423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2026-02-26 08:06:00 +08:00
Code Issues Packages Projects Releases Wiki Activity

Compare commits

base: 423A35C7:v0.7.6
Branches Tags
423A35C7:main 423A35C7:bottler/un_auto 423A35C7:bottler/actions 423A35C7:export-D58685326 423A35C7:gh-pages 423A35C7:bottler-patch-1 423A35C7:classner-patch-pulsar-debug 423A35C7:v0.6
423A35C7:v0.7.9 423A35C7:stable 423A35C7:V0.7.8 423A35C7:v0.7.7 423A35C7:v0.7.6 423A35C7:v0.7.5 423A35C7:v0.7.4 423A35C7:v0.7.3 423A35C7:v0.7.2 423A35C7:v0.7.1 423A35C7:v0.7.0 423A35C7:v0.6.2 423A35C7:v0.6.1 423A35C7:v0.6.0 423A35C7:v0.5.0 423A35C7:v0.4.0 423A35C7:v0.3.0 423A35C7:v0.2.5 423A35C7:v0.2.0 423A35C7:v0.1.1 423A35C7:v0.1.0
...
compare: 423A35C7:bottler/un_auto
Branches Tags
423A35C7:main 423A35C7:bottler/un_auto 423A35C7:bottler/actions 423A35C7:export-D58685326 423A35C7:gh-pages 423A35C7:bottler-patch-1 423A35C7:classner-patch-pulsar-debug 423A35C7:v0.6
423A35C7:v0.7.9 423A35C7:stable 423A35C7:V0.7.8 423A35C7:v0.7.7 423A35C7:v0.7.6 423A35C7:v0.7.5 423A35C7:v0.7.4 423A35C7:v0.7.3 423A35C7:v0.7.2 423A35C7:v0.7.1 423A35C7:v0.7.0 423A35C7:v0.6.2 423A35C7:v0.6.1 423A35C7:v0.6.0 423A35C7:v0.5.0 423A35C7:v0.4.0 423A35C7:v0.3.0 423A35C7:v0.2.5 423A35C7:v0.2.0 423A35C7:v0.1.1 423A35C7:v0.1.0

68 Commits
v0.7.6 ... bottler/un

Author SHA1 Message Date
bottler
62a2031dd4 Revert "Fix CUDA kernel index data type in vision/fair/pytorch3d/pytorch3d/csrc/compositing/alpha_composite.cu +10" 
This reverts commit 3987612062.
 2025-03-27 05:28:03 -07:00
Richard Barnes
3987612062 Fix CUDA kernel index data type in vision/fair/pytorch3d/pytorch3d/csrc/compositing/alpha_composite.cu +10 
Summary:
CUDA kernel variables matching the type `(thread|block|grid).(Idx|Dim).(x|y|z)` [have the data type `uint`](https://docs.nvidia.com/cuda/cuda-c-programming-guide/#built-in-variables).

Many programmers mistakenly use implicit casts to turn these data types into `int`. In fact, the [CUDA Programming Guide](https://docs.nvidia.com/cuda/cuda-c-programming-guide/) it self is inconsistent and incorrect in its use of data types in programming examples.

The result of these implicit casts is that our kernels may give unexpected results when exposed to large datasets, i.e., those exceeding >~2B items.

While we now have linters in place to prevent simple mistakes (D71236150), our codebase has many problematic instances. This diff fixes some of them.

Reviewed By: dtolnay

Differential Revision: D71355356

fbshipit-source-id: cea44891416d9efd2f466d6c45df4e36008fa036
 2025-03-19 13:21:43 -07:00
Alexandros Benetatos
06a76ef8dd Correct "fast" matrix_to_axis_angle near pi (#1953) 
Summary:
A continuation of https://github.com/facebookresearch/pytorch3d/issues/1948 -- this commit fixes a small numerical issue with `matrix_to_axis_angle(..., fast=True)` near `pi`.
bottler feel free to check this out, it's a single-line change.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1953

Reviewed By: MichaelRamamonjisoa

Differential Revision: D70088251

Pulled By: bottler

fbshipit-source-id: 54cc7f946283db700cec2cd5575cf918456b7f32
 2025-03-11 12:25:59 -07:00
Richard Barnes
21205730d9 Fix unused-variable issues, mostly relating to AMD/HIP 
Reviewed By: meyering

Differential Revision: D70845538

fbshipit-source-id: 8e52b5e1f1d96b86404fc3b8cbc6fb952e2cb1a6
 2025-03-08 13:03:17 -08:00
Richard Barnes
7e09505538 Enable -Wunused-value in vision/PACKAGE +1 
Summary:
This diff enables compilation warning flags for the directory in question. Further details are in [this workplace post](https://fb.workplace.com/permalink.php?story_fbid=pfbid02XaWNiCVk69r1ghfvDVpujB8Hr9Y61uDvNakxiZFa2jwiPHscVdEQwCBHrmWZSyMRl&id=100051201402394).

This is a low-risk diff. There are **no run-time effects** and the diff has already been observed to compile locally. **If the code compiles, it work; test errors are spurious.**

Differential Revision: D70282347

fbshipit-source-id: e2fa55c002d7124b13450c812165d244b8a53f4e
 2025-03-04 17:49:30 -08:00
Nicholas Ormrod
20bd8b33f6 facebook-unused-include-check in fbcode/vision 
Summary:
Remove headers flagged by facebook-unused-include-check over fbcode.vision.

+ format and autodeps

This is a codemod. It was automatically generated and will be landed once it is approved and tests are passing in sandcastle.
You have been added as a reviewer by Sentinel or Butterfly.

Autodiff project: uiv
Autodiff partition: fbcode.vision
Autodiff bookmark: ad.uiv.fbcode.vision

Reviewed By: dtolnay

Differential Revision: D70403619

fbshipit-source-id: d109c15774eeb3d809875f75fa2a26ed20d7f9a6
 2025-02-28 18:08:12 -08:00
alex-bene
7a3c0cbc9d Increase performance for conversions including axis angles (#1948) 
Summary:
This is an extension of https://github.com/facebookresearch/pytorch3d/issues/1544 with various speed, stability, and readability improvements. (I could not find a way to make a commit to the existing PR). This PR is still based on the [Rodrigues' rotation formula](https://en.wikipedia.org/wiki/Rotation_formalisms_in_three_dimensions#Rotation_matrix_%E2%86%94_Euler_axis/angle).

The motivation is the same; this change speeds up the conversions up to 10x, depending on the device, batch size, etc.

### Notes
- As the angles get very close to `π`, the existing implementation and the proposed one start to differ. However, (my understanding is that) this is not a problem as the axis can not be stably inferred from the rotation matrix in this case in general.
- bottler , I tried to follow similar conventions as existing functions to deal with weird angles, let me know if something needs to be changed to merge this.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1948

Reviewed By: MichaelRamamonjisoa

Differential Revision: D69193009

Pulled By: bottler

fbshipit-source-id: e5ed34b45b625114ec4419bb89e22a6aefad4eeb
 2025-02-07 07:37:42 -08:00
Roman Shapovalov
215590b497 In FrameDataBuilder, set all path even if we don’t load blobs 
Summary:
This is a somewhat not BC change: some None paths will be replaced by metadata paths, even when they were not used for data loading.

Moreover, removing the legacy fix to the paths in the old CO3D release.

Reviewed By: bottler

Differential Revision: D69048238

fbshipit-source-id: 2a8b26d7b9f5e2adf39c65888b5863a5a9de1996
 2025-02-06 09:41:44 -08:00
Antoine Toisoul
43cd681d4f Updates to Implicitron dataset, metrics and tools 
Summary: Update Pytorch3D to be able to run assetgen (see later diffs in the stack)

Reviewed By: shapovalov

Differential Revision: D65942513

fbshipit-source-id: 1d01141c9f7e106608fa591be6e0d3262cb5944f
 2025-01-27 09:43:42 -08:00
Roman Shapovalov
42a4a7d432 Generalising SqlIndexDataset to support subtypes of SqlSequenceAnnotation 
Summary: We did not often extend sequence-level metadata but now for applications like text-to-3D/video, we need to store captions and similar.

Reviewed By: bottler

Differential Revision: D68269926

fbshipit-source-id: f8af308adce51863d719a335d85cd2558943bd4c
 2025-01-20 03:39:06 -08:00
generatedunixname89002005307016
699bc671ca Add missing Pyre mode headers] [batch:3/1531] [shard:41/N] 
Differential Revision: D68316763

fbshipit-source-id: fb3e1e1a17786f6f681f1b11b48b4efd7a8ac311
 2025-01-17 12:41:56 -08:00
Roman Shapovalov
49cf5a0f37 Loading fg probability from the alpha channel of image_rgb 
Summary:
It is often easier to store the mask together with RGB, especially for renders. The logic in this diff:
* if load_mask and mask_path provided, take the mask from mask_path,
* otherwise, check if the image has the alpha channel and take it as a mask.

Reviewed By: antoinetlc

Differential Revision: D68160212

fbshipit-source-id: d9b6779f90027a4987ba96800983f441edff9c74
 2025-01-15 11:53:30 -08:00
Roman Shapovalov
89b851e64c Refactor a utility function for bbox conversion 
Summary: This function makes it easier to extend FrameData class with new channels; brushing it up a bit.

Reviewed By: bottler

Differential Revision: D67816470

fbshipit-source-id: 6575415c864d0f539e283889760cd2331bf226a7
 2025-01-06 04:17:57 -08:00
Roman Shapovalov
5247f6ad74 Fixing type hints in FrameData 
Summary: As subj

Reviewed By: bottler

Differential Revision: D67791200

fbshipit-source-id: c2db01c94718102618f4c8bc5c5130c65ee1d81f
 2025-01-06 04:17:57 -08:00
Roman Shapovalov
e41aff47db Adding default values to FrameData for internal usage 
Summary: Ensuring all fields in FrameData have defaults.

Reviewed By: bottler

Differential Revision: D67762780

fbshipit-source-id: b680d29a1a11689850905978df544cdb4eb7ddcd
 2025-01-06 04:17:57 -08:00
Roman Shapovalov
64a5bfadc8 Adding SQL Dataset related files to the build script 
Summary: Now that we have SQLAlchemy 2.0, we can fully use them.

Reviewed By: bottler

Differential Revision: D66920096

fbshipit-source-id: 25c0ea1c4f7361e66348035519627dc961b9e6e6
 2024-12-23 16:05:26 -08:00
Thomas Polasek
055ab3a2e3 Convert directory fbcode/vision to use the Ruff Formatter 
Summary:
Converts the directory specified to use the Ruff formatter in pyfmt

ruff_dog

If this diff causes merge conflicts when rebasing, please run
`hg status -n -0 --change . -I '**/*.{py,pyi}' | xargs -0 arc pyfmt`
on your diff, and amend any changes before rebasing onto latest.
That should help reduce or eliminate any merge conflicts.

allow-large-files

Reviewed By: bottler

Differential Revision: D66472063

fbshipit-source-id: 35841cb397e4f8e066e2159550d2f56b403b1bef
 2024-11-26 02:38:20 -08:00
Edward Yang
f6c2ca6bfc Prepare for "Fix type-safety of torch.nn.Module instances": wave 2 
Summary: See D52890934

Reviewed By: malfet, r-barnes

Differential Revision: D66245100

fbshipit-source-id: 019058106ac7eaacf29c1c55912922ea55894d23
 2024-11-21 11:08:51 -08:00
Jeremy Reizenstein
e20cbe9b0e test fixes and lints 
Summary:
- followup recent pyre change D63415925
- make tests remove temporary files
- weights_only=True in torch.load
- lint fixes

3 test fixes from VRehnberg in https://github.com/facebookresearch/pytorch3d/issues/1914
- imageio channels fix
- frozen decorator in test_config
- load_blobs positional

Reviewed By: MichaelRamamonjisoa

Differential Revision: D66162167

fbshipit-source-id: 7737e174691b62f1708443a4fae07343cec5bfeb
 2024-11-20 09:15:51 -08:00
Jeremy Reizenstein
c17e6f947a run CI tests on main 
Reviewed By: MichaelRamamonjisoa

Differential Revision: D66162168

fbshipit-source-id: 90268c1925fa9439b876df143035c9d3c3a74632
 2024-11-20 05:06:52 -08:00
Yann Noutary
91c9f34137 Add safeguard in case num_tris diverges 
Summary:
This PR fixes adds a safeguard preventing num_tris to overflow in `MAX_TRIS`-length arrays. The update rule of `num_tris` is bounded :

