Add comment for llama_log_callback and replace remaining printf calls
This commit is contained in:
grahameth
parent
c857a33b19
commit
98369f62c5
2 changed files with 27 additions and 21 deletions
42
llama.cpp
42
llama.cpp
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@ -1766,7 +1766,7 @@ static struct ggml_cgraph * llama_build_graph(
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}
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#if 0
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printf("\n%s: used_mem: eval ctx %.3f MB, scratch %.3f MB %.3f MB, work buf %.3f MB, n_past = %d, N = %d\n", __func__,
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LLAMA_LOG_INFO("\n%s: used_mem: eval ctx %.3f MB, scratch %.3f MB %.3f MB, work buf %.3f MB, n_past = %d, N = %d\n", __func__,
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ggml_used_mem(ctx0)/1024.0/1024.0,
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lctx.get_buf_max_mem(0)/1024.0/1024.0,
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lctx.get_buf_max_mem(1)/1024.0/1024.0,
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@ -1827,7 +1827,7 @@ static bool llama_eval_internal(
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ggml_allocr_alloc_graph(lctx.alloc, gf);
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#endif
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// fprintf(stderr, "graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
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// LLAMA_LOG_INFO("graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
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// for big prompts, if BLAS is enabled, it is better to use only one thread
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// otherwise, the threads are spin-lock waiting for the BLAS calls and are degrading the performance
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@ -2014,7 +2014,7 @@ struct llama_tokenizer {
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left_sym.n += right_sym.n;
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right_sym.n = 0;
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//printf("left = '%*s' size = %zu\n", (int) left_sym.n, left_sym.text, bigram.size);
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//LLAMA_LOG_INFO("left = '%*s' size = %zu\n", (int) left_sym.n, left_sym.text, bigram.size);
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// remove the right sym from the chain
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left_sym.next = right_sym.next;
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@ -3022,7 +3022,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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tensor.data = read_data.addr;
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model_loader->load_data_for(tensor);
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printf("[%4zu/%4zu] %36s - %16s, type = %6s, ",
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LLAMA_LOG_INFO("[%4zu/%4zu] %36s - %16s, type = %6s, ",
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++idx, model_loader->tensors_map.tensors.size(),
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tensor.name.c_str(), llama_format_tensor_shape(tensor.ne).c_str(),
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ggml_type_name(tensor.type));
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@ -3044,7 +3044,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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new_type = tensor.type;
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new_data = tensor.data;
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new_size = tensor.size;
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printf("size = %8.3f MB\n", tensor.size/1024.0/1024.0);
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LLAMA_LOG_INFO("size = %8.3f MB\n", tensor.size/1024.0/1024.0);
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} else {
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new_type = quantized_type;
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#ifdef GGML_USE_K_QUANTS
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@ -3109,7 +3109,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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f32_data = (float *) f32_conv_buf.addr;
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}
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printf("quantizing to %s .. ", ggml_type_name(new_type));
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LLAMA_LOG_INFO("quantizing to %s .. ", ggml_type_name(new_type));
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fflush(stdout);
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work.resize(nelements * 4); // upper bound on size
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@ -3159,7 +3159,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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}
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}
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printf("size = %8.2f MB -> %8.2f MB | hist: ", tensor.size/1024.0/1024.0, new_size/1024.0/1024.0);
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LLAMA_LOG_INFO("size = %8.2f MB -> %8.2f MB | hist: ", tensor.size/1024.0/1024.0, new_size/1024.0/1024.0);
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int64_t tot_count = 0;
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for (size_t i = 0; i < hist_cur.size(); i++) {
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hist_all[i] += hist_cur[i];
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@ -3168,18 +3168,18 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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if (tot_count > 0) {
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for (size_t i = 0; i < hist_cur.size(); i++) {
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printf("%5.3f ", hist_cur[i] / float(nelements));
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LLAMA_LOG_INFO("%5.3f ", hist_cur[i] / float(nelements));
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}
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}
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printf("\n");
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LLAMA_LOG_INFO("\n");
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}
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total_size_org += tensor.size;
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total_size_new += new_size;
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file_saver.write_tensor(tensor, new_type, new_data, new_size);
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}
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printf("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
