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110 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
takiyu
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f358b9b14d |
Fix squared distance for CPU impl. (#83)
Summary: `PointLineDistanceForward()` should return squared distance. However, it seems that it returned non-squared distance when `v0` was near by `v1` in CPU implementation. Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/83 Reviewed By: bottler Differential Revision: D20097181 Pulled By: nikhilaravi fbshipit-source-id: 7ea851c0837ab89364e42d283c999df21ff5ff02 |
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merayxu
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9e21659fc5 |
Fixed windows MSVC build compatibility (#9)
Summary: Fixed a few MSVC compiler (visual studio 2019, MSVC 19.16.27034) compatibility issues 1. Replaced long with int64_t. aten::data_ptr\<long\> is not supported in MSVC 2. pytorch3d/csrc/rasterize_points/rasterize_points_cpu.cpp, inline function is not correctly recognized by MSVC. 3. pytorch3d/csrc/rasterize_meshes/geometry_utils.cuh const auto kEpsilon = 1e-30; MSVC does not compile this const into both host and device, change to a MACRO. 4. pytorch3d/csrc/rasterize_meshes/geometry_utils.cuh, const float area2 = pow(area, 2.0); 2.0 is considered as double by MSVC and raised an error 5. pytorch3d/csrc/rasterize_points/rasterize_points_cpu.cpp std::tuple<torch::Tensor, torch::Tensor> RasterizePointsCoarseCpu() return type does not match the declaration in rasterize_points_cpu.h. Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/9 Reviewed By: nikhilaravi Differential Revision: D19986567 Pulled By: yuanluxu fbshipit-source-id: f4d98525d088c99c513b85193db6f0fc69c7f017 |
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Georgia Gkioxari
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a3baa367e3 |
face areas backward
Summary: Added backward for mesh face areas & normals. Exposed it as a layer. Replaced the computation with the new op in Meshes and in Sample Points. Current issue: Circular imports. I moved the import of the op in meshes inside the function scope. Reviewed By: jcjohnson Differential Revision: D19920082 fbshipit-source-id: d213226d5e1d19a0c8452f4d32771d07e8b91c0a |
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Georgia Gkioxari
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60f3c4e7d2 |
cpp support for packed to padded
Summary: Cpu implementation for packed to padded and added gradients ``` Benchmark Avg Time(μs) Peak Time(μs) Iterations -------------------------------------------------------------------------------- PACKED_TO_PADDED_2_100_300_1_cpu 138 221 3625 PACKED_TO_PADDED_2_100_300_1_cuda:0 184 261 2716 PACKED_TO_PADDED_2_100_300_16_cpu 555 726 901 PACKED_TO_PADDED_2_100_300_16_cuda:0 179 260 2794 PACKED_TO_PADDED_2_100_3000_1_cpu 396 519 1262 PACKED_TO_PADDED_2_100_3000_1_cuda:0 181 274 2764 PACKED_TO_PADDED_2_100_3000_16_cpu 4517 5003 111 PACKED_TO_PADDED_2_100_3000_16_cuda:0 224 397 2235 PACKED_TO_PADDED_2_1000_300_1_cpu 138 212 3616 PACKED_TO_PADDED_2_1000_300_1_cuda:0 180 282 2775 PACKED_TO_PADDED_2_1000_300_16_cpu 565 711 885 PACKED_TO_PADDED_2_1000_300_16_cuda:0 179 264 2797 PACKED_TO_PADDED_2_1000_3000_1_cpu 389 494 1287 