 - max(num_tris(t)) = 2*num_tris(t-1)
 - num_tris(0) = 12
 - t <= 6

So :
 - max(num_tris) = 2^6*12
 - max(num_tris) = 768

Reviewed By: bottler

Differential Revision: D66162573

fbshipit-source-id: e269a79c75c6cc33306986b1f1256cffbe96c730
 2024-11-20 01:24:28 -08:00
Jeremy Reizenstein
81d82980bc Fix ogl test hang 
Summary: See https://github.com/facebookresearch/pytorch3d/issues/1908

Reviewed By: MichaelRamamonjisoa

Differential Revision: D65280253

fbshipit-source-id: ec05902c5f2f7eb9ddd92bda0045cc3564b8c091
 2024-11-06 11:40:42 -08:00
Jeremy Reizenstein
8fe6934885 fix subdivide_meshes with empty mesh #1788 
Summary:
Simplify code

fixes https://github.com/facebookresearch/pytorch3d/issues/1788

Reviewed By: MichaelRamamonjisoa

Differential Revision: D61847675

fbshipit-source-id: 48400875d1d885bb3615bc9f4b3c7c3d822b67e7
 2024-11-06 11:40:26 -08:00
bottler
c434957b2a Run tests in github action (#1896) 
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1896

Reviewed By: MichaelRamamonjisoa

Differential Revision: D65272512

Pulled By: bottler

fbshipit-source-id: 3bcfab43acd2d6be5444ff25178381510ddac015
 2024-11-06 11:15:34 -08:00
Jeremy Reizenstein
dd2a11b5fc Fix OFF for new numpy errors 
Summary: Error messages have changed around numpy version 2, making existing code fail.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D65280674

fbshipit-source-id: b3ae613ea8f0f4ae20fb6e5e816314b8c10e6c65
 2024-11-06 11:13:59 -08:00
Richard Barnes
9563ef79ca c10::optional -> std::optional in some files 
Reviewed By: jermenkoo

Differential Revision: D65425234

fbshipit-source-id: 1e7707d6b6aab640cc1fdd3bd71a3b50f77a0909
 2024-11-04 12:03:51 -08:00
generatedunixname89002005287564
008c7ab58c Pre-silence Pyre Errors for upcoming upgrade] [batch:67/603] [shard:3/N] 
Reviewed By: MaggieMoss

Differential Revision: D65290095

fbshipit-source-id: ced87d096aa8939700de5599ce6984cd7ae93912
 2024-10-31 16:26:25 -07:00
Jeremy Reizenstein
9eaed4c495 Fix K>1 in multimap UV sampling 
Summary:
Fixes https://github.com/facebookresearch/pytorch3d/issues/1897
"Wrong dimension on gather".

Reviewed By: cijose

Differential Revision: D65280675

fbshipit-source-id: 1d587036887972bb2a2ea56d40df19cbf1aeb6cc
 2024-10-31 16:05:10 -07:00
Richard Barnes
e13848265d at::optional -> std::optional (#1170) 
Summary: Pull Request resolved: https://github.com/pytorch/ao/pull/1170

Reviewed By: gineshidalgo99

Differential Revision: D64938040

fbshipit-source-id: 57f98b90676ad0164a6975ea50e4414fd85ae6c4
 2024-10-25 06:37:57 -07:00
generatedunixname89002005307016
58566963d6 Add type error suppressions for upcoming upgrade 
Reviewed By: MaggieMoss

Differential Revision: D64502797

fbshipit-source-id: cee9a54dfa8a005d5912b895d0bd094f352c5c6f
 2024-10-16 19:22:01 -07:00
Suresh Babu Kolla
e17ed5cd50 Hipify Pulsar for PyTorch3D 
Summary:
- Hipified Pytorch Pulsar
   - Created separate target for Pulsar tests and enabled RE testing
   - Pytorch3D full test suite requires additional work like fixing EGL
     dependencies on AMD

Reviewed By: danzimm

Differential Revision: D61339912

fbshipit-source-id: 0d10bc966e4de4a959f3834a386bad24e449dc1f
 2024-10-09 14:38:42 -07:00
Richard Barnes
8ed0c7a002 c10::optional -> std::optional 
Summary: `c10::optional` is an alias for `std::optional`. Let's remove the alias and use the real thing.

Reviewed By: meyering

Differential Revision: D63402341

fbshipit-source-id: 241383e7ca4b2f3f1f9cac3af083056123dfd02b
 2024-10-03 14:38:37 -07:00
Richard Barnes
2da913c7e6 c10::optional -> std::optional 
Summary: `c10::optional` is an alias for `std::optional`. Let's remove the alias and use the real thing.

Reviewed By: palmje

Differential Revision: D63409387

fbshipit-source-id: fb6db59a14db9e897e2e6b6ad378f33bf2af86e8
 2024-10-02 11:09:29 -07:00
generatedunixname89002005307016
fca83e6369 Convert .pyre_configuration.local to fast by default architecture] [batch:23/263] [shard:3/N] [A] 
Reviewed By: connernilsen

Differential Revision: D63415925

fbshipit-source-id: c3e28405c70f9edcf8c21457ac4faf7315b07322
 2024-09-25 17:34:03 -07:00
Jeremy Reizenstein
75ebeeaea0 update version to 0.7.8 
Summary: as title

Reviewed By: das-intensity

Differential Revision: D62588556

fbshipit-source-id: 55bae19dd1df796e83179cd29d805fcd871b6d23
 2024-09-13 02:31:49 -07:00
Jeremy Reizenstein
ab793177c6 remove pytorch2.0 builds 
Summary: these are failing in ci

Reviewed By: das-intensity

Differential Revision: D62594666

fbshipit-source-id: 5e3a7441be2978803dc2d3e361365e0fffa7ad3b
 2024-09-13 02:07:25 -07:00
Jeremy Reizenstein
9acdd67b83 fix obj material indexing bug #1368 
Summary:
Make the negative index actually not an error

fixes https://github.com/facebookresearch/pytorch3d/issues/1368

Reviewed By: das-intensity

Differential Revision: D62177991

fbshipit-source-id: e5ed433bde1f54251c4d4b6db073c029cbe87343
 2024-09-13 02:00:49 -07:00
Nicholas Dahm
3f428d9981 pytorch 2.4.0 + 2.4.1 
Summary:
Apparently pytorch 2.4 is now supported as per [this closed issue](https://github.com/facebookresearch/pytorch3d/issues/1863).

Added the `2.4.0` & `2.4.1` versions to `regenerate.py` then ran that as per the `README_fb.md` which generated `config.yml` changes.

Reviewed By: bottler

Differential Revision: D62517831

fbshipit-source-id: 002e276dfe2fa078136ff2f6c747d937abbadd1a
 2024-09-11 15:09:43 -07:00
Josh Fromm
05cbea115a Hipify Pytorch3D (#1851) 
Summary:
X-link: https://github.com/pytorch/pytorch/pull/133343

X-link: https://github.com/fairinternal/pytorch3d/pull/45

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1851

Enables pytorch3d to build on AMD. An important part of enabling this was not compiling the Pulsar backend when the target is AMD. There are simply too many kernel incompatibilites to make it work (I tried haha). Fortunately, it doesnt seem like most modern applications of pytorch3d rely on Pulsar. We should be able to unlock most of pytorch3d's goodness on AMD without it.

Reviewed By: bottler, houseroad

Differential Revision: D61171993

fbshipit-source-id: fd4aee378a3568b22676c5bf2b727c135ff710af
 2024-08-15 16:18:22 -07:00
generatedunixname89002005307016
38afdcfc68 upgrade pyre version in fbcode/vision - batch 2 
Reviewed By: bottler

Differential Revision: D60992234

fbshipit-source-id: 899db6ed590ef966ff651c11027819e59b8401a3
 2024-08-09 02:07:45 -07:00
Christine Sun
1e0b1d9c72 Remove Python versions from Install.md 
Summary: To avoid the installation instructions for PyTorch3D becoming out-of-date, instead of specifying certain Python versions, update to just `Python`. Reader will understand it has to be a Python version compatible with GitHub.

Reviewed By: bottler

Differential Revision: D60919848

fbshipit-source-id: 5e974970a0db3d3d32fae44e5dd30cbc1ce237a9
 2024-08-07 13:46:31 -07:00
Rebecca Chen (Python)
44702fdb4b Add "max" point reduction for chamfer distance 
Summary:
* Adds a "max" option for the point_reduction input to the
  chamfer_distance function.
* When combining the x and y directions, maxes the losses instead
  of summing them when point_reduction="max".
* Moves batch reduction to happen after the directions are
  combined.
* Adds test_chamfer_point_reduction_max and
  test_single_directional_chamfer_point_reduction_max tests.

Fixes  https://github.com/facebookresearch/pytorch3d/issues/1838

Reviewed By: bottler

Differential Revision: D60614661

fbshipit-source-id: 7879816acfda03e945bada951b931d2c522756eb
 2024-08-02 10:46:07 -07:00
Jeremy Reizenstein
7edaee71a9 allow matrix_to_quaternion onnx export 
Summary: Attempt to allow torch.onnx.dynamo_export(matrix_to_quaternion) to work.

Differential Revision: D59812279

fbshipit-source-id: 4497e5b543bec9d5c2bdccfb779d154750a075ad
 2024-07-16 11:30:20 -07:00
Roman Shapovalov
d0d0e02007 Fix: setting FrameData.crop_bbox_xywh for backwards compatibility 
Summary: This diff is fixing a backwards compatibility issue in PyTorch3D's dataset API. The code ensures that the `crop_bbox_xywh` attribute is set when box_crop flag is on. This is an implementation detail that people should not really use, however some people depend on this behaviour.

Reviewed By: bottler

Differential Revision: D59777449

fbshipit-source-id: b875e9eb909038b8629ccdade87661bb2c39d529
 2024-07-16 02:21:13 -07:00
Jeremy Reizenstein
4df110b0a9 remove fvcore dependency 
Summary: This is not actually needed and is causing a conda-forge confusion to do with python_abi - which needs users to have `-c conda-forge` when they install pytorch3d.

Reviewed By: patricklabatut

Differential Revision: D59587930

fbshipit-source-id: 961ae13a62e1b2b2ce6d8781db38bd97eca69e65
 2024-07-11 04:35:38 -07:00
Huy Do
51fd114d8b Forward fix internal pyre failure from D58983461 
Summary:
X-link: https://github.com/pytorch/pytorch/pull/129525

Somehow, using underscore alias of some builtin types breaks pyre

Reviewed By: malfet, clee2000

Differential Revision: D59029768

fbshipit-source-id: cfa2171b66475727b9545355e57a8297c1dc0bc6
 2024-06-27 07:35:18 -07:00
Jeremy Reizenstein
89653419d0 version 0.7.7 
Summary: New version

Reviewed By: MichaelRamamonjisoa

Differential Revision: D58668979

fbshipit-source-id: 195eaf83e4da51a106ef72e38dbb98c51c51724c
 2024-06-25 06:59:24 -07:00
Jeremy Reizenstein
7980854d44 require pytorch 2.0+ 
Summary: Problems with timeouts on old builds.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D58819435

fbshipit-source-id: e1976534a102ad3841f3b297c772e916aeea12cb
 2024-06-21 08:15:17 -07:00
Jeremy Reizenstein
51d7c06ddd MKL version fix in CI (#1820) 
Summary:
Fix for "undefined symbol: iJIT_NotifyEvent" build issue,

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1820

Reviewed By: MichaelRamamonjisoa

Differential Revision: D58685326

fbshipit-source-id: 48b54367c00851cc6fbb111ca98d69a2ace8361b
 2024-06-21 08:15:17 -07:00
Sergii Dymchenko
00c36ec01c Update deprecated PyTorch functions in fbcode/vision 
Reviewed By: bottler

Differential Revision: D58762015

fbshipit-source-id: a0d05fe63a88d33e3f7783b5a7b2a476dd3a7449
 2024-06-20 14:06:28 -07:00
vedrenne
b0462d8079 Allow indexing for classes inheriting Transform3d (#1801) 
Summary:
Currently, it is not possible to access a sub-transform using an indexer for all 3d transforms inheriting the `Transforms3d` class.
For instance:

```python
from pytorch3d import transforms

N = 10
r = transforms.random_rotations(N)
T = transforms.Transform3d().rotate(R=r)
R = transforms.Rotate(r)

x = T[0]  # ok
x = R[0]  # TypeError: __init__() got an unexpected keyword argument 'matrix'
```

This is because all these classes (namely `Rotate`, `Translate`, `Scale`, `RotateAxisAngle`) inherit the `__getitem__()` method from `Transform3d` which has the [following code on line 201](https://github.com/facebookresearch/pytorch3d/blob/main/pytorch3d/transforms/transform3d.py#L201):

```python
return self.__class__(matrix=self.get_matrix()[index])
```

The four classes inheriting `Transform3d` are not initialized through a matrix argument, hence they error.
I propose to modify the `__getitem__()` method of the `Transform3d` class to fix this behavior. The least invasive way to do it I can think of consists of creating an empty instance of the current class, then setting the `_matrix` attribute manually. Thus, instead of
```python
return self.__class__(matrix=self.get_matrix()[index])
```
I propose to do:
```python
instance = self.__class__.__new__(self.__class__)
instance._matrix = self.get_matrix()[index]
return instance
```

As far as I can tell, this modification occurs no modification whatsoever for the user, except for the ability to index all 3d transforms.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1801

Reviewed By: MichaelRamamonjisoa

Differential Revision: D58410389

Pulled By: bottler

fbshipit-source-id: f371e4c63d2ae4c927a7ad48c2de8862761078de
 2024-06-17 07:48:18 -07:00
Jeremy Reizenstein
b66d17a324 Undo c10=>std optional rename 
Summary: Undoes the pytorch3d changes in D57294278 because they break builds for for PyTorch<2.1 .

