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data() deprecated

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Summary: replace `data()` with preferred `data_ptr()`, avoiding some deprecation warnings in future pytorch.

Reviewed By: nikhilaravi

Differential Revision: D20645738

fbshipit-source-id: 8f6e02d292729b804fa2a66f94dd0517bbaf7887
This commit is contained in:
Jeremy Reizenstein 2020-03-26 03:19:12 -07:00 committed by Facebook GitHub Bot
parent 8fa7678614
commit e22d431e5b
2 changed files with 45 additions and 45 deletions
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48
pytorch3d/csrc/rasterize_meshes/rasterize_meshes.cu
View File

@ -309,19 +309,19 @@ RasterizeMeshesNaiveCuda(
const size_t threads = 64;
RasterizeMeshesNaiveCudaKernel<<<blocks, threads>>>(
face_verts.contiguous().data<float>(),
mesh_to_faces_packed_first_idx.contiguous().data<int64_t>(),
num_faces_per_mesh.contiguous().data<int64_t>(),
face_verts.contiguous().data_ptr<float>(),
mesh_to_faces_packed_first_idx.contiguous().data_ptr<int64_t>(),
num_faces_per_mesh.contiguous().data_ptr<int64_t>(),
blur_radius,
perspective_correct,
N,
H,
W,
K,
face_idxs.contiguous().data<int64_t>(),
zbuf.contiguous().data<float>(),
pix_dists.contiguous().data<float>(),
bary.contiguous().data<float>());
face_idxs.contiguous().data_ptr<int64_t>(),
zbuf.contiguous().data_ptr<float>(),
pix_dists.contiguous().data_ptr<float>(),
bary.contiguous().data_ptr<float>());
return std::make_tuple(face_idxs, zbuf, bary, pix_dists);
}
@ -467,17 +467,17 @@ torch::Tensor RasterizeMeshesBackwardCuda(
const size_t threads = 64;
RasterizeMeshesBackwardCudaKernel<<<blocks, threads>>>(
face_verts.contiguous().data<float>(),
pix_to_face.contiguous().data<int64_t>(),
face_verts.contiguous().data_ptr<float>(),
pix_to_face.contiguous().data_ptr<int64_t>(),
perspective_correct,
N,
H,
W,
K,
grad_zbuf.contiguous().data<float>(),
grad_bary.contiguous().data<float>(),
grad_dists.contiguous().data<float>(),
grad_face_verts.contiguous().data<float>());
grad_zbuf.contiguous().data_ptr<float>(),
grad_bary.contiguous().data_ptr<float>(),
grad_dists.contiguous().data_ptr<float>(),
grad_face_verts.contiguous().data_ptr<float>());
return grad_face_verts;
}
@ -643,9 +643,9 @@ torch::Tensor RasterizeMeshesCoarseCuda(
const size_t threads = 512;
RasterizeMeshesCoarseCudaKernel<<<blocks, threads, shared_size>>>(
face_verts.contiguous().data<float>(),
mesh_to_face_first_idx.contiguous().data<int64_t>(),
num_faces_per_mesh.contiguous().data<int64_t>(),
face_verts.contiguous().data_ptr<float>(),
mesh_to_face_first_idx.contiguous().data_ptr<int64_t>(),
num_faces_per_mesh.contiguous().data_ptr<int64_t>(),
blur_radius,
N,
F,
@ -654,8 +654,8 @@ torch::Tensor RasterizeMeshesCoarseCuda(
bin_size,
chunk_size,
M,
faces_per_bin.contiguous().data<int32_t>(),
bin_faces.contiguous().data<int32_t>());
faces_per_bin.contiguous().data_ptr<int32_t>(),
bin_faces.contiguous().data_ptr<int32_t>());
return bin_faces;
}
@ -793,8 +793,8 @@ RasterizeMeshesFineCuda(
const size_t threads = 64;
RasterizeMeshesFineCudaKernel<<<blocks, threads>>>(
face_verts.contiguous().data<float>(),
bin_faces.contiguous().data<int32_t>(),
face_verts.contiguous().data_ptr<float>(),
bin_faces.contiguous().data_ptr<int32_t>(),
blur_radius,
bin_size,
perspective_correct,
@ -804,10 +804,10 @@ RasterizeMeshesFineCuda(
H,
W,
K,
face_idxs.contiguous().data<int64_t>(),
zbuf.contiguous().data<float>(),
pix_dists.contiguous().data<float>(),
bary.contiguous().data<float>());
face_idxs.contiguous().data_ptr<int64_t>(),
zbuf.contiguous().data_ptr<float>(),
pix_dists.contiguous().data_ptr<float>(),
bary.contiguous().data_ptr<float>());
return std::make_tuple(face_idxs, zbuf, bary, pix_dists);
}

