File size: 2,791 Bytes
a6dd040 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | /*
* Copyright (c) 2020 NVIDIA Corporation.
* Copyright (c) 2018-2020 Chris Choy (chrischoy@ai.stanford.edu).
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
* IN THE SOFTWARE.
*
* Please cite "4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural
* Networks", CVPR'19 (https://arxiv.org/abs/1904.08755) if you use any part
* of the code.
*/
#ifndef POOLING_AVG_CUH
#define POOLING_AVG_CUH
#include <array>
#include <vector>
#include "gpu.cuh"
#include "kernel_map.cuh"
#include "math_functions.cuh"
#include "types.hpp"
namespace minkowski {
template <typename Dtype, typename Itype, typename ByteAllocator>
void NonzeroAvgPoolingForwardKernelGPU(
Dtype const *d_in_feat, //
default_types::size_type const in_nrows, //
Dtype *d_out_feat, //
default_types::size_type const out_nrows, //
Dtype *d_num_nonzero, //
default_types::size_type const nchannel, //
gpu_kernel_map<Itype, ByteAllocator> const &kernel_map, //
bool const use_avg,
ByteAllocator &allocator, //
cusparseHandle_t cushandle, cudaStream_t stream);
template <typename Dtype, typename Itype, typename ByteAllocator>
void NonzeroAvgPoolingBackwardKernelGPU(
Dtype *d_grad_in_feat, //
default_types::size_type const in_nrows, //
Dtype const *d_grad_out_feat, //
default_types::size_type const out_nrows, //
Dtype const *d_num_nonzero, //
default_types::size_type const nchannel, //
gpu_kernel_map<Itype, ByteAllocator> const &kernel_map, bool const use_avg,
cudaStream_t stream);
} // end namespace minkowski
#endif // POOLING_AVG_CUH
|