Reviewed By: MichaelRamamonjisoa

Differential Revision: D57379779

fbshipit-source-id: 47a12511abcec4c3f4e2f62eff5ba99deb2fab4c
 2024-06-17 07:09:30 -07:00
Kyle Vedder
717493cb79 Fixed last dimension size check so that it doesn't trivially pass. (#1815) 
Summary:
Currently, it checks that the `2`th dimension of `p2` is the same size as the `2`th dimension of `p2` instead of `p1`.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1815

Reviewed By: MichaelRamamonjisoa

Differential Revision: D58586966

Pulled By: bottler

fbshipit-source-id: d4f723fa264f90fe368c10825c1acdfdc4c406dc
 2024-06-17 06:00:13 -07:00
Jeremy Reizenstein
302da69461 builds for PyTorch 2.2.1 2.2.2 2.3.0 2.3.1 
Summary: Build for new pytorch versions

Reviewed By: MichaelRamamonjisoa

Differential Revision: D58668956

fbshipit-source-id: 7fdfb377b370448d6147daded6a21b8db87586fb
 2024-06-17 05:57:59 -07:00
Roman Shapovalov
4ae25bfce7 Moving ray bundle to float dtype 
Summary: We can now move ray bundle to float dtype (e.g. from fp16 like types).

Reviewed By: bottler

Differential Revision: D57493109

fbshipit-source-id: 4e18a427e968b646fe5feafbff653811cd007981
 2024-05-30 10:06:38 -07:00
Richard Barnes
bd52f4a408 c10::optional -> std::optional in tensorboard/adhoc/Adhoc.h +9 
Summary: `c10::optional` was switched to be `std::optional` after PyTorch moved to C++17. Let's eliminate `c10::optional`, if we can.

Reviewed By: albanD

Differential Revision: D57294278

fbshipit-source-id: f6f26133c43f8d92a4588f59df7d689e7909a0cd
 2024-05-13 16:40:34 -07:00
generatedunixname89002005307016
17117106e4 upgrade pyre version in fbcode/vision - batch 2 
Differential Revision: D57183103

fbshipit-source-id: 7e2f42ddc6a1fa02abc27a451987d67a00264cbb
 2024-05-10 01:18:43 -07:00
Richard Barnes
aec76bb4c8 Remove unused-but-set variables in vision/fair/pytorch3d/pytorch3d/csrc/pulsar/include/renderer.render.device.h +1 
Summary:
This diff removes a variable that was set, but which was not used.

LLVM-15 has a warning `-Wunused-but-set-variable` which we treat as an error because it's so often diagnostic of a code issue. Unused but set variables often indicate a programming mistake, but can also just be unnecessary cruft that harms readability and performance.

Removing this variable will not change how your code works, but the unused variable may indicate your code isn't working the way you thought it was. I've gone through each of these by hand, but mistakes may have slipped through. If you feel the diff needs changes before landing, **please commandeer** and make appropriate changes: there are hundreds of these and responding to them individually is challenging.

For questions/comments, contact r-barnes.

 - If you approve of this diff, please use the "Accept & Ship" button :-)

Reviewed By: bottler

Differential Revision: D56886956

fbshipit-source-id: 0c515ed98b812b1c106a59e19ec90751ce32e8c0
 2024-05-02 13:58:05 -07:00
Andres Suarez
47d5dc8824 Apply clang-format 18 
Summary: Previously this code conformed from clang-format 12.

Reviewed By: igorsugak

Differential Revision: D56065247

fbshipit-source-id: f5a985dd8f8b84f2f9e1818b3719b43c5a1b05b3
 2024-04-14 11:28:32 -07:00
generatedunixname89002005307016
fe0b1bae49 upgrade pyre version in fbcode/vision - batch 2 
Differential Revision: D55650177

fbshipit-source-id: d5faa4d805bb40fe3dea70b0601e7a1382b09f3a
 2024-04-02 18:11:50 -07:00
Ruishen Lyu
ccf22911d4 Optimize list_to_packed to avoid for loop (#1737) 
Summary:
For larger N and Mi value (e.g. N=154, Mi=238) I notice list_to_packed() has become a bottleneck for my application. By removing the for loop and running on GPU, i see a 10-20 x speedup.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1737

Reviewed By: MichaelRamamonjisoa

Differential Revision: D54187993

Pulled By: bottler

fbshipit-source-id: 16399a24cb63b48c30460c7d960abef603b115d0
 2024-04-02 07:50:25 -07:00
Ashim Dahal
128be02fc0 feat: adjusted sample_nums (#1768) 
Summary:
adjusted sample_nums to match the number of columns in the image grid. It originally produced image grid with 5 axes but only 3 images and after this fix, the block would work as intended.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1768

Reviewed By: MichaelRamamonjisoa

Differential Revision: D55632872

Pulled By: bottler

fbshipit-source-id: 44d633a8068076889e49d49b8a7910dba0db37a7
 2024-04-02 06:02:48 -07:00
Roeia Kishk
31e3488a51 Changed tutorials' pip searching 
Summary:
### Generalise tutorials' pip searching:
## Required Information:
This diff contains changes to several PyTorch3D tutorials.

**Purpose of this diff:**
Replace the current installation code with a more streamlined approach that tries to install the wheel first and falls back to installing from source if the wheel is not found.

**Why this diff is required:**
This diff makes it easier to cope with new PyTorch releases and reduce the need for manual intervention, as the current process involves checking the version of PyTorch in Colab and building a new wheel if it doesn't match the expected version, which generates additional work each time there is a a new PyTorch version in Colab.

**Changes:**
Before:
```
    if torch.__version__.startswith("2.1.") and sys.platform.startswith("linux"):
        # We try to install PyTorch3D via a released wheel.
        pyt_version_str=torch.__version__.split("+")[0].replace(".", "")
        version_str="".join([
            f"py3{sys.version_info.minor}_cu",
            torch.version.cuda.replace(".",""),
            f"_pyt{pyt_version_str}"
        ])
        !pip install fvcore iopath
        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html
    else:
        # We try to install PyTorch3D from source.
        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'
```
After:
```
    pyt_version_str=torch.__version__.split("+")[0].replace(".", "")
    version_str="".join([
        f"py3{sys.version_info.minor}_cu",
        torch.version.cuda.replace(".",""),
        f"_pyt{pyt_version_str}"
    ])
    !pip install fvcore iopath
    if sys.platform.startswith("linux"):
      # We try to install PyTorch3D via a released wheel.
      !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html
      pip_list = !pip freeze
      need_pytorch3d = not any(i.startswith("pytorch3d==") for  i in pip_list)

    if need_pytorch3d:
        # We try to install PyTorch3D from source.
        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'
```

Reviewed By: bottler

Differential Revision: D55431832

fbshipit-source-id: a8de9162470698320241ae8401427dcb1ce17c37
 2024-03-28 11:24:43 -07:00
generatedunixname89002005307016
b215776f2d upgrade pyre version in fbcode/vision - batch 2 
Differential Revision: D55395614

fbshipit-source-id: 71677892b5d6f219f6df25b4efb51fb0f6b1441b
 2024-03-26 22:02:22 -07:00
Cijo Jose
38cf0dc1c5 TexturesUV multiple maps 
Summary: Implements the  the TexturesUV with multiple map ids.

Reviewed By: bottler

Differential Revision: D53944063

fbshipit-source-id: 06c25eb6d69f72db0484f16566dd2ca32a560b82
 2024-03-12 06:59:31 -07:00
Jaap Suter
7566530669 CUDA marching_cubes fix 
Summary:
Fix an inclusive vs exclusive scan mix-up that was accidentally introduced when removing the Thrust dependency (`Thrust::exclusive_scan`) and reimplementing it using `at::cumsum` (which does an inclusive scan).

This fixes two Github reported issues:

 * https://github.com/facebookresearch/pytorch3d/issues/1731
 * https://github.com/facebookresearch/pytorch3d/issues/1751

Reviewed By: bottler

Differential Revision: D54605545

fbshipit-source-id: da9e92f3f8a9a35f7b7191428d0b9a9ca03e0d4d
 2024-03-07 15:38:24 -08:00
Conner Nilsen
a27755db41 Pyre Configurationless migration for] [batch:85/112] [shard:6/N] 
Reviewed By: inseokhwang

Differential Revision: D54438157

fbshipit-source-id: a6acfe146ed29fff82123b5e458906d4b4cee6a2
 2024-03-04 18:30:37 -08:00
Amethyst Reese
3da7703c5a apply Black 2024 style in fbcode (4/16) 
Summary:
Formats the covered files with pyfmt.

paintitblack

Reviewed By: aleivag

Differential Revision: D54447727

fbshipit-source-id: 8844b1caa08de94d04ac4df3c768dbf8c865fd2f
 2024-03-02 17:31:19 -08:00
344 changed files with 2948 additions and 1306 deletions
Expand all files Collapse all files

