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https://github.com/facebookresearch/pytorch3d.git
synced 2025-11-04 18:02:14 +08:00
ignore cuda for cpu only installation
Summary: Added if `WITH_CUDA` checks for points/mesh rasterization. If installing on cpu only then this causes `Undefined symbol` errors when trying to import pytorch3d. We had these checks for all the other cuda files but not the rasterization files. Thanks ppwwyyxx for the tip! Reviewed By: ppwwyyxx, gkioxari Differential Revision: D19801495 fbshipit-source-id: 20e7adccfdb33ac731c00a89414b2beaf0a35529
This commit is contained in:
Nikhila Ravi
Facebook Github Bot
parent
ca588a59d7
commit
dcb094800f
@ -19,6 +19,7 @@ RasterizeMeshesNaiveCpu(
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int faces_per_pixel,
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bool perspective_correct);
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#ifdef WITH_CUDA
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std::tuple<at::Tensor, at::Tensor, at::Tensor, at::Tensor>
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RasterizeMeshesNaiveCuda(
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const at::Tensor& face_verts,
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@ -28,7 +29,7 @@ RasterizeMeshesNaiveCuda(
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float blur_radius,
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int num_closest,
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bool perspective_correct);
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#endif
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// Forward pass for rasterizing a batch of meshes.
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//
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// Args:
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@ -82,6 +83,7 @@ RasterizeMeshesNaive(
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bool perspective_correct) {
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// TODO: Better type checking.
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if (face_verts.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizeMeshesNaiveCuda(
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face_verts,
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mesh_to_face_first_idx,
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@ -90,6 +92,9 @@ RasterizeMeshesNaive(
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blur_radius,
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faces_per_pixel,
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perspective_correct);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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return RasterizeMeshesNaiveCpu(
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face_verts,
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@ -114,6 +119,7 @@ torch::Tensor RasterizeMeshesBackwardCpu(
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const torch::Tensor& grad_dists,
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bool perspective_correct);
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#ifdef WITH_CUDA
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torch::Tensor RasterizeMeshesBackwardCuda(
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const torch::Tensor& face_verts,
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const torch::Tensor& pix_to_face,
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@ -121,6 +127,7 @@ torch::Tensor RasterizeMeshesBackwardCuda(
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const torch::Tensor& grad_zbuf,
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const torch::Tensor& grad_dists,
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bool perspective_correct);
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#endif
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// Args:
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// face_verts: float32 Tensor of shape (F, 3, 3) (from forward pass) giving
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@ -154,6 +161,7 @@ torch::Tensor RasterizeMeshesBackward(
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const torch::Tensor& grad_dists,
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bool perspective_correct) {
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if (face_verts.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizeMeshesBackwardCuda(
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face_verts,
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pix_to_face,
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@ -161,6 +169,9 @@ torch::Tensor RasterizeMeshesBackward(
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grad_bary,
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grad_dists,
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perspective_correct);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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return RasterizeMeshesBackwardCpu(
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face_verts,
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@ -185,6 +196,7 @@ torch::Tensor RasterizeMeshesCoarseCpu(
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int bin_size,
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int max_faces_per_bin);
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#ifdef WITH_CUDA
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torch::Tensor RasterizeMeshesCoarseCuda(
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const torch::Tensor& face_verts,
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const torch::Tensor& mesh_to_face_first_idx,
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@ -193,7 +205,7 @@ torch::Tensor RasterizeMeshesCoarseCuda(
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float blur_radius,
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int bin_size,
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int max_faces_per_bin);
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#endif
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// Args:
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// face_verts: Tensor of shape (F, 3, 3) giving (packed) vertex positions for
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// faces in all the meshes in the batch. Concretely,
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@ -225,6 +237,7 @@ torch::Tensor RasterizeMeshesCoarse(
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int bin_size,
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int max_faces_per_bin) {
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if (face_verts.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizeMeshesCoarseCuda(
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face_verts,
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mesh_to_face_first_idx,
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@ -233,6 +246,9 @@ torch::Tensor RasterizeMeshesCoarse(
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blur_radius,
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bin_size,
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max_faces_per_bin);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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return RasterizeMeshesCoarseCpu(
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face_verts,
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@ -249,6 +265,7 @@ torch::Tensor RasterizeMeshesCoarse(
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// * FINE RASTERIZATION *
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// ****************************************************************************
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#ifdef WITH_CUDA
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std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor>
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RasterizeMeshesFineCuda(
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const torch::Tensor& face_verts,
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@ -258,7 +275,7 @@ RasterizeMeshesFineCuda(
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int bin_size,
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int faces_per_pixel,
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bool perspective_correct);
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#endif
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// Args:
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// face_verts: Tensor of shape (F, 3, 3) giving (packed) vertex positions for
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// faces in all the meshes in the batch. Concretely,
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@ -306,6 +323,7 @@ RasterizeMeshesFine(
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int faces_per_pixel,
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bool perspective_correct) {
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if (face_verts.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizeMeshesFineCuda(
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face_verts,
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bin_faces,
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@ -314,6 +332,9 @@ RasterizeMeshesFine(
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bin_size,
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faces_per_pixel,
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perspective_correct);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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AT_ERROR("NOT IMPLEMENTED");
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}
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@ -15,13 +15,14 @@ std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> RasterizePointsNaiveCpu(
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const float radius,
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const int points_per_pixel);
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#ifdef WITH_CUDA
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std::tuple<torch::Tensor, torch::Tensor, torch::Tensor>
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RasterizePointsNaiveCuda(
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const torch::Tensor& points,
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const int image_size,
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const float radius,
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const int points_per_pixel);
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#endif
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// Naive (forward) pointcloud rasterization: For each pixel, for each point,
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// check whether that point hits the pixel.
