Function llama_dump_timing_info_yaml

llama.cpp:10887–10913

}

void llama_dump_timing_info_yaml(FILE * stream, const llama_context * ctx) {
    fprintf(stream, "\n");
    fprintf(stream, "###########\n");
    fprintf(stream, "# Timings #\n");
    fprintf(stream, "###########\n");
    fprintf(stream, "\n");

    fprintf(stream, "mst_eval: %.2f  # ms / token during generation\n",
            1.0e-3 * ctx->t_eval_us / ctx->n_eval);
    fprintf(stream, "mst_p_eval: %.2f  # ms / token during prompt processing\n",
            1.0e-3 * ctx->t_p_eval_us / ctx->n_p_eval);
    fprintf(stream, "mst_sample: %.2f  # ms / token during sampling\n",
            1.0e-3 * ctx->t_sample_us / ctx->n_sample);
    fprintf(stream, "n_eval: %d  # number of tokens generated (excluding the first one)\n", ctx->n_eval);
    fprintf(stream, "n_p_eval: %d  # number of tokens processed in batches at the beginning\n", ctx->n_p_eval);
    fprintf(stream, "n_sample: %d  # number of sampled tokens\n", ctx->n_sample);
    fprintf(stream, "t_eval_us: %" PRId64 "  # total microseconds spent generating tokens\n", ctx->t_eval_us);
    fprintf(stream, "t_load_us: %" PRId64 "  # total microseconds spent loading the model\n", ctx->t_load_us);
    fprintf(stream, "t_p_eval_us: %" PRId64 "  # total microseconds spent prompt processing\n", ctx->t_p_eval_us);
    fprintf(stream, "t_sample_us: %" PRId64 "  # total microseconds spent sampling\n", ctx->t_sample_us);
    fprintf(stream, "ts_eval: %.2f  # tokens / second during generation\n",
            1.0e6 * ctx->n_eval / ctx->t_eval_us);
    fprintf(stream, "ts_p_eval: %.2f  # tokens / second during prompt processing\n",
            1.0e6 * ctx->n_p_eval / ctx->t_p_eval_us);
    fprintf(stream, "ts_sample: %.2f  # tokens / second during sampling\n",
            1.0e6 * ctx->n_sample / ctx->t_sample_us);
}

// For internal test use
const std::vector<std::pair<std::string, struct ggml_tensor *>> & llama_internal_get_tensor_map(