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logs : reduce v2 (#25078)

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* server : reduce logs

* cont : common

* cont : spec

* cont : CMN_ -> COM_
This commit is contained in:
Georgi Gerganov
2026-06-28 08:52:15 +03:00
committed by GitHub
parent ebd048fc5e
commit 27c8bb4f63
12 changed files with 203 additions and 194 deletions
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86
tools/server/server-context.cpp
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@@ -106,7 +106,6 @@ struct server_batch {
if ((int32_t)tokens.size() >= n_tokens_alloc) {
return false;
}
// LOG_INF("adding token to batch: slot=%d, token=%d, pos=%d, output=%d\n", id_slot, token, pos, output);
tokens.push_back({ id_slot, token, pos, output });
return true;
}
@@ -228,7 +227,7 @@ struct server_slot {
const size_t cur_size = cur_size_tgt + cur_size_dft;
SRV_WRN(" - saving prompt with length %d, total state size = %.3f MiB (draft: %.3f MiB)\n",
SRV_TRC(" - saving prompt with length %d, total state size = %.3f MiB (draft: %.3f MiB)\n",
(int) prompt.tokens.size(), cur_size / (1024.0 * 1024.0), cur_size_dft / (1024.0 * 1024.0));
auto * cur = prompt_cache.alloc(prompt, cur_size_tgt, cur_size_dft);
@@ -258,7 +257,7 @@ struct server_slot {
GGML_ASSERT(!is_processing());
}
SLT_INF(*this, "clearing prompt with %zu tokens\n", prompt.tokens.size());
SLT_TRC(*this, "clearing prompt with %zu tokens\n", prompt.tokens.size());
common_context_seq_rm(ctx_tgt, id, -1, -1);
if (ctx_dft) {
@@ -627,8 +626,10 @@ struct server_slot {
}
SLT_INF(*this,
"draft acceptance = %0.5f (%5d accepted / %5d generated), mean acceptance length = %5.2f, acceptance rate per position = (%s)\n",
draft_ratio, n_draft_accepted, n_draft_total, mean_acc_len, acceptance_rates_per_pos.c_str());
"draft acceptance = %0.5f (%5d accepted / %5d generated), mean len = %5.2f\n",
draft_ratio, n_draft_accepted, n_draft_total, mean_acc_len);
SLT_TRC(*this,
" acc per pos = (%s)\n", acceptance_rates_per_pos.c_str());
}
common_speculative_print_stats(spec);
@@ -771,7 +772,7 @@ struct server_slot {
}
// TODO @ngxson : move this log line to debug when it become more stable
SLT_INF(*this, "encoding mtmd batch from idx = %zu, n_chunks = %d\n", idx, n_added);
SLT_TRC(*this, "encoding mtmd batch from idx = %zu, n_chunks = %d\n", idx, n_added);
res = mtmd_batch_encode(mbatch.get());
if (res != 0) {
@@ -1032,7 +1033,8 @@ private:
}
SRV_INF("loading model '%s'\n", params.model.path.c_str());
SRV_INF("loading model '%s'\n", params.model.get_name().c_str());
SRV_TRC("local path '%s'\n", params.model.path.c_str());
std::string & mmproj_path = params_base.mmproj.path;
mtmd_context_params mparams = mtmd_context_params_default();
@@ -1061,7 +1063,7 @@ private:
for (auto & [dev, size] : mmproj_mem) {
total += size;
}
SRV_INF("[mtmd] estimated worst-case memory usage of mmproj is %.2f MiB (took %.2f ms)\n", total / (1024.0 * 1024.0), t_elapsed / 1000.0);
SRV_TRC("[mtmd] estimated worst-case memory usage of mmproj is %.2f MiB (took %.2f ms)\n", total / (1024.0 * 1024.0), t_elapsed / 1000.0);
GGML_ASSERT(!params_base.fit_params_target.empty());
for (auto & [dev, size] : mmproj_mem) {
for (size_t i = 0; i < ggml_backend_dev_count(); i++) {
@@ -1141,7 +1143,7 @@ private:
}
}
}
SRV_INF("[spec] estimated memory usage of %s is %.2f MiB\n",
SRV_TRC("[spec] estimated memory usage of %s is %.2f MiB\n",
has_draft ? "draft model" : "MTP context",
total / (1024.0 * 1024.0));
} catch (const std::exception & e) {
@@ -1177,7 +1179,7 @@ private:
// TODO speculative: move to common/speculative.cpp?
