/**
 *  \brief main function to run fix Inferencer
 *  \author Mingzhe Jiang
 *  \copyright 2020 Kneron Inc. All right reserved.
 */


#include "KL730Inferencer.h"
#include <math.h>
#include <unordered_map>
#include <vector>
#include <memory>
//example code, in case users want to use dump and parser functions in this header
//#include "run_fix_inferencer.h"
#include "iostream"

using namespace std;
using std::string;
using std::vector;
using std::unordered_map;
using std::unique_ptr;
using std::shared_ptr;
using namespace dynasty::inferencer;
using namespace dynasty::inferencer::fix_point;


/**
 * This is an example of how to use dynamic fixed point inference.
 * The inferencer output will contain all layer dump if dump level >0, else only the output layer
 * user might need to write his own dump function for different dump purpose, can take run_fix_reference as an example
 * configration parser is also up to user's choice. Can be json or command line params.
 * @param argc
 * @param argv
 * @return
 */

int main(int argc, char *argv[]) {
    {
            bool cuda_en = false;   //enable cuda if cuda library is installed. don't enable if no cuda ata ll
            string model_file_730 = "res/KL730/Mul/output/00011_Mul_inputFM1_1x8x4x4x0x0_inputFM2_1x8x4x4x0x0_1inputs_B0_v0.5.kdp730.scaled.bie";

            //get only output node with dump_level = 0; get all layer dump with dump_level = 2
            int dump_level = 0;
            const float EPSILON = 0.8;  // Max difference tolerance between 520 result and 720 result


            unordered_map<string, string> inference_input_730;
            string input_name_730 = "0";
            string input_path_730 = "res/KL730/Mul/input/simulator_input/test_input.txt";
            inference_input_730[input_name_730] = input_path_730;

            // Inference with 730: cuda disabled
            auto builder = kl730::Inferencer::GetBuilder();
            auto inferencer_730 = kl730::createInferencer(builder.get(), model_file_730,cuda_en, 0);

             unordered_map<std::string, std::vector<float>> float_outputs_730 = inferencer_730->Inference(inference_input_730, dump_level);
             unordered_map<std::string, std::vector<int>> fix_outputs_730 = inferencer_730->ConvertFloatToInt(float_outputs_730, dump_level);

             auto input_dim_730 = builder->GetInputDimensions();
             for(auto& item: input_dim_730) {
                 cout << "input node name: " << item.first << ", shape: ";
                 for(auto num: item.second) cout<< num <<", ";
                 cout << endl;
             }
             cout << "inference with 730 completed" << endl;


            cout << "Done!" << endl;

        return 0;
    }
}