/* * 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. */ #include "coordinate_map.hpp" #include "coordinate_map_cpu.hpp" #include "coordinate_map_key.hpp" #include "coordinate_map_manager.hpp" #include "errors.hpp" #include "types.hpp" #include "utils.hpp" #include "convolution_kernel.hpp" #include #include namespace minkowski { template at::Tensor ConvolutionForwardCPU(at::Tensor const &in_feat, // at::Tensor const &kernel, // default_types::stride_type const &kernel_size, // default_types::stride_type const &kernel_stride, // default_types::stride_type const &kernel_dilation, // RegionType::Type const region_type, // at::Tensor const &offset, // bool const expand_coordinates, // ConvolutionMode::Type const convolution_mode, // CoordinateMapKey *p_in_map_key, // CoordinateMapKey *p_out_map_key, // cpu_manager_type *p_map_manager) { ASSERT(in_feat.is_contiguous(), "in_feat must be contiguous"); ASSERT(kernel.is_contiguous(), "kernel must be contiguous"); ASSERT(!in_feat.is_cuda(), "in_feat must be CPU"); ASSERT(!kernel.is_cuda(), "kernel must be CPU"); ASSERT(in_feat.scalar_type() == kernel.scalar_type(), "type mismatch"); ASSERT(in_feat.dim() == 2, "in_feat.dim():", in_feat.dim()); ASSERT(kernel.dim() == 3, "kernel.dim():", kernel.dim()); ASSERT(in_feat.size(1) == kernel.size(1), "Input feature size and kernel size mismatch"); // create out coordinate map coordinate_map_key_type in_key = p_in_map_key->get_key(); ASSERT(p_map_manager->exists(in_key), ERROR_MAP_NOT_FOUND); ASSERT(in_feat.size(0) == p_map_manager->size(in_key), "Invalid in_feat size", in_feat.size(0), "!=", p_map_manager->size(in_key)); if (!p_out_map_key->is_key_set()) { if (expand_coordinates) { auto map_it = p_map_manager->find(p_in_map_key->get_key()); ASSERT(map_it != p_map_manager->map_end(), ERROR_MAP_NOT_FOUND); auto const &in_map = (*map_it).second; auto out_tensor_stride = detail::stride_tensor_stride( in_map.get_tensor_stride(), kernel_stride, false /* is_transpose */); LOG_DEBUG("Coordinate Expansion"); auto kernel_region = cpu_kernel_region( region_type, // in_map.coordinate_size(), // in_map.get_tensor_stride().data(), // kernel_size.data(), // kernel_dilation.data(), // 0, // volume. Will be initialized automatically offset.data_ptr(), offset.size(0), false // is_transpose ); coordinate_map_key_type out_key = std::get<0>(p_map_manager->stride_region( in_key, kernel_region, out_tensor_stride, expand_coordinates)); p_out_map_key->set_key(out_key); } else { coordinate_map_key_type out_key = std::get<0>(p_map_manager->stride(in_key, kernel_stride)); p_out_map_key->set_key(out_key); } } cpu_kernel_map const &in_out = p_map_manager->kernel_map( p_in_map_key, // p_out_map_key, // kernel_size, // kernel_stride, // kernel_dilation, // region_type, // offset, false /* is_transpose */, false /* is_pool */); auto const out_nrows = p_map_manager->size(p_out_map_key->get_key()); at::Tensor out_feat = torch::zeros({out_nrows, kernel.size(2)}, in_feat.options()); LOG_DEBUG("Allocated", out_nrows, "x", kernel.size(2), "out_features."); if (out_nrows > 0) AT_DISPATCH_FLOATING_TYPES( in_feat.scalar_type(), "convolution_forward_cpu", [&] { ConvolutionForwardKernelCPU( in_feat.template data_ptr(), in_feat.size(1), out_feat.template data_ptr(), out_feat.size(1), kernel.template data_ptr(), in_out.first, in_out.second); }); return out_feat; } template std::pair ConvolutionBackwardCPU(at::Tensor const &in_feat, // at::Tensor &grad_out_feat, // at::Tensor const &kernel, // default_types::stride_type const &kernel_size, // default_types::stride_type const &kernel_stride, // default_types::stride_type const &kernel_dilation, // RegionType::Type const region_type, // at::Tensor const &offset, // ConvolutionMode::Type const convolution_mode, // CoordinateMapKey *p_in_map_key, // CoordinateMapKey *p_out_map_key, // cpu_manager_type *p_map_manager) { ASSERT(in_feat.is_contiguous(), "in_feat must be contiguous"); // ASSERT(grad_out_feat.is_contiguous(), "grad_out_feata must be contiguous"); grad_out_feat = grad_out_feat.contiguous(); ASSERT(kernel.is_contiguous(), "kernel must be contiguous"); ASSERT(!in_feat.is_cuda(), "in_feat must be CPU"); ASSERT(!grad_out_feat.is_cuda(), "in_feat must be CPU"); ASSERT(!kernel.is_cuda(), "kernel must be CPU"); ASSERT(in_feat.scalar_type() == kernel.scalar_type(), "type mismatch"); ASSERT(in_feat.scalar_type() == grad_out_feat.scalar_type(), "type mismatch"); ASSERT(in_feat.dim() == 2, "in_feat.dim():", in_feat.dim()); ASSERT(grad_out_feat.dim() == 2, "grad_out_feat.dim():", grad_out_feat.dim()); ASSERT(kernel.dim() == 3, "kernel.dim():", kernel.dim()); ASSERT(in_feat.size(1) == kernel.size(1), "Input feature size and kernel size mismatch"); coordinate_map_key_type in_key = p_in_map_key->get_key(); ASSERT(p_map_manager->exists(in_key), ERROR_MAP_NOT_FOUND); coordinate_map_key_type out_key = p_out_map_key->get_key(); ASSERT(p_map_manager->exists(out_key), ERROR_MAP_NOT_FOUND); cpu_kernel_map const &in_out = p_map_manager->kernel_map( p_in_map_key, // p_out_map_key, // kernel_size, // kernel_stride, // kernel_dilation, // region_type, // offset, false /* is_transpose */, false /* is_pool */); at::Tensor grad_in_feat = torch::zeros({in_feat.size(0), in_feat.size(1)}, in_feat.options()); at::Tensor grad_kernel = torch::zeros( {kernel.size(0), kernel.size(1), kernel.size(2)}, kernel.options()); if (in_feat.size(0) > 0) AT_DISPATCH_FLOATING_TYPES( in_feat.scalar_type(), "convolution_backward_cpu", [&] { ConvolutionBackwardKernelCPU( in_feat.template data_ptr(), grad_in_feat.template data_ptr(), in_feat.size(1), grad_out_feat.template data_ptr(), grad_out_feat.size(1), kernel.template data_ptr(), grad_kernel.template data_ptr(), in_out.first, in_out.second); }); return std::make_pair(grad_in_feat, grad_kernel); } template at::Tensor ConvolutionForwardCPU( at::Tensor const &in_feat, // at::Tensor const &kernel, // default_types::stride_type const &kernel_size, // default_types::stride_type const &kernel_stride, // default_types::stride_type const &kernel_dilation, // RegionType::Type const region_type, // at::Tensor const &offset, // bool const expand_coordinates, // ConvolutionMode::Type const convolution_mode, // CoordinateMapKey *p_in_map_key, // CoordinateMapKey *p_out_map_key, // cpu_manager_type *p_map_manager); template std::pair ConvolutionBackwardCPU( at::Tensor const &in_feat, // at::Tensor &grad_out_feat, // at::Tensor const &kernel, // default_types::stride_type const &kernel_size, // default_types::stride_type const &kernel_stride, // default_types::stride_type const &kernel_dilation, // RegionType::Type const region_type, // at::Tensor const &offsets, // ConvolutionMode::Type const convolution_mode, // CoordinateMapKey *p_in_map_key, // CoordinateMapKey *p_out_map_key, // cpu_manager_type *p_map_manager); } // end namespace minkowski