common : reimplement logging (#9418)
https://github.com/ggerganov/llama.cpp/pull/9418
This commit is contained in:
Georgi Gerganov
GitHub
parent
e6deac31f7
commit
6262d13e0b
54 changed files with 2092 additions and 2419 deletions
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@ -1,5 +1,6 @@
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#include "arg.h"
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#include "common.h"
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#include "log.h"
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#include "llama.h"
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#include <cmath>
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@ -8,9 +9,9 @@
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#include <vector>
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static void print_usage(int, char ** argv) {
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LOG_TEE("\nexample usage:\n");
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LOG_TEE("\n %s -m model.gguf --junk 250 --pos 90 --keep 32 --grp-attn-n 2 [--seed 1234]\n", argv[0]);
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LOG_TEE("\n");
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LOG("\nexample usage:\n");
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LOG("\n %s -m model.gguf --junk 250 --pos 90 --keep 32 --grp-attn-n 2 [--seed 1234]\n", argv[0]);
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LOG("\n");
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}
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int main(int argc, char ** argv) {
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@ -24,6 +25,8 @@ int main(int argc, char ** argv) {
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return 1;
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}
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gpt_init();
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int n_junk = params.n_junk;
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int n_keep = params.n_keep;
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int n_grp = params.grp_attn_n;
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@ -63,7 +66,7 @@ int main(int argc, char ** argv) {
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llama_model * model = llama_load_model_from_file(params.model.c_str(), model_params);
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if (model == NULL) {
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fprintf(stderr , "%s: error: unable to load model\n" , __func__);
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LOG_ERR("%s: unable to load model\n" , __func__);
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return 1;
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}
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@ -77,7 +80,7 @@ int main(int argc, char ** argv) {
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llama_context * ctx = llama_new_context_with_model(model, ctx_params);
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if (ctx == NULL) {
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fprintf(stderr , "%s: error: failed to create the llama_context\n" , __func__);
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LOG_ERR("%s: failed to create the llama_context\n" , __func__);
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return 1;
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}
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@ -107,14 +110,14 @@ int main(int argc, char ** argv) {
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const int n_batch = ctx_params.n_batch;
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const int n_batch_grp = ctx_params.n_batch/n_grp;
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LOG_TEE("\n%s: n_len = %d, n_ctx = %d, n_kv_req = %d, n_grp = %d, n_batch = %d, n_junk = %d, i_pos = %d\n", __func__, n_len, n_ctx, n_kv_req, n_grp, n_batch, n_junk, i_pos);
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LOG_INF("\n%s: n_len = %d, n_ctx = %d, n_kv_req = %d, n_grp = %d, n_batch = %d, n_junk = %d, i_pos = %d\n", __func__, n_len, n_ctx, n_kv_req, n_grp, n_batch, n_junk, i_pos);
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// print the prompt token-by-token
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LOG_TEE("\n");
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LOG_TEE("prefix tokens: %d\n", n_tokens_prefix);
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LOG_TEE("prompt tokens: %d\n", n_tokens_all);
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//LOG_TEE("prompt: %s\n", params.prompt.c_str());
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LOG_INF("\n");
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LOG_INF("prefix tokens: %d\n", n_tokens_prefix);
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LOG_INF("prompt tokens: %d\n", n_tokens_all);
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//LOG_INF("prompt: %s\n", params.prompt.c_str());
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llama_batch batch = llama_batch_init(params.n_batch, 0, 1);
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@ -145,11 +148,11 @@ int main(int argc, char ** argv) {
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}
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if (llama_decode(ctx, batch) != 0) {
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LOG_TEE("%s: llama_decode() failed\n", __func__);
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LOG_INF("%s: llama_decode() failed\n", __func__);
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return 1;
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}
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LOG_TEE("%s: processed: [%6d, %6d)\n", __func__, i, std::min(i + n_batch, n_tokens_all));
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LOG_INF("%s: processed: [%6d, %6d)\n", __func__, i, std::min(i + n_batch, n_tokens_all));
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if (i + n_batch >= n_tokens_all) {
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break;
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@ -159,7 +162,7 @@ int main(int argc, char ** argv) {
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for (int i = n_ctx; i < n_tokens_all; i += n_batch) {