476
.circleci/config.yml
View File

@@ -162,90 +162,6 @@ workflows:
jobs:
# - main:
# context: DOCKERHUB_TOKEN
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py38_cu113_pyt1120
python_version: '3.8'
pytorch_version: 1.12.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py38_cu116_pyt1120
python_version: '3.8'
pytorch_version: 1.12.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py38_cu113_pyt1121
python_version: '3.8'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py38_cu116_pyt1121
python_version: '3.8'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py38_cu116_pyt1130
python_version: '3.8'
pytorch_version: 1.13.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py38_cu117_pyt1130
python_version: '3.8'
pytorch_version: 1.13.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py38_cu116_pyt1131
python_version: '3.8'
pytorch_version: 1.13.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py38_cu117_pyt1131
python_version: '3.8'
pytorch_version: 1.13.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py38_cu117_pyt200
python_version: '3.8'
pytorch_version: 2.0.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py38_cu118_pyt200
python_version: '3.8'
pytorch_version: 2.0.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py38_cu117_pyt201
python_version: '3.8'
pytorch_version: 2.0.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py38_cu118_pyt201
python_version: '3.8'
pytorch_version: 2.0.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
@@ -303,89 +219,61 @@ workflows:
python_version: '3.8'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py39_cu113_pyt1120
python_version: '3.9'
pytorch_version: 1.12.0
cu_version: cu118
name: linux_conda_py38_cu118_pyt222
python_version: '3.8'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py39_cu116_pyt1120
python_version: '3.9'
pytorch_version: 1.12.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py39_cu113_pyt1121
python_version: '3.9'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py39_cu116_pyt1121
python_version: '3.9'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py39_cu116_pyt1130
python_version: '3.9'
pytorch_version: 1.13.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py39_cu117_pyt1130
python_version: '3.9'
pytorch_version: 1.13.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py39_cu116_pyt1131
python_version: '3.9'
pytorch_version: 1.13.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py39_cu117_pyt1131
python_version: '3.9'
pytorch_version: 1.13.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py39_cu117_pyt200
python_version: '3.9'
pytorch_version: 2.0.0
cu_version: cu121
name: linux_conda_py38_cu121_pyt222
python_version: '3.8'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py39_cu118_pyt200
python_version: '3.9'
pytorch_version: 2.0.0
name: linux_conda_py38_cu118_pyt231
python_version: '3.8'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py39_cu117_pyt201
python_version: '3.9'
pytorch_version: 2.0.1
cu_version: cu121
name: linux_conda_py38_cu121_pyt231
python_version: '3.8'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py39_cu118_pyt201
python_version: '3.9'
pytorch_version: 2.0.1
name: linux_conda_py38_cu118_pyt240
python_version: '3.8'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py38_cu121_pyt240
python_version: '3.8'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py38_cu118_pyt241
python_version: '3.8'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py38_cu121_pyt241
python_version: '3.8'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
@@ -443,89 +331,61 @@ workflows:
python_version: '3.9'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py310_cu113_pyt1120
python_version: '3.10'
pytorch_version: 1.12.0
cu_version: cu118
name: linux_conda_py39_cu118_pyt222
python_version: '3.9'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py310_cu116_pyt1120
python_version: '3.10'
pytorch_version: 1.12.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py310_cu113_pyt1121
python_version: '3.10'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py310_cu116_pyt1121
python_version: '3.10'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py310_cu116_pyt1130
python_version: '3.10'
pytorch_version: 1.13.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py310_cu117_pyt1130
python_version: '3.10'
pytorch_version: 1.13.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda116
context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py310_cu116_pyt1131
python_version: '3.10'
pytorch_version: 1.13.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py310_cu117_pyt1131
python_version: '3.10'
pytorch_version: 1.13.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py310_cu117_pyt200
python_version: '3.10'
pytorch_version: 2.0.0
cu_version: cu121
name: linux_conda_py39_cu121_pyt222
python_version: '3.9'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt200
python_version: '3.10'
pytorch_version: 2.0.0
name: linux_conda_py39_cu118_pyt231
python_version: '3.9'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py310_cu117_pyt201
python_version: '3.10'
pytorch_version: 2.0.1
cu_version: cu121
name: linux_conda_py39_cu121_pyt231
python_version: '3.9'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt201
python_version: '3.10'
pytorch_version: 2.0.1
name: linux_conda_py39_cu118_pyt240
python_version: '3.9'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py39_cu121_pyt240
python_version: '3.9'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py39_cu118_pyt241
python_version: '3.9'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py39_cu121_pyt241
python_version: '3.9'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
@@ -582,6 +442,62 @@ workflows:
name: linux_conda_py310_cu121_pyt220
python_version: '3.10'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt222
python_version: '3.10'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py310_cu121_pyt222
python_version: '3.10'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt231
python_version: '3.10'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py310_cu121_pyt231
python_version: '3.10'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt240
python_version: '3.10'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py310_cu121_pyt240
python_version: '3.10'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt241
python_version: '3.10'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py310_cu121_pyt241
python_version: '3.10'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
@@ -638,6 +554,62 @@ workflows:
name: linux_conda_py311_cu121_pyt220
python_version: '3.11'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py311_cu118_pyt222
python_version: '3.11'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py311_cu121_pyt222
python_version: '3.11'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py311_cu118_pyt231
python_version: '3.11'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py311_cu121_pyt231
python_version: '3.11'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py311_cu118_pyt240
python_version: '3.11'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py311_cu121_pyt240
python_version: '3.11'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py311_cu118_pyt241
python_version: '3.11'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py311_cu121_pyt241
python_version: '3.11'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
@@ -652,6 +624,62 @@ workflows:
name: linux_conda_py312_cu121_pyt220
python_version: '3.12'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py312_cu118_pyt222
python_version: '3.12'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py312_cu121_pyt222
python_version: '3.12'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py312_cu118_pyt231
python_version: '3.12'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py312_cu121_pyt231
python_version: '3.12'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py312_cu118_pyt240
python_version: '3.12'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py312_cu121_pyt240
python_version: '3.12'
pytorch_version: 2.4.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py312_cu118_pyt241
python_version: '3.12'
pytorch_version: 2.4.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py312_cu121_pyt241
python_version: '3.12'
pytorch_version: 2.4.1
- binary_linux_conda_cuda:
name: testrun_conda_cuda_py310_cu117_pyt201
context: DOCKERHUB_TOKEN

12
.circleci/regenerate.py
View File

@@ -19,16 +19,14 @@ from packaging import version
# The CUDA versions which have pytorch conda packages available for linux for each
# version of pytorch.
CONDA_CUDA_VERSIONS = {
"1.12.0": ["cu113", "cu116"],
"1.12.1": ["cu113", "cu116"],
"1.13.0": ["cu116", "cu117"],
"1.13.1": ["cu116", "cu117"],
"2.0.0": ["cu117", "cu118"],
"2.0.1": ["cu117", "cu118"],
"2.1.0": ["cu118", "cu121"],
"2.1.1": ["cu118", "cu121"],
"2.1.2": ["cu118", "cu121"],
"2.2.0": ["cu118", "cu121"],
"2.2.2": ["cu118", "cu121"],
"2.3.1": ["cu118", "cu121"],
"2.4.0": ["cu118", "cu121"],
"2.4.1": ["cu118", "cu121"],
}
@@ -90,7 +88,6 @@ def workflow_pair(
upload=False,
filter_branch,
):
w = []
py = python_version.replace(".", "")
pyt = pytorch_version.replace(".", "")
@@ -129,7 +126,6 @@ def generate_base_workflow(
btype,
filter_branch=None,
):
d = {
"name": base_workflow_name,
"python_version": python_version,

23
.github/workflows/build.yml vendored Normal file
View File

@@ -0,0 +1,23 @@
name: facebookresearch/pytorch3d/build_and_test
on:
pull_request:
branches:
- main
push:
branches:
- main
jobs:
binary_linux_conda_cuda:
runs-on: 4-core-ubuntu-gpu-t4
env:
PYTHON_VERSION: "3.12"
BUILD_VERSION: "${{ github.run_number }}"
PYTORCH_VERSION: "2.4.1"
CU_VERSION: "cu121"
JUST_TESTRUN: 1
steps:
- uses: actions/checkout@v4
- name: Build and run tests
run: |-
conda create --name env --yes --quiet conda-build
conda run --no-capture-output --name env python3 ./packaging/build_conda.py --use-conda-cuda

11
INSTALL.md
View File

@@ -8,11 +8,10 @@
The core library is written in PyTorch. Several components have underlying implementation in CUDA for improved performance. A subset of these components have CPU implementations in C++/PyTorch. It is advised to use PyTorch3D with GPU support in order to use all the features.
- Linux or macOS or Windows
- Python 3.8, 3.9 or 3.10
- PyTorch 1.12.0, 1.12.1, 1.13.0, 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.1.2 or 2.2.0.
- Python
- PyTorch 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2.2.2, 2.3.0, 2.3.1, 2.4.0 or 2.4.1.
- torchvision that matches the PyTorch installation. You can install them together as explained at pytorch.org to make sure of this.
- gcc & g++ ≥ 4.9
- [fvcore](https://github.com/facebookresearch/fvcore)
- [ioPath](https://github.com/facebookresearch/iopath)
- If CUDA is to be used, use a version which is supported by the corresponding pytorch version and at least version 9.2.
- If CUDA older than 11.7 is to be used and you are building from source, the CUB library must be available. We recommend version 1.10.0.
@@ -22,7 +21,7 @@ The runtime dependencies can be installed by running:
conda create -n pytorch3d python=3.9
conda activate pytorch3d
conda install pytorch=1.13.0 torchvision pytorch-cuda=11.6 -c pytorch -c nvidia
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -c iopath iopath
```
For the CUB build time dependency, which you only need if you have CUDA older than 11.7, if you are using conda, you can continue with
@@ -49,6 +48,7 @@ For developing on top of PyTorch3D or contributing, you will need to run the lin
- tdqm
- jupyter
- imageio
- fvcore
- plotly
- opencv-python
@@ -59,6 +59,7 @@ conda install jupyter
pip install scikit-image matplotlib imageio plotly opencv-python
# Tests/Linting
conda install -c fvcore -c conda-forge fvcore
pip install black usort flake8 flake8-bugbear flake8-comprehensions
```
@@ -97,7 +98,7 @@ version_str="".join([
torch.version.cuda.replace(".",""),
f"_pyt{pyt_version_str}"
])
!pip install fvcore iopath
!pip install iopath
!pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html
```

2
dev/linter.sh
View File

@@ -36,5 +36,5 @@ then
echo "Running pyre..."
echo "To restart/kill pyre server, run 'pyre restart' or 'pyre kill' in fbcode/"
( cd ~/fbsource/fbcode; pyre -l vision/fair/pytorch3d/ )
( cd ~/fbsource/fbcode; arc pyre check //vision/fair/pytorch3d/... )
fi

2
dev/run_tutorials.sh
View File

@@ -23,7 +23,7 @@ conda init bash
source ~/.bashrc
conda create -y -n myenv python=3.8 matplotlib ipython ipywidgets nbconvert
conda activate myenv
conda install -y -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -y -c iopath iopath
conda install -y -c pytorch pytorch=1.6.0 cudatoolkit=10.1 torchvision
conda install -y -c pytorch3d-nightly pytorch3d
pip install plotly scikit-image

1
docs/examples/pulsar_basic.py
View File

@@ -10,6 +10,7 @@ This example demonstrates the most trivial, direct interface of the pulsar
sphere renderer. It renders and saves an image with 10 random spheres.
Output: basic.png.
"""
import logging
import math
from os import path

1
docs/examples/pulsar_basic_unified.py
View File

@@ -11,6 +11,7 @@ interface for sphere renderering. It renders and saves an image with
10 random spheres.
Output: basic-pt3d.png.
"""
import logging
from os import path

1
docs/examples/pulsar_cam.py
View File

@@ -14,6 +14,7 @@ distorted. Gradient-based optimization is used to converge towards the
original camera parameters.
Output: cam.gif.
"""
import logging
import math
from os import path

1
docs/examples/pulsar_cam_unified.py
View File

@@ -14,6 +14,7 @@ distorted. Gradient-based optimization is used to converge towards the
original camera parameters.
Output: cam-pt3d.gif
"""
import logging
from os import path

1
docs/examples/pulsar_multiview.py
View File

@@ -18,6 +18,7 @@ This example is not available yet through the 'unified' interface,
because opacity support has not landed in PyTorch3D for general data
structures yet.
"""
import logging
import math
from os import path

1
docs/examples/pulsar_optimization.py
View File

@@ -13,6 +13,7 @@ The scene is initialized with random spheres. Gradient-based
optimization is used to converge towards a faithful
scene representation.
"""
import logging
import math

1
docs/examples/pulsar_optimization_unified.py
View File

@@ -13,6 +13,7 @@ The scene is initialized with random spheres. Gradient-based
optimization is used to converge towards a faithful
scene representation.
"""
import logging
import math

1
docs/requirements.txt
View File

@@ -5,7 +5,6 @@ sphinx_rtd_theme
sphinx_markdown_tables
numpy
iopath
fvcore
https://download.pytorch.org/whl/cpu/torchvision-0.15.2%2Bcpu-cp311-cp311-linux_x86_64.whl
https://download.pytorch.org/whl/cpu/torch-2.0.1%2Bcpu-cp311-cp311-linux_x86_64.whl
omegaconf

30
docs/tutorials/bundle_adjustment.ipynb
View File

@@ -83,25 +83,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/camera_position_optimization_with_differentiable_rendering.ipynb
View File

@@ -70,25 +70,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

32
docs/tutorials/dataloaders_ShapeNetCore_R2N2.ipynb
View File

@@ -45,25 +45,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{
@@ -405,7 +411,7 @@
"outputs": [],
"source": [
"random_model_images = shapenet_dataset.render(\n",
" sample_nums=[3],\n",
" sample_nums=[5],\n",
" device=device,\n",
" cameras=cameras,\n",
" raster_settings=raster_settings,\n",

30
docs/tutorials/deform_source_mesh_to_target_mesh.ipynb
View File

@@ -84,25 +84,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/fit_simple_neural_radiance_field.ipynb
View File

@@ -50,25 +50,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/fit_textured_mesh.ipynb
View File

@@ -62,25 +62,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/fit_textured_volume.ipynb
View File

@@ -41,25 +41,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/implicitron_config_system.ipynb
View File

@@ -72,25 +72,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/implicitron_volumes.ipynb
View File

@@ -66,25 +66,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/render_colored_points.ipynb
View File

@@ -44,25 +44,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/render_densepose.ipynb
View File

@@ -51,25 +51,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

30
docs/tutorials/render_textured_meshes.ipynb
View File

@@ -67,25 +67,31 @@
"import os\n",
"import sys\n",
"import torch\n",
"import subprocess\n",
"need_pytorch3d=False\n",
"try:\n",
" import pytorch3d\n",
"except ModuleNotFoundError:\n",
" need_pytorch3d=True\n",
"if need_pytorch3d:\n",
" if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
" # We try to install PyTorch3D via a released wheel.\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install fvcore iopath\n",
" pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
" version_str=\"\".join([\n",
" f\"py3{sys.version_info.minor}_cu\",\n",
" torch.version.cuda.replace(\".\",\"\"),\n",
" f\"_pyt{pyt_version_str}\"\n",
" ])\n",
" !pip install iopath\n",
" if sys.platform.startswith(\"linux\"):\n",
" print(\"Trying to install wheel for PyTorch3D\")\n",
" !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
" else:\n",
" # We try to install PyTorch3D from source.\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
" pip_list = !pip freeze\n",
" need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for i in pip_list)\n",
" if need_pytorch3d:\n",
" print(f\"failed to find/install wheel for {version_str}\")\n",
"if need_pytorch3d:\n",
" print(\"Installing PyTorch3D from source\")\n",
" !pip install ninja\n",
" !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
]
},
{

43
packaging/build_conda.py
View File

@@ -4,10 +4,11 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os.path
import runpy
import subprocess
from typing import List
from typing import List, Tuple
# required env vars:
# CU_VERSION: E.g. cu112
@@ -23,7 +24,7 @@ pytorch_major_minor = tuple(int(i) for i in PYTORCH_VERSION.split(".")[:2])
source_root_dir = os.environ["PWD"]
def version_constraint(version):
def version_constraint(version) -> str:
"""
Given version "11.3" returns " >=11.3,<11.4"
"""
@@ -32,7 +33,7 @@ def version_constraint(version):
return f" >={version},<{upper}"
def get_cuda_major_minor():
def get_cuda_major_minor() -> Tuple[str, str]:
if CU_VERSION == "cpu":
raise ValueError("fn only for cuda builds")
if len(CU_VERSION) != 5 or CU_VERSION[:2] != "cu":
@@ -42,11 +43,10 @@ def get_cuda_major_minor():
return major, minor
def setup_cuda():
def setup_cuda(use_conda_cuda: bool) -> List[str]:
if CU_VERSION == "cpu":
return
return []
major, minor = get_cuda_major_minor()
os.environ["CUDA_HOME"] = f"/usr/local/cuda-{major}.{minor}/"
os.environ["FORCE_CUDA"] = "1"
basic_nvcc_flags = (
@@ -75,11 +75,26 @@ def setup_cuda():
if os.environ.get("JUST_TESTRUN", "0") != "1":
os.environ["NVCC_FLAGS"] = nvcc_flags
if use_conda_cuda:
os.environ["CONDA_CUDA_TOOLKIT_BUILD_CONSTRAINT1"] = "- cuda-toolkit"
os.environ["CONDA_CUDA_TOOLKIT_BUILD_CONSTRAINT2"] = (
f"- cuda-version={major}.{minor}"
)
return ["-c", f"nvidia/label/cuda-{major}.{minor}.0"]
else:
os.environ["CUDA_HOME"] = f"/usr/local/cuda-{major}.{minor}/"
return []
def setup_conda_pytorch_constraint() -> List[str]:
pytorch_constraint = f"- pytorch=={PYTORCH_VERSION}"
os.environ["CONDA_PYTORCH_CONSTRAINT"] = pytorch_constraint
if pytorch_major_minor < (2, 2):
os.environ["CONDA_PYTORCH_MKL_CONSTRAINT"] = "- mkl!=2024.1.0"
os.environ["SETUPTOOLS_CONSTRAINT"] = "- setuptools<70"
else:
os.environ["CONDA_PYTORCH_MKL_CONSTRAINT"] = ""
os.environ["SETUPTOOLS_CONSTRAINT"] = "- setuptools"
os.environ["CONDA_PYTORCH_BUILD_CONSTRAINT"] = pytorch_constraint
os.environ["PYTORCH_VERSION_NODOT"] = PYTORCH_VERSION.replace(".", "")
@@ -89,7 +104,7 @@ def setup_conda_pytorch_constraint() -> List[str]:
return ["-c", "pytorch", "-c", "nvidia"]
def setup_conda_cudatoolkit_constraint():
def setup_conda_cudatoolkit_constraint() -> None:
if CU_VERSION == "cpu":
os.environ["CONDA_CPUONLY_FEATURE"] = "- cpuonly"
os.environ["CONDA_CUDATOOLKIT_CONSTRAINT"] = ""
@@ -110,14 +125,14 @@ def setup_conda_cudatoolkit_constraint():
os.environ["CONDA_CUDATOOLKIT_CONSTRAINT"] = toolkit
def do_build(start_args: List[str]):
def do_build(start_args: List[str]) -> None:
args = start_args.copy()
test_flag = os.environ.get("TEST_FLAG")
if test_flag is not None:
args.append(test_flag)
args.extend(["-c", "bottler", "-c", "fvcore", "-c", "iopath", "-c", "conda-forge"])
args.extend(["-c", "bottler", "-c", "iopath", "-c", "conda-forge"])
args.append("--no-anaconda-upload")
args.extend(["--python", os.environ["PYTHON_VERSION"]])
args.append("packaging/pytorch3d")
@@ -126,8 +141,16 @@ def do_build(start_args: List[str]):
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Build the conda package.")
parser.add_argument(
"--use-conda-cuda",
action="store_true",
help="get cuda from conda ignoring local cuda",
)
our_args = parser.parse_args()
args = ["conda", "build"]
setup_cuda()
args += setup_cuda(use_conda_cuda=our_args.use_conda_cuda)
init_path = source_root_dir + "/pytorch3d/__init__.py"
build_version = runpy.run_path(init_path)["__version__"]

2
packaging/linux_wheels/README.md
View File

@@ -26,6 +26,6 @@ version_str="".join([
torch.version.cuda.replace(".",""),
f"_pyt{pyt_version_str}"
])
!pip install fvcore iopath
!pip install iopath
!pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html
```

