From 778c070d1b8a67f4387946e424dfadbd58748334 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Fri, 20 Oct 2023 20:44:51 +0300 Subject: [PATCH] server : logs + minor code style --- examples/server/server.cpp | 112 ++++++++++++++++++++----------------- 1 file changed, 62 insertions(+), 50 deletions(-) diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 552f1c512..fb900d299 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -614,13 +614,16 @@ struct llama_server_context // create slots all_slots_are_idle = true; - if(max_ctx_per_slot == -1) { + if (max_ctx_per_slot == -1) + { max_ctx_per_slot = n_ctx / params.n_parallel; // split context } - if(max_ctx_per_slot * params.n_parallel > n_ctx) { + if (max_ctx_per_slot * params.n_parallel > n_ctx) + { printf("Error: The max context per slot is more greater than model context size"); return; } + LOG_TEE("Available slots:\n"); for (int i = 0; i < params.n_parallel; i++) { @@ -628,6 +631,7 @@ struct llama_server_context slot.id = i; slot.max_context_size = max_ctx_per_slot; slot.reset(); + LOG_TEE(" -> Slot %i - max context: %i\n", slot.id, max_ctx_per_slot); slots.push_back(slot); } @@ -788,7 +792,7 @@ struct llama_server_context } } - if(multimodal) + if (multimodal) { const auto &images_data = data.find("image_data"); if (images_data != data.end() && images_data->is_array()) @@ -1068,10 +1072,10 @@ struct llama_server_context slot.has_next_token = false; } - if (!slot.cache_tokens.empty() && result.tok == llama_token_eos(ctx)){ - slot.stopped_eos = true; - slot.has_next_token = false; - LOG_VERBOSE("eos token found", {}); + if (!slot.cache_tokens.empty() && result.tok == llama_token_eos(ctx)) { + slot.stopped_eos = true; + slot.has_next_token = false; + LOG_VERBOSE("eos token found", {}); } LOG_VERBOSE("next token", { @@ -1277,22 +1281,25 @@ struct llama_server_context } task_result next_result(int task_id) { - while(true) { + while (true) { std::this_thread::sleep_for(std::chrono::microseconds(5)); std::lock_guard lock(mutex_results); - if(queue_results.empty()) { + + if (queue_results.empty()) { continue; } - for(int i = 0; i < queue_results.size(); i++) { - if(queue_results[i].id == task_id) { + for (int i = 0; i < (int) queue_results.size(); i++) { + if (queue_results[i].id == task_id) { task_result res = queue_results[i]; queue_results.erase(queue_results.begin() + i); return res; } } } - return task_result{-1, false, false, {}}; + + // never reached + //return task_result{-1, false, false, {}}; } // for multiple images processing @@ -1373,48 +1380,48 @@ struct llama_server_context void process_tasks() { std::lock_guard lock(mutex_tasks); - while(!queue_tasks.empty()) { + while (!queue_tasks.empty()) { task_server task = queue_tasks.front(); queue_tasks.erase(queue_tasks.begin()); switch (task.type) { - case COMPLETION_TASK: { // perform completion task - llama_client_slot* slot = get_slot(json_value(task.data, "slot_id", -1)); - if (slot == nullptr) { - LOG_TEE("slot unavailable\n"); - // send error result - send_error(task.id, "slot unavaliable"); - return; - } + case COMPLETION_TASK: { + llama_client_slot* slot = get_slot(json_value(task.data, "slot_id", -1)); + if (slot == nullptr) { + LOG_TEE("slot unavailable\n"); + // send error result + send_error(task.id, "slot unavaliable"); + return; + } - if (task.data.contains("system_prompt")) { - process_system_prompt_data(task.data["system_prompt"]); - } + if (task.data.contains("system_prompt")) { + process_system_prompt_data(task.data["system_prompt"]); + } - slot->reset(); + slot->reset(); - slot->infill = task.infill_mode; - slot->task_id = task.id; + slot->infill = task.infill_mode; + slot->task_id = task.id; - if (!launch_slot_with_data(slot, task.data)) - { - // send error result - send_error(task.id, "internal_error"); - break; - } - } - case CANCEL_TASK: { // release slot linked with the task id - for(auto & slot : slots) { - if(slot.task_id == task.target_id) { - slot.release(); + if (!launch_slot_with_data(slot, task.data)) + { + // send error result + send_error(task.id, "internal_error"); break; } } - } - break; + case CANCEL_TASK: { // release slot linked with the task id + for (auto & slot : slots) { + if (slot.task_id == task.target_id) { + slot.release(); + break; + } + } + } + break; - default: - break; + default: + break; } } } @@ -1426,6 +1433,7 @@ struct llama_server_context // update the system prompt wait until all slots are idle state if (need_update_system_prompt) { + LOG_TEE("updating system prompt\n"); update_system_prompt(); } @@ -1435,6 +1443,7 @@ struct llama_server_context { if (system_prompt.empty() && clean_kv_cache) { + LOG_TEE("all slots are idle and system prompt is empty, clear the KV cache\n"); kv_cache_clear(); } // avoid 100% usage of cpu all time @@ -1449,6 +1458,7 @@ struct llama_server_context const int n_left = slot.n_past - slot.params.n_keep - 1; const int n_discard = n_left / 2; + LOG_TEE("slot %d: context shift - n_keep = %d, n_left = %d, n_discard = %d\n", slot.id, slot.params.n_keep, n_left, n_discard); llama_kv_cache_seq_rm (ctx, slot.id, slot.params.n_keep + 1 , slot.params.n_keep + n_discard + 1); llama_kv_cache_seq_shift(ctx, slot.id, slot.params.n_keep + 1 + n_discard, slot.n_past, -n_discard); @@ -1463,7 +1473,7 @@ struct llama_server_context slot.truncated = true; - LOG_VERBOSE("input truncated", { + LOG_VERBOSE("context shift", { {"n_ctx", n_ctx}, {"n_keep", params.n_keep}, {"n_left", n_left}, @@ -1478,7 +1488,7 @@ struct llama_server_context if (slot.state == PROCESSING && slot.command == RELEASE) { slot.state = slot.params.cache_prompt ? SLEEPING : IDLE; - if(slot.state == SLEEPING) { + if (slot.state == SLEEPING) { LOG_TEE("slot %i has %i tokens in cache.\n", slot.id, (int) slot.cache_tokens.size()); } else @@ -1504,6 +1514,7 @@ struct llama_server_context slot.n_decoded += 1; slot.n_past += 1; } + // process in chunks of params.n_batch int32_t n_batch = params.n_batch; @@ -1547,7 +1558,7 @@ struct llama_server_context slot.num_prompt_tokens = prompt_tokens.size(); - if(!slot.params.cache_prompt) + if (!slot.params.cache_prompt) { std::fill(slot.ctx_sampling->prev.begin(), slot.ctx_sampling->prev.end(), 0); slot.n_past = 0; @@ -1586,9 +1597,10 @@ struct llama_server_context std::copy(prompt_tokens.begin(), prompt_tokens.end(), slot.ctx_sampling->prev.end() - ps); slot.n_past = common_part(slot.cache_tokens, prompt_tokens); slot.num_prompt_tokens_processed = slot.num_prompt_tokens - slot.n_past; - LOG_TEE("slot %i - in cache: %i tokens | to process: %i tokens\n", slot.id, slot.n_past, slot.num_prompt_tokens_processed); + LOG_TEE("slot %d : in cache: %i tokens | to process: %i tokens\n", slot.id, slot.n_past, slot.num_prompt_tokens_processed); } + LOG_TEE("slot %d : kv cache rm - [%d, end)\n", slot.id, num_tokens_system + slot.n_past); llama_kv_cache_seq_rm(ctx, slot.id, num_tokens_system + slot.n_past, -1); slot.cache_tokens = prompt_tokens; @@ -1596,7 +1608,7 @@ struct llama_server_context if (slot.n_past == (int) slot.num_prompt_tokens) { // we have to evaluate at least 1 token to generate logits. - printf("we have to evaluate at least 1 token to generate logits\n"); + LOG_TEE("slot %d : we have to evaluate at least 1 token to generate logits\n", slot.id); slot.n_past--; } @@ -1606,7 +1618,7 @@ struct llama_server_context {"to_eval", tokens_to_str(ctx, slot.cache_tokens.cbegin() + slot.n_past, slot.cache_tokens.cend())}, }); - const bool has_images = process_images(slot); // has images? + const bool has_images = process_images(slot); // process the prefix of first image std::vector prefix_tokens = has_images ? tokenize(slot.images[0].prefix_prompt, true) : prompt_tokens; @@ -1664,7 +1676,7 @@ struct llama_server_context return false; } - LOG("%s : failed to decode the batch, retrying with n_batch = %d\n", __func__, n_batch / 2); + LOG_TEE("%s : failed to find free space in the KV cache, retrying with smaller n_batch = %d\n", __func__, n_batch / 2); // retry with half the batch size to try to find a free slot in the KV cache n_batch /= 2; @@ -1705,7 +1717,7 @@ struct llama_server_context const int32_t n_probs = slot.sparams.n_probs; if (slot.sparams.temp <= 0 && n_probs > 0) { - // For llama_sample_token_greedy we need to sort candidates + // for llama_sample_token_greedy we need to sort candidates llama_sample_softmax(ctx, &cur_p); }