/* Copyright (c) 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 CONVOLUTION_CUH #define CONVOLUTION_CUH #include #include #include "gpu.cuh" #include "kernel_map.cuh" #include "math_functions.cuh" #include "types.hpp" namespace minkowski { template void ConvolutionForwardKernelGPU( Dtype const *d_in_feat, // default_types::size_type const in_nchannel, // Dtype *d_out_feat, // default_types::size_type const out_nchannel, // Dtype *d_kernel, gpu_kernel_map const &kernel_map, default_types::size_type const in_nrows, // default_types::size_type const out_nrows, // ByteAllocator &allocator, // MinkowskiAlgorithm::Mode const algo_index, // ConvolutionMode::Type const convolution_mode, // cublasHandle_t cuhandle, cudaStream_t stream); template void ConvolutionBackwardKernelGPU( Dtype const *d_in_feat, // Dtype *d_grad_in_feat, // default_types::size_type const in_nchannel, // Dtype const *d_grad_out_feat, // default_types::size_type const out_nchannel, // Dtype const *d_kernel, // Dtype *d_grad_kernel, // gpu_kernel_map const &kernel_map, default_types::size_type const in_nrows, // default_types::size_type const out_nrows, // ByteAllocator &allocator, // MinkowskiAlgorithm::Mode const algo_index, // ConvolutionMode::Type const convolution_mode, // cublasHandle_t cuhandle, cudaStream_t stream); } // end namespace minkowski #endif // end CONVOLUTION_CUH