2
packaging/linux_wheels/inside.sh
View File

@@ -144,7 +144,7 @@ do
conda activate "$tag"
# shellcheck disable=SC2086
conda install -y -c pytorch $extra_channel "pytorch=$pytorch_version" "$cudatools=$CUDA_TAG"
pip install fvcore iopath
pip install iopath
echo "python version" "$python_version" "pytorch version" "$pytorch_version" "cuda version" "$cu_version" "tag" "$tag"
rm -rf dist

13
packaging/pytorch3d/meta.yaml
View File

@@ -8,12 +8,16 @@ source:
requirements:
build:
- {{ compiler('c') }} # [win]
{{ environ.get('CONDA_CUDA_TOOLKIT_BUILD_CONSTRAINT1', '') }}
{{ environ.get('CONDA_CUDA_TOOLKIT_BUILD_CONSTRAINT2', '') }}
{{ environ.get('CONDA_CUB_CONSTRAINT') }}
host:
- python
- setuptools
- mkl =2023 # [x86_64]
{{ environ.get('SETUPTOOLS_CONSTRAINT') }}
{{ environ.get('CONDA_PYTORCH_BUILD_CONSTRAINT') }}
{{ environ.get('CONDA_PYTORCH_MKL_CONSTRAINT') }}
{{ environ.get('CONDA_CUDATOOLKIT_CONSTRAINT') }}
{{ environ.get('CONDA_CPUONLY_FEATURE') }}
@@ -21,7 +25,7 @@ requirements:
- python
- numpy >=1.11
- torchvision >=0.5
- fvcore
- mkl =2023 # [x86_64]
- iopath
{{ environ.get('CONDA_PYTORCH_CONSTRAINT') }}
{{ environ.get('CONDA_CUDATOOLKIT_CONSTRAINT') }}
@@ -47,8 +51,11 @@ test:
- imageio
- hydra-core
- accelerate
- matplotlib
- tabulate
- pandas
- sqlalchemy
commands:
#pytest .
python -m unittest discover -v -s tests -t .

2
projects/implicitron_trainer/__init__.py
View File

@@ -3,3 +3,5 @@
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe

11
projects/implicitron_trainer/experiment.py
View File

@@ -5,7 +5,9 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
""""
# pyre-unsafe
""" "
This file is the entry point for launching experiments with Implicitron.
Launch Training
@@ -42,6 +44,7 @@ The outputs of the experiment are saved and logged in multiple ways:
config file.
"""
import logging
import os
import warnings
@@ -97,7 +100,7 @@ except ModuleNotFoundError:
no_accelerate = os.environ.get("PYTORCH3D_NO_ACCELERATE") is not None
class Experiment(Configurable): # pyre-ignore: 13
class Experiment(Configurable):
"""
This class is at the top level of Implicitron's config hierarchy. Its
members are high-level components necessary for training an implicit rende-
@@ -118,12 +121,16 @@ class Experiment(Configurable): # pyre-ignore: 13
will be saved here.
"""
# pyre-fixme[13]: Attribute `data_source` is never initialized.
data_source: DataSourceBase
data_source_class_type: str = "ImplicitronDataSource"
# pyre-fixme[13]: Attribute `model_factory` is never initialized.
model_factory: ModelFactoryBase
model_factory_class_type: str = "ImplicitronModelFactory"
# pyre-fixme[13]: Attribute `optimizer_factory` is never initialized.
optimizer_factory: OptimizerFactoryBase
optimizer_factory_class_type: str = "ImplicitronOptimizerFactory"
# pyre-fixme[13]: Attribute `training_loop` is never initialized.
training_loop: TrainingLoopBase
training_loop_class_type: str = "ImplicitronTrainingLoop"

2
projects/implicitron_trainer/impl/__init__.py
View File

@@ -3,3 +3,5 @@
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe

10
projects/implicitron_trainer/impl/model_factory.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import logging
import os
from typing import Optional
@@ -24,7 +26,6 @@ logger = logging.getLogger(__name__)
class ModelFactoryBase(ReplaceableBase):
resume: bool = True # resume from the last checkpoint
def __call__(self, **kwargs) -> ImplicitronModelBase:
@@ -43,7 +44,7 @@ class ModelFactoryBase(ReplaceableBase):
@registry.register
class ImplicitronModelFactory(ModelFactoryBase): # pyre-ignore [13]
class ImplicitronModelFactory(ModelFactoryBase):
"""
A factory class that initializes an implicit rendering model.
@@ -59,6 +60,7 @@ class ImplicitronModelFactory(ModelFactoryBase): # pyre-ignore [13]
"""
# pyre-fixme[13]: Attribute `model` is never initialized.
model: ImplicitronModelBase
model_class_type: str = "GenericModel"
resume: bool = True
@@ -113,7 +115,9 @@ class ImplicitronModelFactory(ModelFactoryBase): # pyre-ignore [13]
"cuda:%d" % 0: "cuda:%d" % accelerator.local_process_index
}
model_state_dict = torch.load(
model_io.get_model_path(model_path), map_location=map_location
model_io.get_model_path(model_path),
map_location=map_location,
weights_only=True,
)
try:

5
projects/implicitron_trainer/impl/optimizer_factory.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import inspect
import logging
import os
@@ -121,6 +123,7 @@ class ImplicitronOptimizerFactory(OptimizerFactoryBase):
"""
# Get the parameters to optimize
if hasattr(model, "_get_param_groups"): # use the model function
# pyre-fixme[29]: `Union[Tensor, Module]` is not a function.
p_groups = model._get_param_groups(self.lr, wd=self.weight_decay)
else:
p_groups = [
@@ -239,7 +242,7 @@ class ImplicitronOptimizerFactory(OptimizerFactoryBase):
map_location = {
"cuda:%d" % 0: "cuda:%d" % accelerator.local_process_index
}
optimizer_state = torch.load(opt_path, map_location)
optimizer_state = torch.load(opt_path, map_location, weights_only=True)
else:
raise FileNotFoundError(f"Optimizer state {opt_path} does not exist.")
return optimizer_state

6
projects/implicitron_trainer/impl/training_loop.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import logging
import os
import time
@@ -28,13 +30,13 @@ from .utils import seed_all_random_engines
logger = logging.getLogger(__name__)
# pyre-fixme[13]: Attribute `evaluator` is never initialized.
class TrainingLoopBase(ReplaceableBase):
"""
Members:
evaluator: An EvaluatorBase instance, used to evaluate training results.
"""
# pyre-fixme[13]: Attribute `evaluator` is never initialized.
evaluator: Optional[EvaluatorBase]
evaluator_class_type: Optional[str] = "ImplicitronEvaluator"
@@ -159,7 +161,6 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
for epoch in range(start_epoch, self.max_epochs):
# automatic new_epoch and plotting of stats at every epoch start
with stats:
# Make sure to re-seed random generators to ensure reproducibility
# even after restart.
seed_all_random_engines(seed + epoch)
@@ -393,6 +394,7 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
):
prefix = f"e{stats.epoch}_it{stats.it[trainmode]}"
if hasattr(model, "visualize"):
# pyre-fixme[29]: `Union[Tensor, Module]` is not a function.
model.visualize(
viz,
visdom_env_imgs,

