Class ConvolutionLayer

arm_compute/graph/frontend/Layers.h:377–433

Convolution Layer */

/** Convolution Layer */
class ConvolutionLayer final : public ILayer
{
public:
    /** Construct a convolution layer.
     *
     * @param[in] conv_width         Convolution width.
     * @param[in] conv_height        Convolution height.
     * @param[in] ofm                Output feature map.
     * @param[in] weights            Accessor to get kernel weights from.
     * @param[in] bias               Accessor to get kernel bias from.
     * @param[in] conv_info          Padding and stride information.
     * @param[in] num_groups         (Optional) Number of groups. Default: 1.
     * @param[in] weights_quant_info (Optional) Weights quantization information
     * @param[in] out_quant_info     (Optional) Output quantization info
     */
    ConvolutionLayer(unsigned int           conv_width,
                     unsigned int           conv_height,
                     unsigned int           ofm,
                     ITensorAccessorUPtr    weights,
                     ITensorAccessorUPtr    bias,
                     PadStrideInfo          conv_info,
                     unsigned int           num_groups         = 1,
                     const QuantizationInfo weights_quant_info = QuantizationInfo(),
                     const QuantizationInfo out_quant_info     = QuantizationInfo())
        : _conv_width(conv_width),
          _conv_height(conv_height),
          _ofm(ofm),
          _conv_info(std::move(conv_info)),
          _num_groups(num_groups),
          _weights(std::move(weights)),
          _bias(std::move(bias)),
          _weights_quant_info(std::move(weights_quant_info)),
          _out_quant_info(std::move(out_quant_info))
    {
    }

    NodeID create_layer(IStream &s) override
    {
        NodeIdxPair input         = {s.tail_node(), 0};
        NodeParams  common_params = {name(), s.hints().target_hint};
        return GraphBuilder::add_convolution_node(s.graph(), common_params, input, Size2D(_conv_width, _conv_height),
                                                  _ofm, _conv_info, _num_groups, s.hints().convolution_method_hint,
                                                  s.hints().fast_math_hint, std::move(_weights), std::move(_bias),
                                                  std::move(_weights_quant_info), std::move(_out_quant_info));
    }

private:
    unsigned int           _conv_width;
    unsigned int           _conv_height;
    unsigned int           _ofm;
    const PadStrideInfo    _conv_info;
    unsigned int           _num_groups;
    ITensorAccessorUPtr    _weights;
    ITensorAccessorUPtr    _bias;
    const QuantizationInfo _weights_quant_info;
    const QuantizationInfo _out_quant_info;
};