PACKED_TO_PADDED_2_1000_3000_1_cuda:0 180 271 2777 PACKED_TO_PADDED_2_1000_3000_16_cpu 4522 5170 111 PACKED_TO_PADDED_2_1000_3000_16_cuda:0 216 286 2313 PACKED_TO_PADDED_10_100_300_1_cpu 251 345 1995 PACKED_TO_PADDED_10_100_300_1_cuda:0 178 262 2806 PACKED_TO_PADDED_10_100_300_16_cpu 2354 2750 213 PACKED_TO_PADDED_10_100_300_16_cuda:0 178 291 2814 PACKED_TO_PADDED_10_100_3000_1_cpu 1519 1786 330 PACKED_TO_PADDED_10_100_3000_1_cuda:0 179 237 2791 PACKED_TO_PADDED_10_100_3000_16_cpu 24705 25879 21 PACKED_TO_PADDED_10_100_3000_16_cuda:0 228 316 2191 PACKED_TO_PADDED_10_1000_300_1_cpu 261 432 1919 PACKED_TO_PADDED_10_1000_300_1_cuda:0 181 261 2756 PACKED_TO_PADDED_10_1000_300_16_cpu 2349 2770 213 PACKED_TO_PADDED_10_1000_300_16_cuda:0 180 256 2782 PACKED_TO_PADDED_10_1000_3000_1_cpu 1613 1929 310 PACKED_TO_PADDED_10_1000_3000_1_cuda:0 183 253 2739 PACKED_TO_PADDED_10_1000_3000_16_cpu 22041 23653 23 PACKED_TO_PADDED_10_1000_3000_16_cuda:0 220 343 2270 PACKED_TO_PADDED_32_100_300_1_cpu 555 750 901 PACKED_TO_PADDED_32_100_300_1_cuda:0 188 282 2661 PACKED_TO_PADDED_32_100_300_16_cpu 7550 8131 67 PACKED_TO_PADDED_32_100_300_16_cuda:0 181 272 2770 PACKED_TO_PADDED_32_100_3000_1_cpu 4574 6327 110 PACKED_TO_PADDED_32_100_3000_1_cuda:0 173 254 2884 PACKED_TO_PADDED_32_100_3000_16_cpu 70366 72563 8 PACKED_TO_PADDED_32_100_3000_16_cuda:0 349 654 1433 PACKED_TO_PADDED_32_1000_300_1_cpu 612 728 818 PACKED_TO_PADDED_32_1000_300_1_cuda:0 189 295 2647 PACKED_TO_PADDED_32_1000_300_16_cpu 7699 8254 65 PACKED_TO_PADDED_32_1000_300_16_cuda:0 189 311 2646 PACKED_TO_PADDED_32_1000_3000_1_cpu 5105 5261 98 PACKED_TO_PADDED_32_1000_3000_1_cuda:0 191 260 2625 PACKED_TO_PADDED_32_1000_3000_16_cpu 87073 92708 6 PACKED_TO_PADDED_32_1000_3000_16_cuda:0 344 425 1455 -------------------------------------------------------------------------------- Benchmark Avg Time(μs) Peak Time(μs) Iterations -------------------------------------------------------------------------------- PACKED_TO_PADDED_TORCH_2_100_300_1_cpu 492 627 1016 PACKED_TO_PADDED_TORCH_2_100_300_1_cuda:0 768 975 652 PACKED_TO_PADDED_TORCH_2_100_300_16_cpu 659 804 760 PACKED_TO_PADDED_TORCH_2_100_300_16_cuda:0 781 918 641 PACKED_TO_PADDED_TORCH_2_100_3000_1_cpu 624 734 802 PACKED_TO_PADDED_TORCH_2_100_3000_1_cuda:0 778 929 643 PACKED_TO_PADDED_TORCH_2_100_3000_16_cpu 2609 2850 192 PACKED_TO_PADDED_TORCH_2_100_3000_16_cuda:0 758 901 660 PACKED_TO_PADDED_TORCH_2_1000_300_1_cpu 467 612 1072 PACKED_TO_PADDED_TORCH_2_1000_300_1_cuda:0 772 905 648 PACKED_TO_PADDED_TORCH_2_1000_300_16_cpu 689 839 726 PACKED_TO_PADDED_TORCH_2_1000_300_16_cuda:0 789 1143 635 PACKED_TO_PADDED_TORCH_2_1000_3000_1_cpu 629 735 795 PACKED_TO_PADDED_TORCH_2_1000_3000_1_cuda:0 812 916 616 PACKED_TO_PADDED_TORCH_2_1000_3000_16_cpu 2716 3117 185 PACKED_TO_PADDED_TORCH_2_1000_3000_16_cuda:0 844 1288 593 PACKED_TO_PADDED_TORCH_10_100_300_1_cpu 2387 2557 210 PACKED_TO_PADDED_TORCH_10_100_300_1_cuda:0 4112 4993 122 PACKED_TO_PADDED_TORCH_10_100_300_16_cpu 3385 4254 148 PACKED_TO_PADDED_TORCH_10_100_300_16_cuda:0 3959 4902 127 PACKED_TO_PADDED_TORCH_10_100_3000_1_cpu 2918 3105 172 PACKED_TO_PADDED_TORCH_10_100_3000_1_cuda:0 4054 4450 124 PACKED_TO_PADDED_TORCH_10_100_3000_16_cpu 12748 13623 40 PACKED_TO_PADDED_TORCH_10_100_3000_16_cuda:0 4023 4395 125 