2
projects/implicitron_trainer/impl/utils.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import random

2
projects/implicitron_trainer/tests/__init__.py
View File

@@ -3,3 +3,5 @@
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe

22
projects/implicitron_trainer/tests/test_experiment.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import os
import tempfile
import unittest
@@ -51,12 +53,8 @@ class TestExperiment(unittest.TestCase):
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_class_type = (
"JsonIndexDatasetMapProvider"
)
dataset_args = (
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
)
dataloader_args = (
cfg.data_source_ImplicitronDataSource_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
)
dataset_args = cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
dataloader_args = cfg.data_source_ImplicitronDataSource_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
dataset_args.category = "skateboard"
dataset_args.test_restrict_sequence_id = 0
dataset_args.dataset_root = "manifold://co3d/tree/extracted"
@@ -92,12 +90,8 @@ class TestExperiment(unittest.TestCase):
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_class_type = (
"JsonIndexDatasetMapProvider"
)
dataset_args = (
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
)
dataloader_args = (
cfg.data_source_ImplicitronDataSource_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
)
dataset_args = cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
dataloader_args = cfg.data_source_ImplicitronDataSource_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
dataset_args.category = "skateboard"
dataset_args.test_restrict_sequence_id = 0
dataset_args.dataset_root = "manifold://co3d/tree/extracted"
@@ -109,9 +103,7 @@ class TestExperiment(unittest.TestCase):
cfg.training_loop_ImplicitronTrainingLoop_args.max_epochs = 2
cfg.training_loop_ImplicitronTrainingLoop_args.store_checkpoints = False
cfg.optimizer_factory_ImplicitronOptimizerFactory_args.lr_policy = "Exponential"
cfg.optimizer_factory_ImplicitronOptimizerFactory_args.exponential_lr_step_size = (
2
)
cfg.optimizer_factory_ImplicitronOptimizerFactory_args.exponential_lr_step_size = 2
if DEBUG:
experiment.dump_cfg(cfg)

7
projects/implicitron_trainer/tests/test_optimizer_factory.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import logging
import os
import unittest
@@ -79,8 +81,9 @@ class TestOptimizerFactory(unittest.TestCase):
def test_param_overrides_self_param_group_assignment(self):
pa, pb, pc = [torch.nn.Parameter(data=torch.tensor(i * 1.0)) for i in range(3)]
na, nb = Node(params=[pa]), Node(
params=[pb], param_groups={"self": "pb_self", "p1": "pb_param"}
na, nb = (
Node(params=[pa]),
Node(params=[pb], param_groups={"self": "pb_self", "p1": "pb_param"}),
)
root = Node(children=[na, nb], params=[pc], param_groups={"m1": "pb_member"})
param_groups = self._get_param_groups(root)

2
projects/implicitron_trainer/tests/test_visualize.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import os
import unittest

2
projects/implicitron_trainer/tests/utils.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import contextlib
import logging
import os

2
projects/implicitron_trainer/visualize_reconstruction.py
View File

@@ -5,6 +5,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
"""
Script to visualize a previously trained model. Example call:

4
projects/nerf/nerf/dataset.py
View File

@@ -84,9 +84,9 @@ def get_nerf_datasets(
if autodownload and any(not os.path.isfile(p) for p in (cameras_path, image_path)):
# Automatically download the data files if missing.
download_data((dataset_name,), data_root=data_root)
download_data([dataset_name], data_root=data_root)
train_data = torch.load(cameras_path)
train_data = torch.load(cameras_path, weights_only=True)
n_cameras = train_data["cameras"]["R"].shape[0]
_image_max_image_pixels = Image.MAX_IMAGE_PIXELS

14
projects/nerf/nerf/nerf_renderer.py
View File

@@ -343,12 +343,14 @@ class RadianceFieldRenderer(torch.nn.Module):
# For a full render pass concatenate the output chunks,
# and reshape to image size.
out = {
k: torch.cat(
[ch_o[k] for ch_o in chunk_outputs],
dim=1,
).view(-1, *self._image_size, 3)
if chunk_outputs[0][k] is not None
else None
k: (
torch.cat(
[ch_o[k] for ch_o in chunk_outputs],
dim=1,
).view(-1, *self._image_size, 3)
if chunk_outputs[0][k] is not None
else None
)
for k in ("rgb_fine", "rgb_coarse", "rgb_gt")
}
else:

1
projects/nerf/nerf/stats.py
View File

@@ -194,7 +194,6 @@ class Stats:
it = self.it[stat_set]
for stat in self.log_vars:
if stat not in self.stats[stat_set]:
self.stats[stat_set][stat] = AverageMeter()

3
projects/nerf/test_nerf.py
View File

@@ -24,7 +24,6 @@ CONFIG_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "configs"
@hydra.main(config_path=CONFIG_DIR, config_name="lego")
def main(cfg: DictConfig):
# Device on which to run.
if torch.cuda.is_available():
device = "cuda"
@@ -63,7 +62,7 @@ def main(cfg: DictConfig):
raise ValueError(f"Model checkpoint {checkpoint_path} does not exist!")
print(f"Loading checkpoint {checkpoint_path}.")
loaded_data = torch.load(checkpoint_path)
loaded_data = torch.load(checkpoint_path, weights_only=True)
# Do not load the cached xy grid.
# - this allows setting an arbitrary evaluation image size.
state_dict = {

1
projects/nerf/tests/test_raysampler.py
View File

@@ -42,7 +42,6 @@ class TestRaysampler(unittest.TestCase):
cameras, rays = [], []
for _ in range(batch_size):
R = random_rotations(1)
T = torch.randn(1, 3)
focal_length = torch.rand(1, 2) + 0.5

4
projects/nerf/train_nerf.py
View File

@@ -25,7 +25,6 @@ CONFIG_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "configs"
@hydra.main(config_path=CONFIG_DIR, config_name="lego")
def main(cfg: DictConfig):
# Set the relevant seeds for reproducibility.
np.random.seed(cfg.seed)
torch.manual_seed(cfg.seed)
@@ -77,7 +76,7 @@ def main(cfg: DictConfig):
# Resume training if requested.
if cfg.resume and os.path.isfile(checkpoint_path):
print(f"Resuming from checkpoint {checkpoint_path}.")
loaded_data = torch.load(checkpoint_path)
loaded_data = torch.load(checkpoint_path, weights_only=True)
model.load_state_dict(loaded_data["model"])
stats = pickle.loads(loaded_data["stats"])
print(f" => resuming from epoch {stats.epoch}.")
@@ -219,7 +218,6 @@ def main(cfg: DictConfig):
# Validation
if epoch % cfg.validation_epoch_interval == 0 and epoch > 0:
# Sample a validation camera/image.
val_batch = next(val_dataloader.__iter__())
val_image, val_camera, camera_idx = val_batch[0].values()

4
pytorch3d/__init__.py
View File

@@ -4,4 +4,6 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
__version__ = "0.7.6"
# pyre-unsafe
__version__ = "0.7.8"

2
pytorch3d/common/__init__.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
from .datatypes import Device, get_device, make_device

4
pytorch3d/common/compat.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
from typing import Sequence, Tuple, Union
import torch
@@ -15,7 +17,7 @@ Some functions which depend on PyTorch or Python versions.
def meshgrid_ij(
*A: Union[torch.Tensor, Sequence[torch.Tensor]]
*A: Union[torch.Tensor, Sequence[torch.Tensor]],
) -> Tuple[torch.Tensor, ...]: # pragma: no cover
"""
Like torch.meshgrid was before PyTorch 1.10.0, i.e. with indexing set to ij

2
pytorch3d/common/datatypes.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
from typing import Optional, Union
import torch

2
pytorch3d/common/linear_with_repeat.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import math
from typing import Tuple

2
pytorch3d/common/workaround/__init__.py
View File

@@ -4,5 +4,7 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
from .symeig3x3 import symeig3x3
from .utils import _safe_det_3x3

2
pytorch3d/common/workaround/symeig3x3.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import math
from typing import Optional, Tuple

2
pytorch3d/common/workaround/utils.py
View File

@@ -4,6 +4,8 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# pyre-unsafe
import torch

1
pytorch3d/csrc/ball_query/ball_query_cpu.cpp
View File

@@ -7,7 +7,6 @@
*/
#include <torch/extension.h>
#include <queue>
#include <tuple>
std::tuple<at::Tensor, at::Tensor> BallQueryCpu(

2
pytorch3d/csrc/compositing/alpha_composite.cu
View File

@@ -28,7 +28,6 @@ __global__ void alphaCompositeCudaForwardKernel(
const at::PackedTensorAccessor64<float, 4, at::RestrictPtrTraits> alphas,
const at::PackedTensorAccessor64<int64_t, 4, at::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = result.size(0);
const int64_t C = features.size(0);
const int64_t H = points_idx.size(2);
const int64_t W = points_idx.size(3);
@@ -79,7 +78,6 @@ __global__ void alphaCompositeCudaBackwardKernel(
const at::PackedTensorAccessor64<float, 4, at::RestrictPtrTraits> alphas,
const at::PackedTensorAccessor64<int64_t, 4, at::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = points_idx.size(0);
const int64_t C = features.size(0);
const int64_t H = points_idx.size(2);
const int64_t W = points_idx.size(3);

2
pytorch3d/csrc/compositing/norm_weighted_sum.cu
View File

@@ -28,7 +28,6 @@ __global__ void weightedSumNormCudaForwardKernel(
const at::PackedTensorAccessor64<float, 4, at::RestrictPtrTraits> alphas,
const at::PackedTensorAccessor64<int64_t, 4, at::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = result.size(0);
const int64_t C = features.size(0);
const int64_t H = points_idx.size(2);
const int64_t W = points_idx.size(3);
@@ -92,7 +91,6 @@ __global__ void weightedSumNormCudaBackwardKernel(
const at::PackedTensorAccessor64<float, 4, at::RestrictPtrTraits> alphas,
const at::PackedTensorAccessor64<int64_t, 4, at::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = points_idx.size(0);
const int64_t C = features.size(0);
const int64_t H = points_idx.size(2);
const int64_t W = points_idx.size(3);

2
pytorch3d/csrc/compositing/weighted_sum.cu
View File

@@ -26,7 +26,6 @@ __global__ void weightedSumCudaForwardKernel(
const at::PackedTensorAccessor64<float, 4, at::RestrictPtrTraits> alphas,
const at::PackedTensorAccessor64<int64_t, 4, at::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = result.size(0);
const int64_t C = features.size(0);
const int64_t H = points_idx.size(2);
const int64_t W = points_idx.size(3);
@@ -74,7 +73,6 @@ __global__ void weightedSumCudaBackwardKernel(
const at::PackedTensorAccessor64<float, 4, at::RestrictPtrTraits> alphas,
const at::PackedTensorAccessor64<int64_t, 4, at::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = points_idx.size(0);
const int64_t C = features.size(0);
const int64_t H = points_idx.size(2);
const int64_t W = points_idx.size(3);

7
pytorch3d/csrc/ext.cpp
View File

@@ -99,6 +99,7 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("marching_cubes", &MarchingCubes);
// Pulsar.
// Pulsar not enabled on AMD.
#ifdef PULSAR_LOGGING_ENABLED
c10::ShowLogInfoToStderr();
#endif
@@ -148,10 +149,10 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
py::arg("gamma"),
py::arg("max_depth"),
py::arg("min_depth") /* = 0.f*/,
py::arg(
"bg_col") /* = at::nullopt not exposed properly in pytorch 1.1. */
py::arg("bg_col") /* = std::nullopt not exposed properly in
pytorch 1.1. */
,
py::arg("opacity") /* = at::nullopt ... */,
py::arg("opacity") /* = std::nullopt ... */,
py::arg("percent_allowed_difference") = 0.01f,
py::arg("max_n_hits") = MAX_UINT,
py::arg("mode") = 0)

3
pytorch3d/csrc/iou_box3d/iou_box3d_cpu.cpp
View File

@@ -7,10 +7,7 @@
*/
#include <torch/extension.h>
#include <torch/torch.h>
#include <list>
#include <numeric>
#include <queue>
#include <tuple>
#include "iou_box3d/iou_utils.h"

