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#ifndef TIM_VX_OPS_CONV3D_H_
#define TIM_VX_OPS_CONV3D_H_

#include <array>
#include "tim/vx/builtin_op.h"

namespace tim {
namespace vx {
namespace ops {

/**
 * ## Conv3d
 *
 * Performs a 3-D convolution operation
 * 
 * Input:
 * - input [WHDCN].
 * - kernel [ WHDIcOc ] (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. (left, right, top, bottom, front, rear).
 * - stride : stride along each spatial axis.
 * - dilation : dilation value along each spatial axis of the filter.
 * - multiplier: function similar to group attribute on other framework,
 * but the value is different. multiplier = weights / group.
 * - input_layout : WHDCN or WHCDN.
 * - kernel_layout : WHDIcOc
 */

class Conv3d : public BuiltinOp {
 public:
  Conv3d(Graph* graph, PadType padding,
         const std::array<int32_t, 3>& stride,
         const std::array<int32_t, 3>& dilation, int32_t multiplier = 0,
         DataLayout input_layout = DataLayout::WHDCN,
         DataLayout kernel_layout = DataLayout::WHDIcOc);
  Conv3d(Graph* graph, const std::array<int32_t, 6> pad,
         const std::array<int32_t, 3>& stride,
         const std::array<int32_t, 3>& dilation, int32_t multiplier = 0,
         DataLayout input_layout = DataLayout::WHDCN,
         DataLayout kernel_layout = DataLayout::WHDIcOc);
  Conv3d(Graph* graph, int32_t weights, PadType padding,
         const std::array<int32_t, 3>& ksize,
         const std::array<int32_t, 3>& stride,
         const std::array<int32_t, 3>& dilation, int32_t multiplier = 0,
         DataLayout input_layout = DataLayout::WHDCN,
         DataLayout kernel_layout = DataLayout::WHDIcOc);
  Conv3d(Graph* graph, int32_t weights, PadType padding,
         const std::array<int32_t, 3>& ksize,
         const std::array<int32_t, 3>& stride,
         const std::array<int32_t, 3>& dilation,
         const std::array<int32_t, 6>& pad, int32_t multiplier = 0,
         DataLayout input_layout = DataLayout::WHDCN,
         DataLayout kernel_layout = DataLayout::WHDIcOc);

  DataLayout KernelDataLayout() { return kernel_layout_; }

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

 protected:
  const int32_t weights_;
  const PadType padding_;
  const std::array<int32_t, 3> ksize_;
  const std::array<int32_t, 3> stride_;
  const std::array<int32_t, 3> dilation_;
  const std::array<int32_t, 6> pad_;
  const int32_t multiplier_;
  const DataLayout kernel_layout_;
};

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

#endif /* TIM_VX_OPS_CONV3D_H_ */