @@ struct slot_params {
std::string oaicompat_model;
std::string oaicompat_cmpl_id;
common_chat_syntax oaicompat_chat_syntax;
};
@@ -652,7 +652,7 @@ struct server_prompt_cache {
return res;
}
server_prompt* alloc(const server_prompt& prompt, size_t state_size) {
server_prompt* alloc(const server_prompt& prompt, size_t state_size) {
for (auto it = states.begin(); it != states.end();) {
const size_t len = it->tokens.get_common_prefix(prompt.tokens);
@@ -663,11 +663,11 @@ struct server_prompt_cache {
}
// next, remove any cached prompts that are fully contained in the current prompt
else if(len == it->tokens.size()) {
LLAMA_LOG_INFO(" - removing obsolete cached prompt with length %d\n", len);
LLAMA_LOG_INFO(" - removing obsolete cached prompt with length %d\n", (int)len);
it = states.erase(it);
}
else {
++it;
++it;
}
}
@@ -755,7 +755,7 @@ struct server_prompt_cache {
LLAMA_LOG_INFO(" - cache size limit reached, removing oldest entry (size = %.3f MiB)\n", states.front().size() / (1024.0 * 1024.0));
states.pop_front();
states.pop_front();
}
}
@@ -766,7 +766,7 @@ struct server_prompt_cache {
const size_t limit_tokens_cur = limit_size > 0 ? std::max<size_t>(limit_tokens, limit_size / size_per_token) : limit_tokens;
//if (limit_tokens > 0) {
//
//
// while (states.size() > 1 && n_tokens() > limit_tokens_cur) {
// if (states.empty()) {
// break;
@@ -842,17 +842,17 @@ struct server_slot {
std::string stopping_word;
stop_type stop;
server_prompt server_prompt;
server_prompt server_cached_prompt;
void prompt_save(server_prompt_cache & prompt_cache) const {
assert(server_prompt.data.size() == 0);
assert(server_cached_prompt.data.size() == 0);
const size_t cur_size = llama_state_seq_get_size(ctx, id);
LLAMA_LOG_INFO(" - saving prompt with length %d, total state size = %.3f MiB\n",
(int)server_prompt.tokens.size(), cur_size / (1024.0 * 1024.0));
(int)server_cached_prompt.tokens.size(), cur_size / (1024.0 * 1024.0));
auto* cur = prompt_cache.alloc(server_prompt, cur_size);
auto* cur = prompt_cache.alloc(server_cached_prompt, cur_size);
if (cur == nullptr) {
return;
}
@@ -861,7 +861,7 @@ struct server_slot {
}
void prompt_load(server_prompt_cache& prompt_cache, const server_tokens& tokens) {
bool res = prompt_cache.load(server_prompt, tokens, ctx, id);
bool res = prompt_cache.load(server_cached_prompt, tokens, ctx, id);
if (!res) {
LLAMA_LOG_INFO("failed to load prompt from cache\n");
}
@@ -1009,7 +1009,7 @@ struct server_slot {
}
const common_chat_msg& update_chat_msg(std::vector<common_chat_msg_diff>& diffs) {
auto previous_msg = chat_msg;
auto previous_msg = chat_msg;
auto new_msg = common_chat_parse(
generated_text,
/* is_partial= */ stop != STOP_TYPE_EOS,
@@ -1428,8 +1428,8 @@ struct server_context {
oaicompat_parser_options oai_parser_opt;
// Necessary similarity of prompt for slot selection
float slot_prompt_similarity = 0.0f;
int32_t cache_ram_n_min = 0;
float cache_ram_similarity = 0.5f;
int32_t cache_ram_n_min = 0;
float cache_ram_similarity = 0.5f;
~server_context() {
if (ctx) {
@@ -1530,7 +1530,7 @@ struct server_context {
}
// Load draft model for speculative decoding if specified
if (has_draft_model) {
LLAMA_LOG_INFO("\n\n==================================loading DRAFT model==================================\n\n");
LLAMA_LOG_INFO("\n\n==================================loading DRAFT model==================================\n\n");
gpt_params params_dft;
params_dft.devices = params.devices_draft;
@@ -1571,7 +1571,7 @@ struct server_context {
cparams_dft = llama_context_params_from_gpt_params(params_dft);
cparams_dft.n_batch = n_ctx_dft;
model_draft = llama_init_dft.model;
ctx_draft = llama_init_dft.context;
}
@@ -1669,7 +1669,7 @@ struct server_context {
LLAMA_LOG_INFO("prompt cache is enabled, size limit: %d MiB\n", params.cache_ram_mib);
}
LLAMA_LOG_INFO("%s", "use `--cache-ram 0` to disable the prompt cache\n");
// only apply ram size limit. No token limit for now.
