Method darknet53_block

examples/graph_yolov3.cpp:529–571

    }

    void darknet53_block(const std::string &data_path,
                         std::string      &&param_path,
                         DataLayout         weights_layout,
                         unsigned int       filter_size)
    {
        std::string total_path = "/cnn_data/yolov3_model/";
        std::string param_path2 =
            arm_compute::support::cpp11::to_string(arm_compute::support::cpp11::stoi(param_path) + 1);
        SubStream i_a(graph);
        SubStream i_b(graph);
        i_a << ConvolutionLayer(
                   1U, 1U, filter_size,
                   get_weights_accessor(data_path, total_path + "conv2d_" + param_path + "_w.npy", weights_layout),
                   std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 0, 0))
                   .set_name("conv2d_" + param_path + "/Conv2D")
            << BatchNormalizationLayer(
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path + "_mean.npy"),
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path + "_var.npy"),
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path + "_gamma.npy"),
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path + "_beta.npy"),
                   0.000001f)
                   .set_name("conv2d_" + param_path + "/BatchNorm")
            << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU, 0.1f))
                   .set_name("conv2d_" + param_path + "/LeakyRelu")
            << ConvolutionLayer(
                   3U, 3U, filter_size * 2,
                   get_weights_accessor(data_path, total_path + "conv2d_" + param_path2 + "_w.npy", weights_layout),
                   std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 1, 1))
                   .set_name("conv2d_" + param_path2 + "/Conv2D")
            << BatchNormalizationLayer(
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path2 + "_mean.npy"),
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path2 + "_var.npy"),
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path2 + "_gamma.npy"),
                   get_weights_accessor(data_path, total_path + "batch_normalization_" + param_path2 + "_beta.npy"),
                   0.000001f)
                   .set_name("conv2d_" + param_path2 + "/BatchNorm")
            << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU, 0.1f))
                   .set_name("conv2d_" + param_path2 + "/LeakyRelu");

        graph << EltwiseLayer(std::move(i_a), std::move(i_b), EltwiseOperation::Add)
                     .set_name("")
                     .set_name("add_" + param_path + "_" + param_path2);
    }
};

/** Main program for YOLOv3