// Copyright (c) OpenMMLab. All rights reserved
// Modified from
// https://github.com/sshaoshuai/Pointnet2.PyTorch/tree/master/pointnet2/src/ball_query_gpu.cu

#include <math.h>
#include <stdio.h>
#include <stdlib.h>

#include "ball_query_cuda_kernel.cuh"
#include "pytorch_cuda_helper.hpp"

void BallQueryForwardCUDAKernelLauncher(int b, int n, int m, float min_radius,
                                        float max_radius, int nsample,
                                        const Tensor new_xyz, const Tensor xyz,
                                        Tensor idx) {
  // new_xyz: (B, M, 3)
  // xyz: (B, N, 3)
  // output:
  //      idx: (B, M, nsample)

  at::cuda::CUDAGuard device_guard(new_xyz.device());
  cudaStream_t stream = at::cuda::getCurrentCUDAStream();

  dim3 blocks(DIVUP(m, THREADS_PER_BLOCK),
              b);  // blockIdx.x(col), blockIdx.y(row)
  dim3 threads(THREADS_PER_BLOCK);

  AT_DISPATCH_FLOATING_TYPES_AND_HALF(
      new_xyz.scalar_type(), "ball_query_forward_cuda_kernel", [&] {
        ball_query_forward_cuda_kernel<scalar_t>
            <<<blocks, threads, 0, stream>>>(
                b, n, m, min_radius, max_radius, nsample,
                new_xyz.data_ptr<scalar_t>(), xyz.data_ptr<scalar_t>(),
                idx.data_ptr<int>());
      });

  AT_CUDA_CHECK(cudaGetLastError());
}