PACKED_TO_PADDED_TORCH_10_1000_300_1_cpu 2258 2492 222 PACKED_TO_PADDED_TORCH_10_1000_300_1_cuda:0 3997 4312 126 PACKED_TO_PADDED_TORCH_10_1000_300_16_cpu 3404 3597 147 PACKED_TO_PADDED_TORCH_10_1000_300_16_cuda:0 3877 4227 129 PACKED_TO_PADDED_TORCH_10_1000_3000_1_cpu 2789 3054 180 PACKED_TO_PADDED_TORCH_10_1000_3000_1_cuda:0 3821 4402 131 PACKED_TO_PADDED_TORCH_10_1000_3000_16_cpu 11967 12963 42 PACKED_TO_PADDED_TORCH_10_1000_3000_16_cuda:0 3729 4290 135 PACKED_TO_PADDED_TORCH_32_100_300_1_cpu 6933 8152 73 PACKED_TO_PADDED_TORCH_32_100_300_1_cuda:0 11856 12287 43 PACKED_TO_PADDED_TORCH_32_100_300_16_cpu 9895 11205 51 PACKED_TO_PADDED_TORCH_32_100_300_16_cuda:0 12354 13596 41 PACKED_TO_PADDED_TORCH_32_100_3000_1_cpu 9516 10128 53 PACKED_TO_PADDED_TORCH_32_100_3000_1_cuda:0 12917 13597 39 PACKED_TO_PADDED_TORCH_32_100_3000_16_cpu 41209 43783 13 PACKED_TO_PADDED_TORCH_32_100_3000_16_cuda:0 12210 13288 41 PACKED_TO_PADDED_TORCH_32_1000_300_1_cpu 7179 7689 70 PACKED_TO_PADDED_TORCH_32_1000_300_1_cuda:0 11896 12381 43 PACKED_TO_PADDED_TORCH_32_1000_300_16_cpu 10127 15494 50 PACKED_TO_PADDED_TORCH_32_1000_300_16_cuda:0 12034 12817 42 PACKED_TO_PADDED_TORCH_32_1000_3000_1_cpu 8743 10251 58 PACKED_TO_PADDED_TORCH_32_1000_3000_1_cuda:0 12023 12908 42 PACKED_TO_PADDED_TORCH_32_1000_3000_16_cpu 39071 41777 13 PACKED_TO_PADDED_TORCH_32_1000_3000_16_cuda:0 11999 13690 42 -------------------------------------------------------------------------------- ``` Reviewed By: bottler, nikhilaravi, jcjohnson Differential Revision: D19870575 fbshipit-source-id: 23a2477b73373c411899633386c87ab034c3702a |
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Jeremy Reizenstein
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bdc2bb578c |
MACOSX_DEPLOYMENT_TARGET=10.14
Summary: pybind now seems to need C++17 on a mac, so advise people to use it. (Also delete an unused variable to silence a warning I got on a mac build.) Reported in github issue #68. Reviewed By: nikhilaravi Differential Revision: D19970512 fbshipit-source-id: f9be20c8ed425bd6ba8d009a7d62dad658dccdb1 |
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Nikhila Ravi
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97acf16de2 |
lint fixes
Summary: Ran `dev/linter.sh`. Reviewed By: bottler Differential Revision: D19761062 fbshipit-source-id: 1a49abe4a5f2bc7641b2b46e254aa77e6a48aa7d |
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Georgia Gkioxari
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29cd181a83 |
CPU implem for face areas normals
Summary: Added cpu implementation for face areas normals. Moved test and bm to separate functions. ``` Benchmark Avg Time(μs) Peak Time(μs) Iterations -------------------------------------------------------------------------------- FACE_AREAS_NORMALS_2_100_300_False 196 268 2550 FACE_AREAS_NORMALS_2_100_300_True 106 179 4733 FACE_AREAS_NORMALS_2_100_3000_False 1447 1630 346 FACE_AREAS_NORMALS_2_100_3000_True 107 178 4674 FACE_AREAS_NORMALS_2_1000_300_False 201 309 2486 FACE_AREAS_NORMALS_2_1000_300_True 107 186 4673 FACE_AREAS_NORMALS_2_1000_3000_False 1451 1636 345 FACE_AREAS_NORMALS_2_1000_3000_True 107 186 4655 FACE_AREAS_NORMALS_10_100_300_False 767 918 653 FACE_AREAS_NORMALS_10_100_300_True 106 167 4712 FACE_AREAS_NORMALS_10_100_3000_False 7036 7754 72 