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#ifndef TENSORFLOW_KERNELS_TILE_OPS_H_
#define TENSORFLOW_KERNELS_TILE_OPS_H_
#include "tensorflow/core/platform/port.h"
#include "tensorflow/core/framework/tensor_types.h"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
namespace tensorflow {
namespace functor {
template <typename Device, typename T, int NDIM>
struct Tile {
void operator()(const Device& d, typename TTypes<T, NDIM>::Tensor out,
typename TTypes<T, NDIM>::ConstTensor in,
const Eigen::array<int32, NDIM>& broadcast_array) const {
out.device(d) = in.broadcast(broadcast_array);
}
};
template <typename Device, typename T, int NDIM>
struct TileGrad {
void operator()(const Device& d, typename TTypes<T, NDIM>::Tensor out,
typename TTypes<T, NDIM>::ConstTensor in,
const Eigen::DSizes<ptrdiff_t, NDIM>& indices,
const Eigen::DSizes<ptrdiff_t, NDIM>& sizes,
bool first) const {
if (first) {
out.device(d) = in.slice(indices, sizes);
} else {
out.device(d) += in.slice(indices, sizes);
}
}
};
template <typename Device, typename T, int NDIM, int REDUCEDNDIM>
struct ReduceAndReshape {
void operator()(const Device& d, typename TTypes<T, NDIM>::Tensor out,
typename TTypes<T, NDIM>::ConstTensor in,
const Eigen::DSizes<ptrdiff_t, REDUCEDNDIM>& reduce_dim,
const Eigen::DSizes<ptrdiff_t, NDIM>& reshape_dim) const {
out.device(d) = in.sum(reduce_dim).reshape(reshape_dim);
}
};
} // end namespace functor
} // end namespace tensorflow
#endif // TENSORFLOW_KERNELS_TILE_OPS_H_
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