Function TEST

runtime/test/instruction/setsubtensor.cpp:7–162

using namespace test;

TEST(INSTRUCTION, SetSubTensorTest) {
    std::vector<Instruction> insts;
    std::vector<std::shared_ptr<Tensor>> in_tensors;
    std::vector<std::shared_ptr<Tensor>> out_tensors;
    std::vector<Tensor*> inputs;

    //! input shape =[20, 20, 20]
    std::vector<float> data(20 * 20 * 20);
    for (size_t i = 0; i < 20 * 20 * 20; i++) {
        data[i] = i;
    }
    auto src_tensor = create_tensor({20, 20, 20}, TinyNN_FLOAT, data.data());

    //! input shape =[20, 20, 20]
    std::vector<float> data_ret(20 * 20 * 20);
    for (size_t i = 0; i < 20 * 20 * 20; i++) {
        data_ret[i] = i;
    }
    auto result_tensor = create_tensor({20, 20, 20}, TinyNN_FLOAT, data_ret.data());

    auto create_setsubtensor = [&](Tensor* value, IndexDesc* index, IndexDesc* flag,
                                   std::vector<uint32_t> scaler_value = {}) {
        auto subtensor = std::make_shared<SubTensor>();
        inputs.clear();
        inputs.push_back(src_tensor.get());
        inputs.push_back(value);
        if (flag->start == 1) {
            in_tensors.push_back(create_scalar_tensor(scaler_value[0], TinyNN_INT));
            inputs.push_back(in_tensors.back().get());
            scaler_value.erase(scaler_value.begin());
        }
        if (flag->end == 1) {
            in_tensors.push_back(create_scalar_tensor(scaler_value[0], TinyNN_INT));
            inputs.push_back(in_tensors.back().get());
            scaler_value.erase(scaler_value.begin());
        }
        if (flag->step == 1) {
            in_tensors.push_back(create_scalar_tensor(scaler_value[0], TinyNN_INT));
            inputs.push_back(in_tensors.back().get());
            scaler_value.erase(scaler_value.begin());
        }
        if (flag->index == 1) {
            in_tensors.push_back(create_scalar_tensor(scaler_value[0], TinyNN_INT));
            inputs.push_back(in_tensors.back().get());
            scaler_value.erase(scaler_value.begin());
        }
        auto output = std::make_shared<Tensor>();
        output->is_dynamic = true;
        out_tensors.push_back(output);

        subtensor->nr_descs = 1;
        subtensor->descs = index;
        subtensor->flags = flag;

        subtensor->nr_input = inputs.size();
        subtensor->inputs = inputs.data();
        subtensor->output = out_tensors.back().get();
        return subtensor;