FACE_AREAS_NORMALS_10_100_3000_True 113 164 4445 FACE_AREAS_NORMALS_10_1000_300_False 748 947 669 FACE_AREAS_NORMALS_10_1000_300_True 108 169 4638 FACE_AREAS_NORMALS_10_1000_3000_False 7069 7783 71 FACE_AREAS_NORMALS_10_1000_3000_True 108 172 4646 FACE_AREAS_NORMALS_32_100_300_False 2286 2496 219 FACE_AREAS_NORMALS_32_100_300_True 108 180 4631 FACE_AREAS_NORMALS_32_100_3000_False 23184 24369 22 FACE_AREAS_NORMALS_32_100_3000_True 159 213 3147 FACE_AREAS_NORMALS_32_1000_300_False 2414 2645 208 FACE_AREAS_NORMALS_32_1000_300_True 112 197 4480 FACE_AREAS_NORMALS_32_1000_3000_False 21687 22964 24 FACE_AREAS_NORMALS_32_1000_3000_True 141 211 3540 -------------------------------------------------------------------------------- Benchmark Avg Time(μs) Peak Time(μs) Iterations -------------------------------------------------------------------------------- FACE_AREAS_NORMALS_TORCH_2_100_300_False 5465 5782 92 FACE_AREAS_NORMALS_TORCH_2_100_300_True 1198 1351 418 FACE_AREAS_NORMALS_TORCH_2_100_3000_False 48228 48869 11 FACE_AREAS_NORMALS_TORCH_2_100_3000_True 1186 1304 422 FACE_AREAS_NORMALS_TORCH_2_1000_300_False 5556 6097 90 FACE_AREAS_NORMALS_TORCH_2_1000_300_True 1200 1328 417 FACE_AREAS_NORMALS_TORCH_2_1000_3000_False 48683 50016 11 FACE_AREAS_NORMALS_TORCH_2_1000_3000_True 1185 1306 422 FACE_AREAS_NORMALS_TORCH_10_100_300_False 24215 25097 21 FACE_AREAS_NORMALS_TORCH_10_100_300_True 1150 1314 435 FACE_AREAS_NORMALS_TORCH_10_100_3000_False 232605 234952 3 FACE_AREAS_NORMALS_TORCH_10_100_3000_True 1193 1314 420 FACE_AREAS_NORMALS_TORCH_10_1000_300_False 24912 25343 21 FACE_AREAS_NORMALS_TORCH_10_1000_300_True 1216 1330 412 FACE_AREAS_NORMALS_TORCH_10_1000_3000_False 239907 241253 3 FACE_AREAS_NORMALS_TORCH_10_1000_3000_True 1226 1333 408 FACE_AREAS_NORMALS_TORCH_32_100_300_False 73991 75776 7 FACE_AREAS_NORMALS_TORCH_32_100_300_True 1193 1339 420 FACE_AREAS_NORMALS_TORCH_32_100_3000_False 728932 728932 1 FACE_AREAS_NORMALS_TORCH_32_100_3000_True 1186 1359 422 FACE_AREAS_NORMALS_TORCH_32_1000_300_False 76385 79129 7 FACE_AREAS_NORMALS_TORCH_32_1000_300_True 1165 1310 430 FACE_AREAS_NORMALS_TORCH_32_1000_3000_False 753276 753276 1 FACE_AREAS_NORMALS_TORCH_32_1000_3000_True 1205 1340 415 -------------------------------------------------------------------------------- ``` Reviewed By: bottler, jcjohnson Differential Revision: D19864385 fbshipit-source-id: 3a87ae41a8e3ab5560febcb94961798f2e09dfb8 |
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Nikhila Ravi
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dcb094800f |
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 |
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Justin Johnson
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e290f87ca9 |
Add CPU implementation for nearest neighbor
Summary: Adds a CPU implementation for `pytorch3d.ops.nn_points_idx`. Also renames the associated C++ and CUDA functions to use `AllCaps` names used in other C++ / CUDA code. Reviewed By: gkioxari Differential Revision: D19670491 fbshipit-source-id: 1b6409404025bf05e6a93f5d847e35afc9062f05 |
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facebook-github-bot
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dbf06b504b |
Initial commit
fbshipit-source-id: ad58e416e3ceeca85fae0583308968d04e78fe0d |