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//
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@ -47,8 +48,12 @@ std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> RasterizePointsNaive(
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const float radius,
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const int points_per_pixel) {
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if (points.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizePointsNaiveCuda(
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points, image_size, radius, points_per_pixel);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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return RasterizePointsNaiveCpu(
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points, image_size, radius, points_per_pixel);
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@ -66,13 +71,14 @@ torch::Tensor RasterizePointsCoarseCpu(
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const int bin_size,
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const int max_points_per_bin);
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#ifdef WITH_CUDA
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torch::Tensor RasterizePointsCoarseCuda(
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const torch::Tensor& points,
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const int image_size,
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const float radius,
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const int bin_size,
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const int max_points_per_bin);
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#endif
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// Args:
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// points: Tensor of shape (N, P, 3)
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// radius: Radius of points to rasterize (in NDC units)
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@ -91,8 +97,12 @@ torch::Tensor RasterizePointsCoarse(
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const int bin_size,
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const int max_points_per_bin) {
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if (points.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizePointsCoarseCuda(
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points, image_size, radius, bin_size, max_points_per_bin);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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return RasterizePointsCoarseCpu(
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points, image_size, radius, bin_size, max_points_per_bin);
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@ -103,6 +113,7 @@ torch::Tensor RasterizePointsCoarse(
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// * FINE RASTERIZATION *
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// ****************************************************************************
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#ifdef WITH_CUDA
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std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> RasterizePointsFineCuda(
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const torch::Tensor& points,
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const torch::Tensor& bin_points,
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@ -110,7 +121,7 @@ std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> RasterizePointsFineCuda(
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const float radius,
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const int bin_size,
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const int points_per_pixel);
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#endif
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// Args:
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// points: float32 Tensor of shape (N, P, 3)
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// bin_points: int32 Tensor of shape (N, B, B, M) giving the indices of points
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@ -137,8 +148,12 @@ std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> RasterizePointsFine(
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const int bin_size,
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const int points_per_pixel) {
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if (points.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizePointsFineCuda(
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points, bin_points, image_size, radius, bin_size, points_per_pixel);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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AT_ERROR("NOT IMPLEMENTED");
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}
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@ -154,12 +169,13 @@ torch::Tensor RasterizePointsBackwardCpu(
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const torch::Tensor& grad_zbuf,
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const torch::Tensor& grad_dists);
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#ifdef WITH_CUDA
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torch::Tensor RasterizePointsBackwardCuda(
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const torch::Tensor& points,
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const torch::Tensor& idxs,
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const torch::Tensor& grad_zbuf,
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const torch::Tensor& grad_dists);
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#endif
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// Args:
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// points: float32 Tensor of shape (N, P, 3)
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// idxs: int32 Tensor of shape (N, H, W, K) (from forward pass)
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@ -178,7 +194,11 @@ torch::Tensor RasterizePointsBackward(
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const torch::Tensor& grad_zbuf,
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const torch::Tensor& grad_dists) {
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if (points.type().is_cuda()) {
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#ifdef WITH_CUDA
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return RasterizePointsBackwardCuda(points, idxs, grad_zbuf, grad_dists);
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#else
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AT_ERROR("Not compiled with GPU support");
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#endif
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} else {
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return RasterizePointsBackwardCpu(points, idxs, grad_zbuf, grad_dists);
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}
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