423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2025-08-02 03:42:50 +08:00
Code Issues Packages Projects Releases Wiki Activity

Fix windows build (#1689)

Browse Source 
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

https://github.com/facebookresearch/pytorch3d/pull/9

https://github.com/facebookresearch/pytorch3d/issues/1679

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1689

Reviewed By: MichaelRamamonjisoa

Differential Revision: D51521562

Pulled By: bottler

fbshipit-source-id: d8ea81e223c642e0e9fb283f5d7efc9d6ac00d93
This commit is contained in:
sewon.jeon 2023-12-05 03:14:06 -08:00 committed by Facebook GitHub Bot
parent 83bacda8fb
commit 7606854ff7
1 changed files with 8 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

14
pytorch3d/csrc/marching_cubes/marching_cubes.cu
View File

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