src/model/operation/pooling.h

#ifndef SINGA_MODEL_OPERATION_POOLING_H_
#define SINGA_MODEL_OPERATION_POOLING_H_

#include <string>
#include "singa/core/tensor.h"

#ifdef USE_MKLDNN
#include <mkldnn.hpp>
#endif // USE_MKLDNN

#ifdef USE_CUDNN
#include <cudnn.h>
#include "../layer/cudnn_utils.h"
#endif

namespace singa {

class PoolingHandle {
 public:
  PoolingHandle(const Tensor &input, const std::vector<int>& kernel_size,
                const std::vector<int>& stride, const std::vector<int>& padding,
                const bool is_max = true);
  ~PoolingHandle();

  int kernel_w;
  int pad_w;
  int stride_w;
  int kernel_h;
  int pad_h;
  int stride_h;

  int batchsize;
  int channels;
  int height;
  int width;

  int pooled_height;
  int pooled_width;

  bool is_max_pooling;

#ifdef USE_MKLDNN
  mkldnn::memory::data_type dtype;
  mkldnn::memory::dims x_dims;
  mkldnn::memory::dims y_dims;
  mkldnn::memory::dims s_dims;
  mkldnn::memory::dims k_dims;
  mkldnn::memory::dims p_dims;
  mkldnn::algorithm pooling_algo;
  const mkldnn::memory::desc *x_md = nullptr;
  const mkldnn::memory::desc *y_md = nullptr;
  const mkldnn::pooling_forward::desc *pool_fwd_d = nullptr;
  const mkldnn::pooling_forward::primitive_desc *pool_fwd_pd = nullptr;
  const mkldnn::memory::primitive_desc *pool_ws_d = nullptr;
  const mkldnn::memory *ws_mem = nullptr;
#endif // USE_MKLDNN
};

#ifdef USE_MKLDNN

Tensor CpuPoolingForward(const PoolingHandle &ph, const Tensor &x);
Tensor CpuPoolingBackward(const PoolingHandle &ph, const Tensor &dy,
                          const Tensor& x, const Tensor& y);

#endif // USE_MKLDNN

#ifdef USE_CUDNN
class CudnnPoolingHandle : public PoolingHandle {
 public:
  CudnnPoolingHandle(const Tensor &input, const std::vector<int>& kernel_size,
                     const std::vector<int>& stride, const std::vector<int>& padding,
                     const bool is_max = true);
  ~CudnnPoolingHandle();

  cudnnTensorDescriptor_t x_desc = nullptr;
  cudnnTensorDescriptor_t y_desc = nullptr;
  cudnnPoolingDescriptor_t pool_desc = nullptr;
  cudnnNanPropagation_t nan_prop = CUDNN_PROPAGATE_NAN;

};

Tensor GpuPoolingForward(const CudnnPoolingHandle &cph, const Tensor &x);

Tensor GpuPoolingBackward(const CudnnPoolingHandle &cph, const Tensor &dy,
                          const Tensor& x, const Tensor& y);

#endif  //USE_CUDNN

}  // namespace singa

#endif  // SINGA_MODEL_OPERATION_POOLING_H_