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const int n_discard = n_batch;
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LOG_TEE("%s: shifting KV cache with %d\n", __func__, n_discard);
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LOG_INF("%s: shifting KV cache with %d\n", __func__, n_discard);
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llama_kv_cache_seq_rm (ctx, 0, n_keep , n_keep + n_discard);
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llama_kv_cache_seq_add(ctx, 0, n_keep + n_discard, n_ctx, -n_discard);
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@ -179,18 +182,18 @@ int main(int argc, char ** argv) {
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}
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if (llama_decode(ctx, batch) != 0) {
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LOG_TEE("%s: llama_decode() failed\n", __func__);
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LOG_ERR("%s: llama_decode() failed\n", __func__);
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return 1;
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}
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LOG_TEE("%s: processed: [%6d, %6d)\n", __func__, i, std::min(i + n_batch, n_tokens_all));
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LOG_INF("%s: processed: [%6d, %6d)\n", __func__, i, std::min(i + n_batch, n_tokens_all));
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}
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{
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const int n_discard = n_past - n_ctx + n_predict;
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if (n_discard > 0) {
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LOG_TEE("%s: shifting KV cache with %d to free space for the answer\n", __func__, n_discard);
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LOG_INF("%s: shifting KV cache with %d to free space for the answer\n", __func__, n_discard);
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llama_kv_cache_seq_rm (ctx, 0, n_keep , n_keep + n_discard);
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llama_kv_cache_seq_add(ctx, 0, n_keep + n_discard, n_ctx, -n_discard);
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@ -201,17 +204,16 @@ int main(int argc, char ** argv) {
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}
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}
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LOG_TEE("\n");
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LOG_TEE("%s: passkey = %d, inserted at position %d / %d (token pos: ~%d)\n", __func__, passkey, i_pos, n_junk, (i_pos * n_tokens_all) / n_junk);
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LOG_TEE("\n");
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LOG_INF("\n");
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LOG_INF("%s: passkey = %d, inserted at position %d / %d (token pos: ~%d)\n", __func__, passkey, i_pos, n_junk, (i_pos * n_tokens_all) / n_junk);
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LOG_INF("\n");
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// main loop
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int n_cur = n_tokens_all;
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int n_decode = 0;
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LOG_TEE("%s", prompt_suffix.c_str());
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fflush(stdout);
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LOG_INF("%s", prompt_suffix.c_str());
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const auto t_main_start = ggml_time_us();
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@ -222,13 +224,12 @@ int main(int argc, char ** argv) {
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// is it an end of generation?
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if (llama_token_is_eog(model, new_token_id) || n_cur == n_len) {
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LOG_TEE("\n");
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LOG("\n");
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break;
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}
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LOG_TEE("%s", llama_token_to_piece(ctx, new_token_id).c_str());
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fflush(stdout);
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LOG("%s", llama_token_to_piece(ctx, new_token_id).c_str());
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n_decode += 1;
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@ -243,22 +244,22 @@ int main(int argc, char ** argv) {
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// evaluate the current batch with the transformer model
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if (llama_decode(ctx, batch)) {
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fprintf(stderr, "%s : failed to eval, return code %d\n", __func__, 1);
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LOG_ERR("%s : failed to eval, return code %d\n", __func__, 1);
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return 1;
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}
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}
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LOG_TEE("\n");
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LOG("\n");
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const auto t_main_end = ggml_time_us();
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LOG_TEE("%s: decoded %d tokens in %.2f s, speed: %.2f t/s\n",
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LOG_INF("%s: decoded %d tokens in %.2f s, speed: %.2f t/s\n",
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__func__, n_decode, (t_main_end - t_main_start) / 1000000.0f, n_decode / ((t_main_end - t_main_start) / 1000000.0f));
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LOG_TEE("\n");
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LOG("\n");
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llama_perf_context_print(ctx);
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fprintf(stderr, "\n");
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LOG("\n");
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llama_sampler_free(smpl);
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