// only apply ram size limit. No token limit for now.
prompt_cache = std::make_unique<server_prompt_cache>(params.cache_ram_mib, 0);
}
else {
@@ -1828,21 +1828,21 @@ struct server_context {
update_cache = update_cache && (ret->mctx == nullptr);
LLAMA_LOG_INFO("prompt cache: cache size: %d, cache_ram_n_min: %d, f_keep: %.2f, cache_ram_similarity: %.2f\n",
tokens.size(), cache_ram_n_min, f_keep, cache_ram_similarity);
(int)tokens.size(), cache_ram_n_min, f_keep, cache_ram_similarity);
if (update_cache) {
const int64_t t_start = ggml_time_us();
LLAMA_LOG_INFO("updating prompt cache\n");
ret->server_prompt.tokens = server_tokens(tokens.get_text_tokens(), false); // copy cache tokens
ret->server_cached_prompt.tokens = server_tokens(tokens.get_text_tokens(), false); // copy cache tokens
ret->prompt_save(*prompt_cache);
LLAMA_LOG_INFO("prompt cache save took %.2f ms\n", (ggml_time_us() - t_start) / 1000.0);
}
// has prompts saved earlier to load
// has prompts saved earlier to load
if (!prompt_cache->states.empty()) {
const int64_t t_start = ggml_time_us();
ret->server_prompt.tokens = server_tokens(tokens.get_text_tokens(), false); // copy cache tokens
ret->server_cached_prompt.tokens = server_tokens(tokens.get_text_tokens(), false); // copy cache tokens
ret->prompt_load(*prompt_cache, task.tokens);
prompt_cache->update();
ret->cache_tokens = server_tokens(ret->server_prompt.tokens.get_text_tokens(), false); // recover cache tokens
ret->cache_tokens = server_tokens(ret->server_cached_prompt.tokens.get_text_tokens(), false); // recover cache tokens
LLAMA_LOG_INFO("prompt cache load took %.2f ms\n", (ggml_time_us() - t_start) / 1000.0);
}
}
@@ -2007,7 +2007,7 @@ struct server_context {
}
slot.prompt_tokens = std::move(task.tokens);
}
// penalize user-provided tokens
{
slot.sparams.penalty_prompt_tokens.clear();
@@ -2072,7 +2072,7 @@ struct server_context {
slot.params.oaicompat_chat_syntax.thinking_forced_open = json_value(data, "thinking_forced_open", false);
}
{
const auto preserved_tokens = data.find("preserved_tokens");
if (preserved_tokens != data.end()) {
for (const auto& t : *preserved_tokens) {
@@ -2126,7 +2126,7 @@ struct server_context {
}
}
}
if (slot.sparams.grammar_lazy && slot.sparams.grammar_triggers.empty()) {
throw std::runtime_error("Error: no triggers set for lazy grammar!");
}
@@ -2314,7 +2314,7 @@ struct server_context {
pos = std::min(slot.n_sent_text, slot.generated_text.size());
}
else if (slot.has_next_token && !llama_token_is_eog(model, result.tok)) {
stop_pos = slot.find_stopping_strings(str_test, token_str.size(), false);
stop_pos = slot.find_stopping_strings(str_test, token_str.size(), false);
send_text = stop_pos == std::string::npos;
}
@@ -3312,7 +3312,7 @@ struct server_context {
if (slot.n_prompt_tokens >= slot.n_ctx) {
send_error(slot, "the request exceeds the available context size, try increasing it", ERROR_TYPE_SERVER);
slot.release();
continue;
continue;
}
llama_sampling_reset(llama_get_model_vocab(model), slot.ctx_sampling);
@@ -3322,7 +3322,7 @@ struct server_context {
slot.ga_i = 0;
} else {
GGML_ASSERT(slot.ga_n == 1);
// reuse any previously computed tokens that are common with the new prompt
slot.n_past = slot.cache_tokens.get_common_prefix(prompt_tokens);
@@ -3909,11 +3909,11 @@ static std::vector<json> format_partial_response_oaicompat(server_task_result ta
{"model", modelname},
{"object", "chat.completion.chunk"}
};
if (task_result.timings.prompt_n != -1) {
ret.push_back({ "timings", task_result.timings.to_json() });
}
//
if (!finish_reason.empty()) {
int num_tokens_predicted = json_value(result, "tokens_predicted", 0);
