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

// extern THCState *state;

#include <ATen/cuda/CUDAContext.h>
#include <ATen/cuda/CUDAEvent.h>
// cudaStream_t stream = at::cuda::getCurrentCUDAStream();

#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 ball_query_wrapper_fast(int b, int n, int m, float radius, int nsample, 
    at::Tensor new_xyz_tensor, at::Tensor xyz_tensor, at::Tensor idx_tensor) {
    CHECK_INPUT(new_xyz_tensor);
    CHECK_INPUT(xyz_tensor);
    const float *new_xyz = new_xyz_tensor.data<float>();
    const float *xyz = xyz_tensor.data<float>();
    int *idx = idx_tensor.data<int>();

    ball_query_kernel_launcher_fast(b, n, m, radius, nsample, new_xyz, xyz, idx);
    return 1;
}


int ball_center_query_wrapper_fast(int b, int n, int m, float radius,
    at::Tensor point_tensor, at::Tensor key_point_tensor, at::Tensor idx_tensor) {
    CHECK_INPUT(point_tensor);
    CHECK_INPUT(key_point_tensor);
    const float *point = point_tensor.data<float>();
    const float *key_point = key_point_tensor.data<float>();
    int *idx = idx_tensor.data<int>();

    ball_center_query_kernel_launcher_fast(b, n, m, radius, point, key_point, idx);
    return 1;
}


int knn_query_wrapper_fast(int b, int n, int m, int nsample,
    at::Tensor new_xyz_tensor, at::Tensor xyz_tensor, at::Tensor dist2_tensor, at::Tensor idx_tensor) {
    CHECK_INPUT(new_xyz_tensor);
    CHECK_INPUT(xyz_tensor);
    const float *new_xyz = new_xyz_tensor.data<float>();
    const float *xyz = xyz_tensor.data<float>();
    float *dist2 = dist2_tensor.data<float>();
    int *idx = idx_tensor.data<int>();

    knn_query_kernel_launcher_fast(b, n, m, nsample, new_xyz, xyz, dist2, idx);
    return 1;
}


int ball_query_wrapper_stack(int B, int M, float radius, int nsample,
    at::Tensor new_xyz_tensor, at::Tensor new_xyz_batch_cnt_tensor,
    at::Tensor xyz_tensor, at::Tensor xyz_batch_cnt_tensor, at::Tensor idx_tensor) {
    CHECK_INPUT(new_xyz_tensor);
    CHECK_INPUT(xyz_tensor);
    CHECK_INPUT(new_xyz_batch_cnt_tensor);
    CHECK_INPUT(xyz_batch_cnt_tensor);

    const float *new_xyz = new_xyz_tensor.data<float>();
    const float *xyz = xyz_tensor.data<float>();
    const int *new_xyz_batch_cnt = new_xyz_batch_cnt_tensor.data<int>();
    const int *xyz_batch_cnt = xyz_batch_cnt_tensor.data<int>();
    int *idx = idx_tensor.data<int>();

    ball_query_kernel_launcher_stack(B, M, radius, nsample, new_xyz, new_xyz_batch_cnt, xyz, xyz_batch_cnt, idx);
    return 1;
}