const auto & params_spec = params_base.speculative.draft;
SRV_INF("loading draft model '%s'\n", params_spec.mparams.path.c_str());
SRV_TRC("loading draft model '%s'\n", params_spec.mparams.path.c_str());
auto params_dft = params_base;
@@ -1229,7 +1231,7 @@ private:
// no new model load, so we simply report 0.0 and 1.0 progress
load_progress_callback(0.0f, &load_progress_spec);
SRV_INF("creating MTP draft context against the target model '%s'\n",
SRV_TRC("creating MTP draft context against the target model '%s'\n",
params_base.model.path.c_str());
auto cparams_mtp = common_context_params_to_llama(params_base);
@@ -1303,9 +1305,6 @@ private:
// Necessary similarity of prompt for slot selection
slot_prompt_similarity = params_base.slot_prompt_similarity;
// setup slots
SRV_INF("initializing slots, n_slots = %d\n", params_base.n_parallel);
const int n_ctx_train = llama_model_n_ctx_train(model_tgt);
int n_ctx_slot = llama_n_ctx_seq(ctx_tgt);
@@ -1322,9 +1321,13 @@ private:
}
if (ctx_tgt_seq_rm_type == COMMON_CONTEXT_SEQ_RM_TYPE_FULL) {
SRV_WRN("%s", "speculative decoding will use checkpoints\n");
SRV_TRC("%s", "speculative decoding will use checkpoints\n");
}
// setup slots
SRV_INF("initializing, n_slots = %d, n_ctx_slot = %d, kv_unified = '%s'\n",
params_base.n_parallel, n_ctx_slot, params_base.kv_unified ? "true" : "false");
// initialize slots
for (int i = 0; i < params_base.n_parallel; i++) {
slots.emplace_back();
@@ -1344,7 +1347,7 @@ private:
}
if (spec) {
SRV_INF("%s", "speculative decoding context initialized\n");
SRV_TRC("%s", "speculative decoding context initialized\n");
} else {
ctx_dft.reset();
}
@@ -1361,7 +1364,7 @@ private:
slot.mctx = mctx;
slot.prompt.tokens.has_mtmd = mctx != nullptr;
SLT_INF(slot, "new slot, n_ctx = %d\n", slot.n_ctx);
SLT_TRC(slot, "new slot, n_ctx = %d\n", slot.n_ctx);
slot.callback_on_release = [this](int id_slot) {
queue_tasks.pop_deferred_task(id_slot);
@@ -1397,23 +1400,23 @@ private:
if (params_base.cache_ram_mib != 0) {
if (params_base.cache_ram_mib < 0) {
SRV_INF("prompt cache is enabled, size limit: %s\n", "no limit");
SRV_TRC("prompt cache is enabled, size limit: %s\n", "no limit");
} else {
SRV_INF("prompt cache is enabled, size limit: %d MiB\n", params_base.cache_ram_mib);
SRV_TRC("prompt cache is enabled, size limit: %d MiB\n", params_base.cache_ram_mib);
}
SRV_INF("%s", "use `--cache-ram 0` to disable the prompt cache\n");
SRV_TRC("%s", "use `--cache-ram 0` to disable the prompt cache\n");
prompt_cache = std::make_unique<server_prompt_cache>(params_base.cache_ram_mib, n_ctx);
} else {
SRV_INF("%s", "prompt cache is disabled - use `--cache-ram N` to enable it\n");
SRV_TRC("%s", "prompt cache is disabled - use `--cache-ram N` to enable it\n");
}
SRV_INF("%s", "for more info see https://github.com/ggml-org/llama.cpp/pull/16391\n");
SRV_TRC("%s", "for more info see https://github.com/ggml-org/llama.cpp/pull/16391\n");
if (params_base.n_ctx_checkpoints > 0) {
SRV_INF("context checkpoints enabled, max = %d, min spacing = %d\n",
SRV_TRC("context checkpoints enabled, max = %d, min spacing = %d\n",
params_base.n_ctx_checkpoints, params_base.checkpoint_min_step);
} else {
SRV_INF("%s", "context checkpoints disabled\n");
SRV_TRC("%s", "context checkpoints disabled\n");
}
if (!params_base.model_alias.empty()) {
@@ -1470,11 +1473,11 @@ private:
params_base.cache_idle_slots = false;
} else {
if (params_base.kv_unified) {
SRV_INF("%s", "idle slots will be saved to prompt cache and cleared upon starting a new task\n");
SRV_TRC("%s", "idle slots will be saved to prompt cache and cleared upon starting a new task\n");
} else {
// without a unified KV cache, clearing a slot frees no reusable room, so we only
// publish a RAM-cache copy of idle slots (their KV stays in VRAM) [TAG_IDLE_SLOT_CLEAR]
SRV_INF("%s", "idle slots will be saved to prompt cache upon starting a new task\n");
SRV_TRC("%s", "idle slots will be saved to prompt cache upon starting a new task\n");
}
SRV_DBG("%s", "__TEST_TAG_CACHE_IDLE_SLOTS_ENABLED__\n");
}
@@ -1500,7 +1503,7 @@ private:
try {
chat_templates = common_chat_templates_init(model_tgt, params_base.chat_template);
LOG_INF("%s: chat template, example_format: '%s'\n", __func__,
SRV_TRC("%s: chat template, example_format: '%s'\n", __func__,
common_chat_format_example(chat_templates.get(), params_base.use_jinja, params_base.default_template_kwargs).c_str());
} catch (const std::exception & e) {
@@ -1515,7 +1518,7 @@ private:
// 2. The chat template supports it
const bool template_supports_thinking = params_base.use_jinja && common_chat_templates_support_enable_thinking(chat_templates.get());
const bool enable_thinking = params_base.enable_reasoning != 0 && template_supports_thinking;
SRV_INF("%s: chat template, thinking = %d\n", __func__, enable_thinking);
SRV_TRC("%s: chat template, thinking = %d\n", __func__, enable_thinking);
// IMPORTANT: chat_params is reused across sleeping / resuming states,
// never store llama_context/llama_model pointers in chat_params,
@@ -1658,7 +1661,7 @@ private:
update_cache = update_cache && task.type == SERVER_TASK_TYPE_COMPLETION;
if (update_cache) {
SRV_INF("%s", "updating prompt cache\n");
SRV_TRC("%s", "updating prompt cache\n");
const int64_t t_start = ggml_time_us();
@@ -1670,7 +1673,7 @@ private:
prompt_cache->update();
SRV_INF("prompt cache update took %.2f ms\n", (ggml_time_us() - t_start) / 1000.0);
SRV_TRC("prompt cache update took %.2f ms\n", (ggml_time_us() - t_start) / 1000.0);
}
}
@@ -2290,7 +2293,7 @@ private:
int id_parent = parent_task.id;
SRV_INF("launching slots for parent task id_task = %d with %zu child tasks\n", id_parent, parent_task.child_tasks.size());
SRV_TRC("launching slots for parent task id_task = %d with %zu child tasks\n", id_parent, parent_task.child_tasks.size());
// to be called in case of failure to release all launched slots
auto release_slots = [this, id_parent]() {
@@ -2351,7 +2354,7 @@ private:
// stash the draft's speculative state with the checkpoint
common_speculative_get_state(spec.get(), slot.id, cur.data_spec);
SLT_INF(slot,
SLT_TRC(slot,
"created context checkpoint %d of %d (pos_min = %d, pos_max = %d, n_tokens = %" PRId64 ", size = %.3f MiB)\n",
(int) slot.prompt.checkpoints.size(), params_base.n_ctx_checkpoints, cur.pos_min,
cur.pos_max, cur.n_tokens, (float) cur.size() / 1024 / 1024);
@@ -2415,7 +2418,7 @@ private:
if (params_base.cache_idle_slots) {
for (auto & slot : slots) {
if (!slot.is_processing()) {
SLT_INF(slot, "%s", "saving idle slot to prompt cache\n");
SLT_TRC(slot, "%s", "saving idle slot to prompt cache\n");
if (slot.prompt_save(*prompt_cache)) {
SLT_DBG(slot, "%s", "__TEST_TAG_CACHE_IDLE_SLOT__\n");
