Fix windows build (#1689)

Summary:
Change the data type usage in the code to ensure cross-platform compatibility
long -> int64_t

<img width="628" alt="image" src="https://github.com/facebookresearch/pytorch3d/assets/6214316/40041f7f-3c09-4571-b9ff-676c625802e9">

Tested under
Win 11 and Ubuntu 22.04
with
CUDA 12.1.1 torch 2.1.1

Related issues & PR

#9

#1679

Pull Request resolved: #1689

Reviewed By: MichaelRamamonjisoa

Differential Revision: D51521562

Pulled By: bottler

fbshipit-source-id: d8ea81e223c642e0e9fb283f5d7efc9d6ac00d93

pytorch3d/csrc/marching_cubes/marching_cubes.cu

@@ -223,7 +223,7 @@ __global__ void CompactVoxelsKernel(
         compactedVoxelArray,
     const at::PackedTensorAccessor32<int, 1, at::RestrictPtrTraits>
         voxelOccupied,
-    const at::PackedTensorAccessor32<long, 1, at::RestrictPtrTraits>
+    const at::PackedTensorAccessor32<int64_t, 1, at::RestrictPtrTraits>
         voxelOccupiedScan,
     uint numVoxels) {
   uint id = blockIdx.x * blockDim.x + threadIdx.x;
@@ -255,7 +255,8 @@ __global__ void GenerateFacesKernel(
     at::PackedTensorAccessor<int64_t, 1, at::RestrictPtrTraits> ids,
     at::PackedTensorAccessor32<int, 1, at::RestrictPtrTraits>
         compactedVoxelArray,
-    at::PackedTensorAccessor32<long, 1, at::RestrictPtrTraits> numVertsScanned,
+    at::PackedTensorAccessor32<int64_t, 1, at::RestrictPtrTraits>
+        numVertsScanned,
     const uint activeVoxels,
     const at::PackedTensorAccessor32<float, 3, at::RestrictPtrTraits> vol,
     const at::PackedTensorAccessor32<int, 2, at::RestrictPtrTraits> faceTable,
@@ -471,7 +472,7 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
   auto d_voxelOccupiedScan_ = d_voxelOccupiedScan.index({Slice(1, None)});
 
   // number of active voxels
-  int activeVoxels = d_voxelOccupiedScan[numVoxels].cpu().item<long>();
+  int64_t activeVoxels = d_voxelOccupiedScan[numVoxels].cpu().item<int64_t>();
 
   const int device_id = vol.device().index();
   auto opt = at::TensorOptions().dtype(at::kInt).device(at::kCUDA, device_id);
@@ -492,7 +493,8 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
   CompactVoxelsKernel<<<grid, threads, 0, stream>>>(
       d_compVoxelArray.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
       d_voxelOccupied.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
-      d_voxelOccupiedScan_.packed_accessor32<long, 1, at::RestrictPtrTraits>(),
+      d_voxelOccupiedScan_
+          .packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
       numVoxels);
   AT_CUDA_CHECK(cudaGetLastError());
   cudaDeviceSynchronize();
@@ -502,7 +504,7 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
   auto d_voxelVertsScan_ = d_voxelVertsScan.index({Slice(1, None)});
 
   // total number of vertices
-  int totalVerts = d_voxelVertsScan[numVoxels].cpu().item<long>();
+  int64_t totalVerts = d_voxelVertsScan[numVoxels].cpu().item<int64_t>();
 
   // Execute "GenerateFacesKernel" kernel
   // This runs only on the occupied voxels.
@@ -522,7 +524,7 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
       faces.packed_accessor<int64_t, 2, at::RestrictPtrTraits>(),
       ids.packed_accessor<int64_t, 1, at::RestrictPtrTraits>(),
       d_compVoxelArray.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
-      d_voxelVertsScan_.packed_accessor32<long, 1, at::RestrictPtrTraits>(),
+      d_voxelVertsScan_.packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
       activeVoxels,
       vol.packed_accessor32<float, 3, at::RestrictPtrTraits>(),
       faceTable.packed_accessor32<int, 2, at::RestrictPtrTraits>(),