Function TEST_CASE

tests/validation/NEON/GEMMLowp.cpp:211–258

Test case for memory injection in @ref cpu::CpuGemmLowpMatrixMultiplyCore. * * Configure the operator once and inject memory at run-time in multiple executions. * * Checks performed in order: * - Both runs compute the same output */

 * - Both runs compute the same output
 */
TEST_CASE(MemoryInjection, framework::DatasetMode::ALL)
{
    auto gemm     = std::make_unique<cpu::CpuGemmLowpMatrixMultiplyCore>();
    auto a_info   = TensorInfo(TensorShape(32U, 72U), 1, DataType::QASYMM8);
    auto b_info   = TensorInfo(TensorShape(17U, 32U), 1, DataType::QASYMM8);
    auto dst_info = TensorInfo(TensorShape(17U, 72U), 1, DataType::S32);
    a_info.set_quantization_info(QuantizationInfo(1.0f / 255, -9));
    b_info.set_quantization_info(QuantizationInfo(1.0f / 255, 1));
    const auto gemm_info = GEMMInfo{};
    gemm->configure(&a_info, &b_info, nullptr, &dst_info, gemm_info);

    // telhs are newly created every call of this lambda function
    auto a   = create_tensor<Tensor>(a_info);
    auto b   = create_tensor<Tensor>(b_info);
    auto dst = create_tensor<Tensor>(dst_info);
    a.allocator()->allocate();
    b.allocator()->allocate();
    dst.allocator()->allocate();

    ITensorPack run_pack  = {{TensorType::ACL_SRC_0, &a}, {TensorType::ACL_SRC_1, &b}, {TensorType::ACL_DST, &dst}};
    ITensorPack prep_pack = {
        {TensorType::ACL_SRC_1, &b},
    };

    auto mg = MemoryGroup{};
    auto ws = manage_workspace<Tensor>(gemm->workspace(), mg, run_pack, prep_pack);

    auto run_conv = [&]() -> Tensor
    {
        auto dst = create_tensor<Tensor>(dst_info);
        dst.allocator()->allocate();
        run_pack.add_tensor(TensorType::ACL_DST, &dst);

        library->fill_tensor_value(Accessor(a), static_cast<uint8_t>(1));
        library->fill_tensor_value(Accessor(b), static_cast<uint8_t>(2));
        // This operator is configured once and captured by this lambda.
        gemm->prepare(prep_pack);
        gemm->run(run_pack);
        return dst;
    };
    auto result_0 = run_conv();
    auto result_1 = run_conv();
    for (size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i)
    {
        ARM_COMPUTE_EXPECT(((uint8_t *)result_0.buffer())[i] == ((uint8_t *)result_1.buffer())[i],
                           framework::LogLevel::ERRORS);
    }
}

/** Test case for memory injection in @ref NEGEMMLowpMatrixMultiplyCore.
 *