group_points.cpp

// Modified from
// https://github.com/sshaoshuai/Pointnet2.PyTorch/tree/master/pointnet2/src/group_points.cpp

#include <THC/THC.h>
#include <cuda.h>
#include <cuda_runtime_api.h>
#include <torch/extension.h>
#include <torch/serialize/tensor.h>

#include <vector>

extern THCState *state;

int group_points_wrapper(int b, int c, int n, int npoints, int nsample,
                         at::Tensor points_tensor, at::Tensor idx_tensor,
                         at::Tensor out_tensor);

void group_points_kernel_launcher(int b, int c, int n, int npoints, int nsample,
                                  const float *points, const int *idx,
                                  float *out, cudaStream_t stream);

int group_points_grad_wrapper(int b, int c, int n, int npoints, int nsample,
                              at::Tensor grad_out_tensor, at::Tensor idx_tensor,
                              at::Tensor grad_points_tensor);

void group_points_grad_kernel_launcher(int b, int c, int n, int npoints,
                                       int nsample, const float *grad_out,
                                       const int *idx, float *grad_points,
                                       cudaStream_t stream);

int group_points_grad_wrapper(int b, int c, int n, int npoints, int nsample,
                              at::Tensor grad_out_tensor, at::Tensor idx_tensor,
                              at::Tensor grad_points_tensor) {
  float *grad_points = grad_points_tensor.data_ptr<float>();
  const int *idx = idx_tensor.data_ptr<int>();
  const float *grad_out = grad_out_tensor.data_ptr<float>();

  cudaStream_t stream = at::cuda::getCurrentCUDAStream().stream();

  group_points_grad_kernel_launcher(b, c, n, npoints, nsample, grad_out, idx,
                                    grad_points, stream);
  return 1;
}

int group_points_wrapper(int b, int c, int n, int npoints, int nsample,
                         at::Tensor points_tensor, at::Tensor idx_tensor,
                         at::Tensor out_tensor) {
  const float *points = points_tensor.data_ptr<float>();
  const int *idx = idx_tensor.data_ptr<int>();
  float *out = out_tensor.data_ptr<float>();

  cudaStream_t stream = at::cuda::getCurrentCUDAStream().stream();

  group_points_kernel_launcher(b, c, n, npoints, nsample, points, idx, out,
                               stream);
  return 1;
}

PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
  m.def("forward", &group_points_wrapper, "group_points_wrapper");
  m.def("backward", &group_points_grad_wrapper, "group_points_grad_wrapper");
}