42
pytorch3d/csrc/rasterize_points/rasterize_points.cu
View File

@ -172,16 +172,16 @@ RasterizePointsNaiveCuda(
const size_t blocks = 1024;
const size_t threads = 64;
RasterizePointsNaiveCudaKernel<<<blocks, threads>>>(
points.contiguous().data<float>(),
cloud_to_packed_first_idx.contiguous().data<int64_t>(),
num_points_per_cloud.contiguous().data<int64_t>(),
points.contiguous().data_ptr<float>(),
cloud_to_packed_first_idx.contiguous().data_ptr<int64_t>(),
num_points_per_cloud.contiguous().data_ptr<int64_t>(),
radius,
N,
S,
K,
point_idxs.contiguous().data<int32_t>(),
zbuf.contiguous().data<float>(),
pix_dists.contiguous().data<float>());
point_idxs.contiguous().data_ptr<int32_t>(),
zbuf.contiguous().data_ptr<float>(),
pix_dists.contiguous().data_ptr<float>());
return std::make_tuple(point_idxs, zbuf, pix_dists);
}
@ -347,9 +347,9 @@ torch::Tensor RasterizePointsCoarseCuda(
const size_t blocks = 64;
const size_t threads = 512;
RasterizePointsCoarseCudaKernel<<<blocks, threads, shared_size>>>(
points.contiguous().data<float>(),
cloud_to_packed_first_idx.contiguous().data<int64_t>(),
num_points_per_cloud.contiguous().data<int64_t>(),
points.contiguous().data_ptr<float>(),
cloud_to_packed_first_idx.contiguous().data_ptr<int64_t>(),
num_points_per_cloud.contiguous().data_ptr<int64_t>(),
radius,
N,
P,
@ -357,8 +357,8 @@ torch::Tensor RasterizePointsCoarseCuda(
bin_size,
chunk_size,
M,
points_per_bin.contiguous().data<int32_t>(),
bin_points.contiguous().data<int32_t>());
points_per_bin.contiguous().data_ptr<int32_t>(),
bin_points.contiguous().data_ptr<int32_t>());
return bin_points;
}
@ -464,8 +464,8 @@ std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> RasterizePointsFineCuda(
const size_t blocks = 1024;
const size_t threads = 64;
RasterizePointsFineCudaKernel<<<blocks, threads>>>(
points.contiguous().data<float>(),
bin_points.contiguous().data<int32_t>(),
points.contiguous().data_ptr<float>(),
bin_points.contiguous().data_ptr<int32_t>(),
radius,
bin_size,
N,
@ -473,9 +473,9 @@ std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> RasterizePointsFineCuda(
M,
S,
K,
point_idxs.contiguous().data<int32_t>(),
zbuf.contiguous().data<float>(),
pix_dists.contiguous().data<float>());
point_idxs.contiguous().data_ptr<int32_t>(),
zbuf.contiguous().data_ptr<float>(),
pix_dists.contiguous().data_ptr<float>());
return std::make_tuple(point_idxs, zbuf, pix_dists);
}
@ -547,16 +547,16 @@ torch::Tensor RasterizePointsBackwardCuda(
const size_t threads = 64;
RasterizePointsBackwardCudaKernel<<<blocks, threads>>>(
points.contiguous().data<float>(),
idxs.contiguous().data<int32_t>(),
points.contiguous().data_ptr<float>(),
idxs.contiguous().data_ptr<int32_t>(),
N,
P,
H,
W,
K,
grad_zbuf.contiguous().data<float>(),
grad_dists.contiguous().data<float>(),
grad_points.contiguous().data<float>());
grad_zbuf.contiguous().data_ptr<float>(),
grad_dists.contiguous().data_ptr<float>(),
grad_points.contiguous().data_ptr<float>());
return grad_points;
}