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printf("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);
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LLAMA_LOG_INFO("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
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LLAMA_LOG_INFO("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);
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{
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int64_t sum_all = 0;
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@ -3188,11 +3188,11 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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}
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if (sum_all > 0) {
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printf("%s: hist: ", __func__);
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LLAMA_LOG_INFO("%s: hist: ", __func__);
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for (size_t i = 0; i < hist_all.size(); i++) {
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printf("%5.3f ", hist_all[i] / float(sum_all));
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LLAMA_LOG_INFO("%5.3f ", hist_all[i] / float(sum_all));
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}
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printf("\n");
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LLAMA_LOG_INFO("\n");
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}
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}
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}
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@ -3250,10 +3250,9 @@ struct llama_context * llama_new_context_with_model(
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unsigned percentage = (unsigned) (100 * progress);
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while (percentage > *cur_percentage_p) {
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*cur_percentage_p = percentage;
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fprintf(stderr, ".");
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fflush(stderr);
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LLAMA_LOG_INFO(".");
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if (percentage >= 100) {
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fprintf(stderr, "\n");
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LLAMA_LOG_INFO("\n");
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}
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}
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};
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@ -3308,14 +3307,14 @@ struct llama_context * llama_new_context_with_model(
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// measure memory requirements for the graph
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size_t alloc_size = ggml_allocr_alloc_graph(ctx->alloc, gf) + tensor_alignment;
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fprintf(stderr, "%s: compute buffer total size = %7.2f MB\n", __func__, (ctx->buf_compute.size + alloc_size) / 1024.0 / 1024.0);
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LLAMA_LOG_INFO("%s: compute buffer total size = %7.2f MB\n", __func__, (ctx->buf_compute.size + alloc_size) / 1024.0 / 1024.0);
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// debug - for comparison with scratch buffer
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//size_t prev_req =
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// MEM_REQ_SCRATCH0(hparams.n_ctx).at(ctx->model.type) +
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// MEM_REQ_SCRATCH1().at(ctx->model.type) +
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// MEM_REQ_EVAL().at(ctx->model.type);
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//fprintf(stderr, "%s: (debug) equivalent with scratch buffer = %7.2f MB\n", __func__, prev_req / 1024.0 / 1024.0);
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//LLAMA_LOG_INFO("%s: (debug) equivalent with scratch buffer = %7.2f MB\n", __func__, prev_req / 1024.0 / 1024.0);
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// recreate allocator with exact memory requirements
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ggml_allocr_free(ctx->alloc);
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@ -3679,7 +3678,7 @@ int llama_apply_lora_from_file_internal(const struct llama_model & model, const
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n_tensors++;
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if (n_tensors % 4 == 0) {
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fprintf(stderr, ".");
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LLAMA_LOG_INFO(".");
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}
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}
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}
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@ -4316,5 +4315,6 @@ static void llama_log_internal(llama_log_level level, const char * format, ...)
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static void llama_log_callback_default(llama_log_level level, const char * text, void * user_data) {
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(void) level;
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(void) user_data;
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fprintf(stderr, "%s", text);
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fputs(text, stderr);
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fflush(stderr);
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}
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6
llama.h
6
llama.h
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@ -91,6 +91,12 @@ extern "C" {
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LLAMA_LOG_LEVEL_WARN = 3,
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LLAMA_LOG_LEVEL_INFO = 4
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};
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// Signature for logging events
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// Note that text includes the new line character at the end for most events.
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// If your logging mechanism cannot handle that, check if the last character is '\n' and strip it
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// if it exists.
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// It might not exist for progress report where '.' is output repeatedly.
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typedef void (*llama_log_callback)(llama_log_level level, const char * text, void * user_data);
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struct llama_context_params {
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