Function main

tests/bin/test_convert_calibration.cpp:56–219

}

int main(int argc, char* argv[])
{
    int res;

    while((res = getopt(argc, argv, "r:")) != -1)
    {
        switch(res)
        {
            case 'r':
                repeat_count = strtoul(optarg, NULL, 10);
                break;
            default:
                break;
        }
    }

    // const char * model_name="mobilenet";
    int img_h = 224;
    int img_w = 224;

    /* prepare input data */
    float* input_data = ( float* )malloc(sizeof(float) * img_h * img_w * 3);
    get_input_data(image_file, input_data, img_h, img_w, channel_mean, 0.017);
    int img_size = img_h * img_w * 3;
    float in_scale = 0;
    int in_zero = 0;
    init_tengine();

    if(request_tengine_version("0.9") < 0)
        return 1;

    graph_t graph = create_graph(nullptr, "tengine", text_file);

    if(graph == nullptr)
    {
        std::cout << "Create graph0 failed\n";
        return -1;
    }

    /* get input tensor */
    int node_idx = 0;
    int tensor_idx = 0;

    tensor_t input_tensor = get_graph_input_tensor(graph, node_idx, tensor_idx);
    if(input_tensor == nullptr)
    {
        std::printf("Cannot find input tensor,node_idx: %d,tensor_idx: %d\n", node_idx, tensor_idx);
        return -1;
    }
    
	get_tensor_quant_param(input_tensor,&in_scale,&in_zero,1);
	
	int8_t * input_s8 = (int8_t*)malloc(sizeof(int8_t) * img_size);
	
	for(int i = 0; i < img_size;i++)
	{
		input_s8[i] = round(input_data[i] / in_scale);
	}