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convolution_gpu.cu
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convolution_gpu.cu
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/*
* 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_key.hpp"
#include "coordinate_map_manager.hpp"
#include "errors.hpp"
#include "types.hpp"
#include "utils.hpp"
#include "convolution_kernel.cuh"
#include "kernel_map.cuh"
#include "convolution_cpu.cpp"
#include <ATen/cuda/CUDAUtils.h>
#include <pybind11/pybind11.h>
#include <torch/extension.h>
namespace minkowski {
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
at::Tensor ConvolutionForwardGPU(
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, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *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 CUDA");
ASSERT(kernel.is_cuda(), "kernel must be CUDA");
ASSERT(at::cuda::check_device({in_feat, kernel}),
"in_feat and kernel must be on the same device");
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");
// TODO kernel volume assertion.
// create out coordinate map
// TODO: custom upsampling
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 */);
auto kernel_region = cpu_kernel_region<coordinate_type>(
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<coordinate_type>(), 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);
}
}
auto 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.");
cublasHandle_t handle = at::cuda::getCurrentCUDABlasHandle();
cudaStream_t stream = at::cuda::getCurrentCUDAStream().stream();
cublasSetStream(handle, stream);
LOG_DEBUG("Convolution on", out_nrows, "x", kernel.size(2));
AT_DISPATCH_FLOATING_TYPES(
in_feat.scalar_type(), "convolution_forward_gpu", [&] {
LOG_DEBUG("ConvolutionForwardKernelGPU with",
std::is_same<float, scalar_t>::value ? "float" : "double");
TemplatedAllocator<char> byte_allocator;
ConvolutionForwardKernelGPU<scalar_t, default_types::index_type,
TemplatedAllocator<char>>(
in_feat.template data_ptr<scalar_t>(), //
in_feat.size(1), //
out_feat.template data_ptr<scalar_t>(), //
out_feat.size(1), //
kernel.template data_ptr<scalar_t>(), //
in_out, //
in_feat.size(0), //
out_nrows, //
byte_allocator, //
p_map_manager->algorithm(), //
convolution_mode, handle, stream);
});
return out_feat;
}
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
std::pair<at::Tensor, at::Tensor> ConvolutionBackwardGPU(
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, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *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 CUDA");
ASSERT(grad_out_feat.is_cuda(), "in_feat must be CUDA");
ASSERT(kernel.is_cuda(), "kernel must be CUDA");
ASSERT(at::cuda::check_device({in_feat, grad_out_feat, kernel}),
"in_feat, grad_out_feat, kernel must be on the same device");
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);
auto 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, false);
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());
cublasHandle_t handle = at::cuda::getCurrentCUDABlasHandle();
cudaStream_t stream = at::cuda::getCurrentCUDAStream().stream();
cublasSetStream(handle, stream);
AT_DISPATCH_FLOATING_TYPES(
in_feat.scalar_type(), "convolution_backward_gpu", [&] {
TemplatedAllocator<char> byte_allocator;
ConvolutionBackwardKernelGPU<scalar_t, default_types::index_type,
TemplatedAllocator<char>>(
in_feat.template data_ptr<scalar_t>(), //
grad_in_feat.template data_ptr<scalar_t>(), //
in_feat.size(1), //
grad_out_feat.template data_ptr<scalar_t>(), //
grad_out_feat.size(1), //
kernel.template data_ptr<scalar_t>(), //
grad_kernel.template data_ptr<scalar_t>(), //
in_out, //
in_feat.size(0), //
grad_out_feat.size(0), //
byte_allocator, //
p_map_manager->algorithm(), //
convolution_mode, //
handle, stream);
});
return std::make_pair(grad_in_feat, grad_kernel);
}
// Forward
// default_allocator
template at::Tensor ConvolutionForwardGPU<default_types::dcoordinate_type,
detail::default_allocator>(
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, //
gpu_manager_type<default_types::dcoordinate_type, detail::default_allocator>
*p_map_manager);
// c10_allocator
template at::Tensor ConvolutionForwardGPU<default_types::dcoordinate_type,
detail::c10_allocator>(
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, //
gpu_manager_type<default_types::dcoordinate_type, detail::c10_allocator>
*p_map_manager);
// Backward
// default_allocator
template std::pair<at::Tensor, at::Tensor>
ConvolutionBackwardGPU<default_types::dcoordinate_type,
detail::default_allocator>(
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, //
gpu_manager_type<default_types::dcoordinate_type, detail::default_allocator>
*p_map_manager);
// c10_allocator
template std::pair<at::Tensor, at::Tensor>
ConvolutionBackwardGPU<default_types::dcoordinate_type,
detail::c10_allocator>(
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, //
gpu_manager_type<default_types::dcoordinate_type, detail::c10_allocator>
*p_map_manager);
} // end namespace minkowski