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Error instead of crash for tensors on exotic devices (#1986)

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Summary:
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1986

Adds device checks to prevent crashes on unsupported devices in PyTorch3D. Updates the `pytorch3d_cutils.h` file to include new macro CHECK_CPU that checks if a tensor is on the CPU device. This macro is then used in the directories from `ball_query` to `face_area_normals` to ensure that tensors are not on unsupported devices like MPS.

Note that this is the first part of a larger change, and to keep diffs better organized, subsequent diffs will update the remaining directories.

Reviewed By: bottler

Differential Revision: D77473296

fbshipit-source-id: 13dc84620dee667bddebad1dade2d2cb5a59c737
This commit is contained in:
Melvin He 2025-06-30 12:27:38 -07:00 committed by Facebook GitHub Bot
parent 71db7a0ea2
commit 177eec6378
7 changed files with 42 additions and 0 deletions
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2
pytorch3d/csrc/ball_query/ball_query.h
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@ -81,6 +81,8 @@ inline std::tuple<at::Tensor, at::Tensor> BallQuery(
AT_ERROR("Not compiled with GPU support.");
#endif
}
CHECK_CPU(p1);
CHECK_CPU(p2);
return BallQueryCpu(
p1.contiguous(),
p2.contiguous(),

5
pytorch3d/csrc/blending/sigmoid_alpha_blend.h
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@ -98,6 +98,11 @@ at::Tensor SigmoidAlphaBlendBackward(
AT_ERROR("Not compiled with GPU support.");
#endif
}
CHECK_CPU(distances);
CHECK_CPU(pix_to_face);
CHECK_CPU(alphas);
CHECK_CPU(grad_alphas);
return SigmoidAlphaBlendBackwardCpu(
grad_alphas, alphas, distances, pix_to_face, sigma);
}

8
pytorch3d/csrc/compositing/alpha_composite.h
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@ -74,6 +74,9 @@ torch::Tensor alphaCompositeForward(
AT_ERROR("Not compiled with GPU support");
#endif
} else {
CHECK_CPU(features);
CHECK_CPU(alphas);
CHECK_CPU(points_idx);
return alphaCompositeCpuForward(features, alphas, points_idx);
}
}
@ -101,6 +104,11 @@ std::tuple<torch::Tensor, torch::Tensor> alphaCompositeBackward(
AT_ERROR("Not compiled with GPU support");
#endif
} else {
CHECK_CPU(grad_outputs);
CHECK_CPU(features);
CHECK_CPU(alphas);
CHECK_CPU(points_idx);
return alphaCompositeCpuBackward(
grad_outputs, features, alphas, points_idx);
}

9
pytorch3d/csrc/compositing/norm_weighted_sum.h
View File

@ -73,6 +73,10 @@ torch::Tensor weightedSumNormForward(
AT_ERROR("Not compiled with GPU support");
#endif
} else {
CHECK_CPU(features);
CHECK_CPU(alphas);
CHECK_CPU(points_idx);
return weightedSumNormCpuForward(features, alphas, points_idx);
}
}
@ -100,6 +104,11 @@ std::tuple<torch::Tensor, torch::Tensor> weightedSumNormBackward(
AT_ERROR("Not compiled with GPU support");
#endif
} else {
CHECK_CPU(grad_outputs);
CHECK_CPU(features);
CHECK_CPU(alphas);
CHECK_CPU(points_idx);
return weightedSumNormCpuBackward(
grad_outputs, features, alphas, points_idx);
}

8
pytorch3d/csrc/compositing/weighted_sum.h
View File

@ -72,6 +72,9 @@ torch::Tensor weightedSumForward(
AT_ERROR("Not compiled with GPU support");
#endif
} else {
CHECK_CPU(features);
CHECK_CPU(alphas);
CHECK_CPU(points_idx);
return weightedSumCpuForward(features, alphas, points_idx);
}
}
@ -98,6 +101,11 @@ std::tuple<torch::Tensor, torch::Tensor> weightedSumBackward(
AT_ERROR("Not compiled with GPU support");
#endif
} else {
CHECK_CPU(grad_outputs);
CHECK_CPU(features);
CHECK_CPU(alphas);
CHECK_CPU(points_idx);
return weightedSumCpuBackward(grad_outputs, features, alphas, points_idx);
}
}

6
pytorch3d/csrc/face_areas_normals/face_areas_normals.h
View File

@ -60,6 +60,8 @@ std::tuple<at::Tensor, at::Tensor> FaceAreasNormalsForward(
AT_ERROR("Not compiled with GPU support.");
#endif
}
CHECK_CPU(verts);
CHECK_CPU(faces);
return FaceAreasNormalsForwardCpu(verts, faces);
}
@ -80,5 +82,9 @@ at::Tensor FaceAreasNormalsBackward(
AT_ERROR("Not compiled with GPU support.");
#endif
}
CHECK_CPU(grad_areas);
CHECK_CPU(grad_normals);
CHECK_CPU(verts);
CHECK_CPU(faces);
return FaceAreasNormalsBackwardCpu(grad_areas, grad_normals, verts, faces);
}

4
pytorch3d/csrc/utils/pytorch3d_cutils.h
View File

@ -15,3 +15,7 @@
#define CHECK_CONTIGUOUS_CUDA(x) \
CHECK_CUDA(x); \
CHECK_CONTIGUOUS(x)
#define CHECK_CPU(x) \
TORCH_CHECK( \
x.device().type() == torch::kCPU, \
"Cannot use CPU implementation: " #x " not on CPU.")