5
pytorch3d/csrc/iou_box3d/iou_utils.cuh
View File

@@ -461,10 +461,8 @@ __device__ inline std::tuple<float3, float3> ArgMaxVerts(
__device__ inline bool IsCoplanarTriTri(
const FaceVerts& tri1,
const FaceVerts& tri2) {
const float3 tri1_ctr = FaceCenter({tri1.v0, tri1.v1, tri1.v2});
const float3 tri1_n = FaceNormal({tri1.v0, tri1.v1, tri1.v2});
const float3 tri2_ctr = FaceCenter({tri2.v0, tri2.v1, tri2.v2});
const float3 tri2_n = FaceNormal({tri2.v0, tri2.v1, tri2.v2});
// Check if parallel
@@ -500,7 +498,6 @@ __device__ inline bool IsCoplanarTriPlane(
const FaceVerts& tri,
const FaceVerts& plane,
const float3& normal) {
const float3 tri_ctr = FaceCenter({tri.v0, tri.v1, tri.v2});
const float3 nt = FaceNormal({tri.v0, tri.v1, tri.v2});
// check if parallel
@@ -728,7 +725,7 @@ __device__ inline int BoxIntersections(
}
}
// Update the face_verts_out tris
num_tris = offset;
num_tris = min(MAX_TRIS, offset);
for (int j = 0; j < num_tris; ++j) {
face_verts_out[j] = tri_verts_updated[j];
}

2
pytorch3d/csrc/knn/knn.cu
View File

@@ -338,7 +338,7 @@ std::tuple<at::Tensor, at::Tensor> KNearestNeighborIdxCuda(
TORCH_CHECK((norm == 1) || (norm == 2), "Norm must be 1 or 2.");
TORCH_CHECK(p2.size(2) == D, "Point sets must have the same last dimension");
TORCH_CHECK(p1.size(2) == D, "Point sets must have the same last dimension");
auto long_dtype = lengths1.options().dtype(at::kLong);
auto idxs = at::zeros({N, P1, K}, long_dtype);
auto dists = at::zeros({N, P1, K}, p1.options());

70
pytorch3d/csrc/marching_cubes/marching_cubes.cu
View File

@@ -382,6 +382,44 @@ __global__ void GenerateFacesKernel(
} // end for grid-strided kernel
}
// ATen/Torch does not have an exclusive-scan operator. Additionally, in the
// code below we need to get the "total number of items to work on" after
// a scan, which with an inclusive-scan would simply be the value of the last
// element in the tensor.
//
// This utility function hits two birds with one stone, by running
// an inclusive-scan into a right-shifted view of a tensor that's
// allocated to be one element bigger than the input tensor.
//
// Note; return tensor is `int64_t` per element, even if the input
// tensor is only 32-bit. Also, the return tensor is one element bigger
// than the input one.
//
// Secondary optional argument is an output argument that gets the
// value of the last element of the return tensor (because you almost
// always need this CPU-side right after this function anyway).
static at::Tensor ExclusiveScanAndTotal(
const at::Tensor& inTensor,
int64_t* optTotal = nullptr) {
const auto inSize = inTensor.sizes()[0];
auto retTensor = at::zeros({inSize + 1}, at::kLong).to(inTensor.device());
using at::indexing::None;
using at::indexing::Slice;
auto rightShiftedView = retTensor.index({Slice(1, None)});
// Do an (inclusive-scan) cumulative sum in to the view that's
// shifted one element to the right...
at::cumsum_out(rightShiftedView, inTensor, 0, at::kLong);
if (optTotal) {
*optTotal = retTensor[inSize].cpu().item<int64_t>();
}
// ...so that the not-shifted tensor holds the exclusive-scan
return retTensor;
}
// Entrance for marching cubes cuda extension. Marching Cubes is an algorithm to
// create triangle meshes from an implicit function (one of the form f(x, y, z)
// = 0). It works by iteratively checking a grid of cubes superimposed over a
@@ -444,20 +482,18 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
using at::indexing::Slice;
auto d_voxelVerts =
at::zeros({numVoxels + 1}, at::TensorOptions().dtype(at::kInt))
at::zeros({numVoxels}, at::TensorOptions().dtype(at::kInt))
.to(vol.device());
auto d_voxelVerts_ = d_voxelVerts.index({Slice(1, None)});
auto d_voxelOccupied =
at::zeros({numVoxels + 1}, at::TensorOptions().dtype(at::kInt))
at::zeros({numVoxels}, at::TensorOptions().dtype(at::kInt))
.to(vol.device());
auto d_voxelOccupied_ = d_voxelOccupied.index({Slice(1, None)});
// Execute "ClassifyVoxelKernel" kernel to precompute
// two arrays - d_voxelOccupied and d_voxelVertices to global memory,
// which stores the occupancy state and number of voxel vertices per voxel.
ClassifyVoxelKernel<<<grid, threads, 0, stream>>>(
d_voxelVerts_.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
d_voxelOccupied_.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
d_voxelVerts.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
d_voxelOccupied.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
vol.packed_accessor32<float, 3, at::RestrictPtrTraits>(),
isolevel);
AT_CUDA_CHECK(cudaGetLastError());
@@ -467,12 +503,9 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
// count for voxels in the grid and compute the number of active voxels.
// If the number of active voxels is 0, return zero tensor for verts and
// faces.
auto d_voxelOccupiedScan = at::cumsum(d_voxelOccupied, 0);
auto d_voxelOccupiedScan_ = d_voxelOccupiedScan.index({Slice(1, None)});
// number of active voxels
int64_t activeVoxels = d_voxelOccupiedScan[numVoxels].cpu().item<int64_t>();
int64_t activeVoxels = 0;
auto d_voxelOccupiedScan =
ExclusiveScanAndTotal(d_voxelOccupied, &activeVoxels);
const int device_id = vol.device().index();
auto opt = at::TensorOptions().dtype(at::kInt).device(at::kCUDA, device_id);
@@ -487,24 +520,21 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
return std::make_tuple(verts, faces, ids);
}
// Execute "CompactVoxelsKernel" kernel to compress voxels for accleration.
// Execute "CompactVoxelsKernel" kernel to compress voxels for acceleration.
// This allows us to run triangle generation on only the occupied voxels.
auto d_compVoxelArray = at::zeros({activeVoxels}, opt);
CompactVoxelsKernel<<<grid, threads, 0, stream>>>(
d_compVoxelArray.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
d_voxelOccupied.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
d_voxelOccupiedScan_
d_voxelOccupiedScan
.packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
numVoxels);
AT_CUDA_CHECK(cudaGetLastError());
cudaDeviceSynchronize();
// Scan d_voxelVerts array to generate offsets of vertices for each voxel
auto d_voxelVertsScan = at::cumsum(d_voxelVerts, 0);
auto d_voxelVertsScan_ = d_voxelVertsScan.index({Slice(1, None)});
// total number of vertices
int64_t totalVerts = d_voxelVertsScan[numVoxels].cpu().item<int64_t>();
int64_t totalVerts = 0;
auto d_voxelVertsScan = ExclusiveScanAndTotal(d_voxelVerts, &totalVerts);
// Execute "GenerateFacesKernel" kernel
// This runs only on the occupied voxels.
@@ -524,7 +554,7 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
faces.packed_accessor<int64_t, 2, at::RestrictPtrTraits>(),
ids.packed_accessor<int64_t, 1, at::RestrictPtrTraits>(),
d_compVoxelArray.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
d_voxelVertsScan_.packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
d_voxelVertsScan.packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
activeVoxels,
vol.packed_accessor32<float, 3, at::RestrictPtrTraits>(),
faceTable.packed_accessor32<int, 2, at::RestrictPtrTraits>(),

2
pytorch3d/csrc/points_to_volumes/points_to_volumes_cpu.cpp
View File

@@ -8,9 +8,7 @@
#include <torch/csrc/autograd/VariableTypeUtils.h>
#include <torch/extension.h>
#include <algorithm>
#include <cmath>
#include <thread>
#include <vector>
// In the x direction, the location {0, ..., grid_size_x - 1} correspond to

4
pytorch3d/csrc/pulsar/global.h
View File

@@ -36,11 +36,13 @@
#pragma nv_diag_suppress 2951
#pragma nv_diag_suppress 2967
#else
#if !defined(USE_ROCM)
#pragma diag_suppress = attribute_not_allowed
#pragma diag_suppress = 1866
#pragma diag_suppress = 2941
#pragma diag_suppress = 2951
#pragma diag_suppress = 2967
#endif //! USE_ROCM
#endif
#else // __CUDACC__
#define INLINE inline
@@ -56,7 +58,9 @@
#pragma clang diagnostic pop
#ifdef WITH_CUDA
#include <ATen/cuda/CUDAContext.h>
#if !defined(USE_ROCM)
#include <vector_functions.h>
#endif //! USE_ROCM
#else
#ifndef cudaStream_t
typedef void* cudaStream_t;

0
pytorch3d/csrc/pulsar/cuda/README.md → pytorch3d/csrc/pulsar/gpu/README.md
View File

8
pytorch3d/csrc/pulsar/cuda/commands.h → pytorch3d/csrc/pulsar/gpu/commands.h
View File

@@ -59,6 +59,11 @@ getLastCudaError(const char* errorMessage, const char* file, const int line) {
#define SHARED __shared__
#define ACTIVEMASK() __activemask()
#define BALLOT(mask, val) __ballot_sync((mask), val)
/* TODO (ROCM-6.2): None of the WARP_* are used anywhere and ROCM-6.2 natively
* supports __shfl_*. Disabling until the move to ROCM-6.2.
*/
#if !defined(USE_ROCM)
/**
* Find the cumulative sum within a warp up to the current
* thread lane, with each mask thread contributing base.
@@ -115,6 +120,7 @@ INLINE DEVICE float3 WARP_SUM_FLOAT3(
ret.z = WARP_SUM(group, mask, base.z);
return ret;
}
#endif //! USE_ROCM
// Floating point.
// #define FMUL(a, b) __fmul_rn((a), (b))
@@ -142,6 +148,7 @@ INLINE DEVICE float3 WARP_SUM_FLOAT3(
#define FMA(x, y, z) __fmaf_rn((x), (y), (z))
#define I2F(a) __int2float_rn(a)
#define FRCP(x) __frcp_rn(x)
#if !defined(USE_ROCM)
__device__ static float atomicMax(float* address, float val) {
int* address_as_i = (int*)address;
int old = *address_as_i, assumed;
@@ -166,6 +173,7 @@ __device__ static float atomicMin(float* address, float val) {
} while (assumed != old);
return __int_as_float(old);
}
#endif //! USE_ROCM
#define DMAX(a, b) FMAX(a, b)
#define DMIN(a, b) FMIN(a, b)
#define DSQRT(a) sqrt(a)

0
pytorch3d/csrc/pulsar/cuda/renderer.backward.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.backward.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.backward_dbg.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.backward_dbg.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.calc_gradients.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.calc_gradients.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.calc_signature.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.calc_signature.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.construct.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.construct.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.create_selector.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.create_selector.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.destruct.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.destruct.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.fill_bg.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.fill_bg.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.forward.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.forward.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.norm_cam_gradients.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.norm_cam_gradients.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.norm_sphere_gradients.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.norm_sphere_gradients.gpu.cu
View File

0
pytorch3d/csrc/pulsar/cuda/renderer.render.gpu.cu → pytorch3d/csrc/pulsar/gpu/renderer.render.gpu.cu
View File

4
pytorch3d/csrc/pulsar/host/commands.h
View File

@@ -357,11 +357,11 @@ void MAX_WS(
//
//
#define END_PARALLEL() \
end_parallel:; \
end_parallel :; \
}
#define END_PARALLEL_NORET() }
#define END_PARALLEL_2D() \
end_parallel:; \
end_parallel :; \
} \
}
#define END_PARALLEL_2D_NORET() \

2
pytorch3d/csrc/pulsar/include/camera.device.h
View File

@@ -14,7 +14,7 @@
#include "./commands.h"
namespace pulsar {
IHD CamGradInfo::CamGradInfo() {
IHD CamGradInfo::CamGradInfo(int x) {
cam_pos = make_float3(0.f, 0.f, 0.f);
pixel_0_0_center = make_float3(0.f, 0.f, 0.f);
pixel_dir_x = make_float3(0.f, 0.f, 0.f);

2
pytorch3d/csrc/pulsar/include/camera.h
View File

@@ -63,7 +63,7 @@ inline bool operator==(const CamInfo& a, const CamInfo& b) {
};
struct CamGradInfo {
HOST DEVICE CamGradInfo();
HOST DEVICE CamGradInfo(int = 0);
float3 cam_pos;
float3 pixel_0_0_center;
float3 pixel_dir_x;

2
pytorch3d/csrc/pulsar/include/commands.h
View File

@@ -24,7 +24,7 @@
// #pragma diag_suppress = 68
#include <ATen/cuda/CUDAContext.h>
// #pragma pop
#include "../cuda/commands.h"
#include "../gpu/commands.h"
#else
#pragma clang diagnostic push
#pragma clang diagnostic ignored "-Weverything"

2
pytorch3d/csrc/pulsar/include/math.h
View File

@@ -46,6 +46,7 @@ IHD float3 outer_product_sum(const float3& a) {
}
// TODO: put intrinsics here.
#if !defined(USE_ROCM)
IHD float3 operator+(const float3& a, const float3& b) {
return make_float3(a.x + b.x, a.y + b.y, a.z + b.z);
}
@@ -93,6 +94,7 @@ IHD float3 operator*(const float3& a, const float3& b) {
IHD float3 operator*(const float& a, const float3& b) {
return b * a;
}
#endif //! USE_ROCM
INLINE DEVICE float length(const float3& v) {
// TODO: benchmark what's faster.

