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

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<float>();
    const int *idx = idx_tensor.data<int>();
    const float *grad_out = grad_out_tensor.data<float>();

    cudaStream_t stream = THCState_getCurrentStream(state);

    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<float>();
    const int *idx = idx_tensor.data<int>();
    float *out = out_tensor.data<float>();

    cudaStream_t stream = THCState_getCurrentStream(state);

    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");
}