@@ -4605,7 +4605,7 @@ int main(int argc, char ** argv) {
{ "n_ctx", ctx_server.n_ctx }
};
if (ctx_server.params.use_jinja) {
if (auto tool_use_src = common_chat_templates_source(ctx_server.chat_templates.get(), "tool_use")) {
data["chat_template_tool_use"] = tool_use_src;
@@ -4831,7 +4831,7 @@ int main(int argc, char ** argv) {
OAICOMPAT_TYPE_NONE); // infill is not OAI compatible
};
const auto handle_tokenize = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
const auto handle_tokenize = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
const json body = json::parse(req.body);
std::vector<llama_token> tokens;
@@ -4843,7 +4843,7 @@ int main(int argc, char ** argv) {
return res.set_content(data.dump(), "application/json; charset=utf-8");
};
const auto handle_detokenize = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
const auto handle_detokenize = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
const json body = json::parse(req.body);
std::string content;
@@ -4857,7 +4857,7 @@ int main(int argc, char ** argv) {
};
const auto handle_embeddings = [&ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
const auto handle_embeddings = [&ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
const json body = json::parse(req.body);
bool is_openai = false;
@@ -4908,7 +4908,7 @@ int main(int argc, char ** argv) {
return res.set_content(root.dump(), "application/json; charset=utf-8");
};
const auto handle_lora_adapters_list = [&](const httplib::Request & req, httplib::Response & res) {
const auto handle_lora_adapters_list = [&](const httplib::Request & req, httplib::Response & res) {
json result = json::array();
for (size_t i = 0; i < ctx_server.lora_adapters.size(); ++i) {
auto & la = ctx_server.lora_adapters[i];
@@ -4922,7 +4922,7 @@ int main(int argc, char ** argv) {
res.status = 200; // HTTP OK
};
const auto handle_lora_adapters_apply = [&](const httplib::Request & req, httplib::Response & res) {
const auto handle_lora_adapters_apply = [&](const httplib::Request & req, httplib::Response & res) {
const std::vector<json> body = json::parse(req.body);
int max_idx = ctx_server.lora_adapters.size();
@@ -4954,7 +4954,7 @@ int main(int argc, char ** argv) {
res.status = 200; // HTTP OK
};
const auto list_saved_prompts = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res) {
const auto list_saved_prompts = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res) {
json response = json::array();
namespace fs = std::filesystem;
@@ -5014,7 +5014,7 @@ int main(int argc, char ** argv) {
res.set_content(response.dump(), "application/json; charset=utf-8");
};
const auto list_slot_prompts = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res) {
const auto list_slot_prompts = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res) {
json response = json::array();
for (server_slot & slot : ctx_server.slots) {
response.push_back({
@@ -5027,7 +5027,7 @@ int main(int argc, char ** argv) {
};
const auto delete_saved_prompt = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res)-> void {
const auto delete_saved_prompt = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res)-> void {
json response;
namespace fs = std::filesystem;
@@ -5074,7 +5074,7 @@ int main(int argc, char ** argv) {
res.set_content(response.dump(), "application/json; charset=utf-8");
};
const auto rename_saved_prompt = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res)-> void {
const auto rename_saved_prompt = [&ctx_server, &params](const httplib::Request& req, httplib::Response& res)-> void {
json response;
namespace fs = std::filesystem;