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#ifndef TIM_VX_OPS_GROUPEDCONV2D_H_
#define TIM_VX_OPS_GROUPEDCONV2D_H_

#include <array>

#include "tim/vx/builtin_op.h"

namespace tim {
namespace vx {
namespace ops {

/**
 * ## GroupedConv2d
 *
 * Performs a grouped 2-D convolution operation.
 * 
 * Input:
 * - input [WHCN or CWHN].
 * - kernel [ WHIcOc ] (Ic: Input Channels. Oc: Output Channels).
 * - bias [ O ]. Optional.
 *
 * Attribute:
 * - weights : the output channel number for weight tensor.
 * - ksize : the height and width for weight tensor.
 * - padding : AUTO, VALID or SAME.
 * - pad : pad value for each spatial axis.
 * - stride : stride along each spatial axis.
 * - dilation : dilation value along each spatial axis of the filter.
 * - group_number: Split conv to n group.
 * - layout : WHCN or CWHN.
 */

class GroupedConv2d : public BuiltinOp {
 public:
  GroupedConv2d(Graph* graph, PadType padding,
         const std::array<uint32_t, 2>& strides,
         const std::array<uint32_t, 2>& dilation,
         int32_t grouped_number,
         DataLayout input_layout = DataLayout::WHCN,
         DataLayout kernel_layout = DataLayout::WHIcOc);
  GroupedConv2d(Graph* graph,
         const std::array<uint32_t, 4>& pad,
         const std::array<uint32_t, 2>& strides,
         const std::array<uint32_t, 2>& dilation,
         int32_t group_number,
         DataLayout input_layout = DataLayout::WHCN,
         DataLayout kernel_layout = DataLayout::WHIcOc);

  DataLayout KernelDataLayout() { return kernel_layout_; }

  std::shared_ptr<Operation> Clone(std::shared_ptr<Graph>& graph) const override;

 protected:
  const PadType padding_;
  const std::array<uint32_t, 2> strides_;
  const std::array<uint32_t, 2> dilation_;
  const std::array<uint32_t, 4> pad_;
  const int32_t group_number_;
  const DataLayout kernel_layout_;
};

}  // namespace ops
}  // namespace vx
}  // namespace tim

#endif /* TIM_VX_OPS_GROUPED_CONV2D_H_ */