Method do_setup

examples/neon_matmul.cpp:35–96

{
public:
    bool do_setup(int argc, char **argv) override
    {
        size_t m = 4096;
        size_t n = 4096;
        size_t k = 128;

        if (argc == 4)
        {
            try
            {
                m = std::stoul(argv[1]);
                n = std::stoul(argv[2]);
                k = std::stoul(argv[3]);
            }
            catch (const std::exception &e)
            {
                ARM_COMPUTE_ERROR(e.what());
                return false;
            }
        }
        else if (argc != 1)
        {
            ARM_COMPUTE_ERROR("Invalid number of arguments. Usage:\n"
                              "<M> <N> <K>\n");
            return false;
        }

        const TensorInfo a_info{TensorShape{k, m}, 1, DataType::F32, DataLayout::NHWC};
        const TensorInfo b_info{TensorShape{n, k}, 1, DataType::F32, DataLayout::NHWC};
        const TensorInfo output_info{TensorShape{n, m}, 1, DataType::F32, DataLayout::NHWC};

        a.allocator()->init(a_info);
        b.allocator()->init(b_info);
        output.allocator()->init(output_info);

        a.info()->set_are_values_constant(false);
        b.info()->set_are_values_constant(false);
        output.info()->set_are_values_constant(false);

        const MatMulInfo        info;
        const CpuMatMulSettings settings;

        auto status = NEMatMul::validate(a.info(), b.info(), output.info(), info, settings);
        if (status.error_code() != ErrorCode::OK)
        {
            ARM_COMPUTE_ERROR(status.error_description().c_str());
            return false;
        }

        matmul.configure(&a, &b, &output, info, settings);
        a.allocator()->allocate();
        b.allocator()->allocate();
        output.allocator()->allocate();

        // Fill with fixed values
        const std::vector<float> values_a(m * k, 2.2f);
        const std::vector<float> values_b(n * k, 3.5f);
        fill_tensor_vector(a, values_a);