@@ -2671,7 +2674,7 @@ private:
auto new_loras = construct_lora_list(task.set_lora);
// logging
for (size_t i = 0; i < new_loras.size(); ++i) {
SRV_INF("set lora adapter idx=%zu scale=%f\n", i, new_loras[i].scale);
SRV_TRC("set lora adapter idx=%zu scale=%f\n", i, new_loras[i].scale);
}
// TODO @ngxson : make lora_adapters a dedicated member of server_context
params_base.lora_adapters = new_loras;
@@ -2771,7 +2774,7 @@ private:
}
if (all_idle) {
SRV_INF("%s", "all slots are idle\n");
SRV_TRC("%s", "all slots are idle\n");
return; // skip further processing
} else {
@@ -3287,10 +3290,9 @@ private:
const auto it = std::find_if(
slot.prompt.checkpoints.rbegin(),
slot.prompt.checkpoints.rend(),
[&, func_name = __func__](const auto & cur) {
[&](const auto & cur) {
// guarantee that a checkpoint will result in at least one token being processed [TAG_PROMPT_LOGITS]
LOG_INF("slot %12.*s: id %2d | task %d | Checking checkpoint with [%d, %d] against %d...\n", 12,
func_name, (slot).id, ((slot).task ? (slot).task->id : -1), cur.pos_min, cur.pos_max, pos_min_thold);
SLT_TRC(slot, "checking checkpoint with [%d, %d] against %d...\n", cur.pos_min, cur.pos_max, pos_min_thold);
// workaround for [TAG_CHECKPOINTS_FIX_POS_MIN]
if (cur.pos_max > pos_next) {
return false;
@@ -3310,11 +3312,11 @@ private:
pos_next = std::min(pos_next, std::max(it->pos_min + 1, it->pos_max));
n_past = std::min(slot.prompt.tokens.size_up_to_pos(pos_next), (size_t) it->n_tokens);
SLT_WRN(slot, "restored context checkpoint (pos_min = %d, pos_max = %d, n_tokens = %" PRId64 ", n_past = %d, size = %.3f MiB)\n", it->pos_min, it->pos_max, it->n_tokens, n_past, (float) it->size() / 1024 / 1024);
SLT_TRC(slot, "restored context checkpoint (pos_min = %d, pos_max = %d, n_tokens = %" PRId64 ", n_past = %d, size = %.3f MiB)\n", it->pos_min, it->pos_max, it->n_tokens, n_past, (float) it->size() / 1024 / 1024);
}
if (do_reset) {
SLT_WRN(slot, "forcing full prompt re-processing due to lack of cache data (likely due to SWA or hybrid/recurrent memory, see %s)\n",
SLT_TRC(slot, "forcing full prompt re-processing due to lack of cache data (likely due to SWA or hybrid/recurrent memory, see %s)\n",
"https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055");
pos_next = 0;
n_past = 0;
@@ -3327,7 +3329,7 @@ private:
for (auto it = slot.prompt.checkpoints.begin(); it != slot.prompt.checkpoints.end();) {
const auto & cur = *it;
if (cur.pos_max > pos_next) {
SLT_WRN(slot, "erased invalidated context checkpoint (pos_min = %d, pos_max = %d, n_tokens = %" PRId64 ", n_swa = %d, pos_next = %d, size = %.3f MiB)\n", cur.pos_min, cur.pos_max, cur.n_tokens, n_swa, pos_next, (float) cur.size() / 1024 / 1024);
SLT_TRC(slot, "erased invalidated context checkpoint (pos_min = %d, pos_max = %d, n_tokens = %" PRId64 ", n_swa = %d, pos_next = %d, size = %.3f MiB)\n", cur.pos_min, cur.pos_max, cur.n_tokens, n_swa, pos_next, (float) cur.size() / 1024 / 1024);
it = slot.prompt.checkpoints.erase(it);
} else {
++it;
@@ -3674,7 +3676,7 @@ private:
// all children slots should already launched by launch_slots_with_parent_task()
// copy state to the child slots
for (auto & child : children) {
SLT_INF(slot, " - copying state to child %d\n", child->id);
SLT_TRC(slot, " - copying state to child %d\n", child->id);
GGML_ASSERT(child->state == SLOT_STATE_WAIT_OTHER);