TIM-VX/include/tim/vx/ops/groupedconv2d.h

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3.1 KiB
C++

/****************************************************************************
*
* Copyright (c) 2020-2023 Vivante Corporation
*
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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_ */