Method do_setup

examples/graph_shufflenet.cpp:42–154

    {
    }
    bool do_setup(int argc, char **argv) override
    {
        // Parse arguments
        cmd_parser.parse(argc, argv);
        cmd_parser.validate();

        // Consume common parameters
        common_params = consume_common_graph_parameters(common_opts);

        // Return when help menu is requested
        if (common_params.help)
        {
            cmd_parser.print_help(argv[0]);
            return false;
        }

        // Set default layout if needed (Single kernel grouped convolution not yet supported int NHWC)
        if (!common_opts.data_layout->is_set())
        {
            common_params.data_layout = DataLayout::NHWC;
        }

        // Checks
        ARM_COMPUTE_EXIT_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type),
                                "QASYMM8 not supported for this graph");

        // Print parameter values
        std::cout << common_params << std::endl;
        std::cout << "Model: Shufflenet_1_g4" << std::endl;

        // Create model path
        std::string model_path = "/cnn_data/shufflenet_model/";

        // Get trainable parameters data path
        std::string data_path = common_params.data_path;

        // Add model path to data path
        if (!data_path.empty())
        {
            data_path += model_path;
        }

        // Create input descriptor
        const auto        operation_layout = common_params.data_layout;
        const TensorShape tensor_shape =
            permute_shape(TensorShape(224U, 224U, 3U, common_params.batches), DataLayout::NCHW, operation_layout);
        TensorDescriptor input_descriptor =
            TensorDescriptor(tensor_shape, common_params.data_type).set_layout(operation_layout);

        // Set weights trained layout
        const DataLayout weights_layout = DataLayout::NCHW;

        // Create preprocessor
        std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(0);

        graph << common_params.target << common_params.fast_math_hint
              << InputLayer(input_descriptor, get_input_accessor(common_params, std::move(preprocessor),
                                                                 false /* Do not convert to BGR */))