Function get_input_data

lite/test/test_common.h:60–90

}

__attribute__((unused)) static std::shared_ptr<Tensor> get_input_data(
        std::string path) {
    std::string type_str;
    std::vector<npy::ndarray_len_t> stl_shape;
    std::vector<int8_t> raw;
    npy::LoadArrayFromNumpy(path, type_str, stl_shape, raw);
    auto lite_tensor = std::make_shared<Tensor>(LiteDeviceType::LITE_CPU);
    Layout layout;
    layout.ndim = stl_shape.size();
    const std::map<std::string, LiteDataType> type_map = {
            {"f4", LiteDataType::LITE_FLOAT},  {"f2", LiteDataType::LITE_HALF},
            {"i8", LiteDataType::LITE_INT64},  {"i4", LiteDataType::LITE_INT},
            {"u4", LiteDataType::LITE_UINT},   {"i2", LiteDataType::LITE_INT16},
            {"u2", LiteDataType::LITE_UINT16}, {"i1", LiteDataType::LITE_INT8},
            {"u1", LiteDataType::LITE_UINT8}};
    layout.shapes[0] = 1;
    for (size_t i = 0; i < stl_shape.size(); i++) {
        layout.shapes[i] = static_cast<size_t>(stl_shape[i]);
    }
    for (auto& item : type_map) {
        if (type_str.find(item.first) != std::string::npos) {
            layout.data_type = item.second;
            break;
        }
    }
    lite_tensor->set_layout(layout);
    size_t length = lite_tensor->get_tensor_total_size_in_byte();
    void* dest = lite_tensor->get_memory_ptr();
    memcpy(dest, raw.data(), length);
    return lite_tensor;
}

__attribute__((unused)) static std::shared_ptr<Tensor> mgelite_lar(
        std::string model_path, const Config& config, std::string,