| | #include <torch/serialize/tensor.h> |
| | #include <vector> |
| | |
| | #include <cuda.h> |
| | #include <cuda_runtime_api.h> |
| | #include "cluster_gpu.h" |
| |
|
| | |
| |
|
| | #include <ATen/cuda/CUDAContext.h> |
| | #include <ATen/cuda/CUDAEvent.h> |
| | |
| |
|
| | #define CHECK_CUDA(x) do { \ |
| | if (!x.type().is_cuda()) { \ |
| | fprintf(stderr, "%s must be CUDA tensor at %s:%d\n", #x, __FILE__, __LINE__); \ |
| | exit(-1); \ |
| | } \ |
| | } while (0) |
| | #define CHECK_CONTIGUOUS(x) do { \ |
| | if (!x.is_contiguous()) { \ |
| | fprintf(stderr, "%s must be contiguous tensor at %s:%d\n", #x, __FILE__, __LINE__); \ |
| | exit(-1); \ |
| | } \ |
| | } while (0) |
| | #define CHECK_INPUT(x) CHECK_CUDA(x);CHECK_CONTIGUOUS(x) |
| |
|
| | int dbscan_wrapper_fast(int b, int n, float eps, int min_pts, at::Tensor xyz_tensor, at::Tensor idx_tensor) { |
| | CHECK_INPUT(xyz_tensor); |
| | const float *xyz = xyz_tensor.data<float>(); |
| | int *idx = idx_tensor.data<int>(); |
| |
|
| | dbscan_kernel_launcher_fast(b, n, eps, min_pts, xyz, idx); |
| | return 1; |
| | } |
| |
|
| |
|
| | int cluster_pts_wrapper_fast(int b, int n, int m, at::Tensor xyz_tensor, at::Tensor idx_tensor, |
| | at::Tensor new_xyz_tensor, at::Tensor num_tensor) { |
| | CHECK_INPUT(xyz_tensor); |
| | CHECK_INPUT(idx_tensor); |
| | const float *xyz = xyz_tensor.data<float>(); |
| | const int *idx = idx_tensor.data<int>(); |
| | float *new_xyz = new_xyz_tensor.data<float>(); |
| | int *num = num_tensor.data<int>(); |
| |
|
| | cluster_pts_kernel_launcher_fast(b, n, m, xyz, idx, new_xyz, num); |
| | return 1; |
| | } |
| |
|
| |
|