Function TEST_CASE

tests/validation/CL/MatMulLowpNativeKernel.cpp:82–113

TEST_SUITE(Validate)

TEST_CASE(SupportedKernelConfigurations, framework::DatasetMode::ALL)
{
    using MatMulConfigurationPair = std::pair<MatMulKernelInfo, bool>;

    const std::vector<MatMulConfigurationPair> supported_block_sizes = {
        // MatMulKernelInfo(adj_lhs, adj_rhs, M0, N0, K0, export_rhs_to_cl_image = false)
        // Lhs not-transposed, Rhs-not-transposed
        {MatMulKernelInfo(false, false, 0, 1, 1), false},  // M0 should be > 0
        {MatMulKernelInfo(false, false, 3, 5, 1), false},  // N0 not in {1, 2, 3, 4, 8, 16}
        {MatMulKernelInfo(false, false, 3, 6, 1), false},  // N0 not in {1, 2, 3, 4, 8, 16}
        {MatMulKernelInfo(false, false, 3, 3, 17), false}, // K0 not in {1, 2, 3, 4, 8, 16}
        {MatMulKernelInfo(false, false, 3, 3, 7), false},  // K0 not in {1, 2, 3, 4, 8, 16}
        {MatMulKernelInfo(false, false, 9, 1, 2), true},
        {MatMulKernelInfo(false, false, 3, 16, 3), true},
        {MatMulKernelInfo(false, false, 7, 3, 4), true},
        {MatMulKernelInfo(false, false, 7, 3, 4, true), true}, // export to CLImage is unsupported for quantized types
    };

    // Set big enough shapes so that block sizes are not truncated. Also, set all dimensions equal
    // so that it doesn't fail for different NT/T configurations. We aim to test the block sizes here,
    // not the shapes themselves.
    const TensorInfo lhs_info = TensorInfo(TensorShape(100U, 100U), 1, DataType::QASYMM8_SIGNED);
    const TensorInfo rhs_info = TensorInfo(TensorShape(100U, 100U), 1, DataType::QASYMM8_SIGNED);

    for (auto &pair : supported_block_sizes)
    {
        TensorInfo output_info;
        Status     status = ClMatMulLowpNativeKernel::validate(&lhs_info, &rhs_info, nullptr, &output_info, pair.first);

        ARM_COMPUTE_EXPECT(bool(status) == pair.second, framework::LogLevel::ERRORS);
    }
}

TEST_CASE(ValidateInputShapes, framework::DatasetMode::ALL)
{