2
pytorch3d/csrc/pulsar/include/renderer.construct.device.h
View File

@@ -93,7 +93,7 @@ HOST void construct(
MALLOC(self->di_sorted_d, DrawInfo, max_num_balls);
MALLOC(self->region_flags_d, char, max_num_balls);
MALLOC(self->num_selected_d, size_t, 1);
MALLOC(self->forw_info_d, float, width* height*(3 + 2 * n_track));
MALLOC(self->forw_info_d, float, width* height * (3 + 2 * n_track));
MALLOC(self->min_max_pixels_d, IntersectInfo, 1);
MALLOC(self->grad_pos_d, float3, max_num_balls);
MALLOC(self->grad_col_d, float, max_num_balls* n_channels);

10
pytorch3d/csrc/pulsar/include/renderer.render.device.h
View File

@@ -99,7 +99,7 @@ GLOBAL void render(
/** Whether loading of balls is completed. */
SHARED bool loading_done;
/** The number of balls loaded overall (just for statistics). */
SHARED int n_balls_loaded;
[[maybe_unused]] SHARED int n_balls_loaded;
/** The area this thread block covers. */
SHARED IntersectInfo block_area;
if (thread_block.thread_rank() == 0) {
@@ -283,9 +283,15 @@ GLOBAL void render(
(percent_allowed_difference > 0.f &&
max_closest_possible_intersection > depth_threshold) ||
tracker.get_n_hits() >= max_n_hits;
#if defined(__CUDACC__) && defined(__HIP_PLATFORM_AMD__)
unsigned long long warp_done = __ballot(done);
int warp_done_bit_cnt = __popcll(warp_done);
#else
uint warp_done = thread_warp.ballot(done);
int warp_done_bit_cnt = POPC(warp_done);
#endif //__CUDACC__ && __HIP_PLATFORM_AMD__
if (thread_warp.thread_rank() == 0)
ATOMICADD_B(&n_pixels_done, POPC(warp_done));
ATOMICADD_B(&n_pixels_done, warp_done_bit_cnt);
// This sync is necessary to keep n_loaded until all threads are done with
// painting.
thread_block.sync();

46
pytorch3d/csrc/pulsar/pytorch/renderer.cpp
View File

@@ -213,8 +213,8 @@ std::tuple<size_t, size_t, bool, torch::Tensor> Renderer::arg_check(
const float& gamma,
const float& max_depth,
float& min_depth,
const c10::optional<torch::Tensor>& bg_col,
const c10::optional<torch::Tensor>& opacity,
const std::optional<torch::Tensor>& bg_col,
const std::optional<torch::Tensor>& opacity,
const float& percent_allowed_difference,
const uint& max_n_hits,
const uint& mode) {
@@ -668,8 +668,8 @@ std::tuple<torch::Tensor, torch::Tensor> Renderer::forward(
const float& gamma,
const float& max_depth,
float min_depth,
const c10::optional<torch::Tensor>& bg_col,
const c10::optional<torch::Tensor>& opacity,
const std::optional<torch::Tensor>& bg_col,
const std::optional<torch::Tensor>& opacity,
const float& percent_allowed_difference,
const uint& max_n_hits,
const uint& mode) {
@@ -888,14 +888,14 @@ std::tuple<torch::Tensor, torch::Tensor> Renderer::forward(
};
std::tuple<
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>>
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>>
Renderer::backward(
const torch::Tensor& grad_im,
const torch::Tensor& image,
@@ -912,8 +912,8 @@ Renderer::backward(
const float& gamma,
const float& max_depth,
float min_depth,
const c10::optional<torch::Tensor>& bg_col,
const c10::optional<torch::Tensor>& opacity,
const std::optional<torch::Tensor>& bg_col,
const std::optional<torch::Tensor>& opacity,
const float& percent_allowed_difference,
const uint& max_n_hits,
const uint& mode,
@@ -922,7 +922,7 @@ Renderer::backward(
const bool& dif_rad,
const bool& dif_cam,
const bool& dif_opy,
const at::optional<std::pair<uint, uint>>& dbg_pos) {
const std::optional<std::pair<uint, uint>>& dbg_pos) {
this->ensure_on_device(this->device_tracker.device());
size_t batch_size;
size_t n_points;
@@ -1045,14 +1045,14 @@ Renderer::backward(
}
// Prepare the return value.
std::tuple<
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>>
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>>
ret;
if (mode == 1 || (!dif_pos && !dif_col && !dif_rad && !dif_cam && !dif_opy)) {
return ret;

30
pytorch3d/csrc/pulsar/pytorch/renderer.h
View File

@@ -44,21 +44,21 @@ struct Renderer {
const float& gamma,
const float& max_depth,
float min_depth,
const c10::optional<torch::Tensor>& bg_col,
const c10::optional<torch::Tensor>& opacity,
const std::optional<torch::Tensor>& bg_col,
const std::optional<torch::Tensor>& opacity,
const float& percent_allowed_difference,
const uint& max_n_hits,
const uint& mode);
std::tuple<
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>,
at::optional<torch::Tensor>>
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>,
std::optional<torch::Tensor>>
backward(
const torch::Tensor& grad_im,
const torch::Tensor& image,
@@ -75,8 +75,8 @@ struct Renderer {
const float& gamma,
const float& max_depth,
float min_depth,
const c10::optional<torch::Tensor>& bg_col,
const c10::optional<torch::Tensor>& opacity,
const std::optional<torch::Tensor>& bg_col,
const std::optional<torch::Tensor>& opacity,
const float& percent_allowed_difference,
const uint& max_n_hits,
const uint& mode,
@@ -85,7 +85,7 @@ struct Renderer {
const bool& dif_rad,
const bool& dif_cam,
const bool& dif_opy,
const at::optional<std::pair<uint, uint>>& dbg_pos);
const std::optional<std::pair<uint, uint>>& dbg_pos);
// Infrastructure.
/**
@@ -115,8 +115,8 @@ struct Renderer {
const float& gamma,
const float& max_depth,
float& min_depth,
const c10::optional<torch::Tensor>& bg_col,
const c10::optional<torch::Tensor>& opacity,
const std::optional<torch::Tensor>& bg_col,
const std::optional<torch::Tensor>& opacity,
const float& percent_allowed_difference,
const uint& max_n_hits,
const uint& mode);

5
pytorch3d/csrc/pulsar/pytorch/tensor_util.cpp
View File

@@ -8,6 +8,7 @@
#ifdef WITH_CUDA
#include <ATen/cuda/CUDAContext.h>
#include <c10/cuda/CUDAException.h>
#include <cuda_runtime_api.h>
#endif
#include <torch/extension.h>
@@ -33,13 +34,13 @@ torch::Tensor sphere_ids_from_result_info_nograd(
.contiguous();
if (forw_info.device().type() == c10::DeviceType::CUDA) {
#ifdef WITH_CUDA
cudaMemcpyAsync(
C10_CUDA_CHECK(cudaMemcpyAsync(
result.data_ptr(),
tmp.data_ptr(),
sizeof(uint32_t) * tmp.size(0) * tmp.size(1) * tmp.size(2) *
tmp.size(3),
cudaMemcpyDeviceToDevice,
at::cuda::getCurrentCUDAStream());
at::cuda::getCurrentCUDAStream()));
#else
throw std::runtime_error(
"Copy on CUDA device initiated but built "

7
pytorch3d/csrc/pulsar/pytorch/util.cpp
View File

@@ -7,6 +7,7 @@
*/
#ifdef WITH_CUDA
#include <c10/cuda/CUDAException.h>
#include <cuda_runtime_api.h>
namespace pulsar {
@@ -17,7 +18,8 @@ void cudaDevToDev(
const void* src,
const int& size,
const cudaStream_t& stream) {
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToDevice, stream);
C10_CUDA_CHECK(
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToDevice, stream));
}
void cudaDevToHost(
@@ -25,7 +27,8 @@ void cudaDevToHost(
const void* src,
const int& size,
const cudaStream_t& stream) {
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToHost, stream);
C10_CUDA_CHECK(
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToHost, stream));
}
} // namespace pytorch

3
pytorch3d/csrc/rasterize_coarse/rasterize_coarse.cu
View File

@@ -244,8 +244,7 @@ at::Tensor RasterizeCoarseCuda(
if (num_bins_y >= kMaxItemsPerBin || num_bins_x >= kMaxItemsPerBin) {
std::stringstream ss;
ss << "In RasterizeCoarseCuda got num_bins_y: " << num_bins_y
<< ", num_bins_x: " << num_bins_x << ", "
<< "; that's too many!";
<< ", num_bins_x: " << num_bins_x << ", " << "; that's too many!";
AT_ERROR(ss.str());
}
auto opts = elems_per_batch.options().dtype(at::kInt);

2
pytorch3d/csrc/rasterize_meshes/rasterize_meshes.cu
View File

@@ -144,7 +144,7 @@ __device__ void CheckPixelInsideFace(
const bool zero_face_area =
(face_area <= kEpsilon && face_area >= -1.0f * kEpsilon);
if (zmax < 0 || cull_backfaces && back_face || outside_bbox ||
if (zmax < 0 || (cull_backfaces && back_face) || outside_bbox ||
zero_face_area) {
return;
}

1
pytorch3d/csrc/rasterize_meshes/rasterize_meshes_cpu.cpp
View File

@@ -9,7 +9,6 @@
#include <torch/extension.h>
#include <algorithm>
#include <list>
#include <queue>
#include <thread>
#include <tuple>
#include "ATen/core/TensorAccessor.h"

2
pytorch3d/csrc/sample_farthest_points/sample_farthest_points.cu
View File

@@ -35,8 +35,6 @@ __global__ void FarthestPointSamplingKernel(
__shared__ int64_t selected_store;
// Get constants
const int64_t N = points.size(0);
const int64_t P = points.size(1);
const int64_t D = points.size(2);
// Get batch index and thread index

3
pytorch3d/csrc/utils/float_math.cuh
View File

@@ -18,6 +18,8 @@ const auto vEpsilon = 1e-8;
// Common functions and operators for float2.
// Complex arithmetic is already defined for AMD.
#if !defined(USE_ROCM)
__device__ inline float2 operator-(const float2& a, const float2& b) {
return make_float2(a.x - b.x, a.y - b.y);
}
@@ -41,6 +43,7 @@ __device__ inline float2 operator*(const float2& a, const float2& b) {
__device__ inline float2 operator*(const float a, const float2& b) {
return make_float2(a * b.x, a * b.y);
}
#endif
__device__ inline float FloatMin3(const float a, const float b, const float c) {
return fminf(a, fminf(b, c));

2
pytorch3d/csrc/utils/geometry_utils.cuh
View File

@@ -376,8 +376,6 @@ PointLineDistanceBackward(
float tt = t_top / t_bot;
tt = __saturatef(tt);
const float2 p_proj = (1.0f - tt) * v0 + tt * v1;
const float2 d = p - p_proj;
const float dist = sqrt(dot(d, d));
const float2 grad_p = -1.0f * grad_dist * 2.0f * (p_proj - p);
const float2 grad_v0 = grad_dist * (1.0f - tt) * 2.0f * (p_proj - p);

26
pytorch3d/csrc/utils/warp_reduce.cuh
View File

@@ -23,37 +23,51 @@ WarpReduceMin(scalar_t* min_dists, int64_t* min_idxs, const size_t tid) {
min_idxs[tid] = min_idxs[tid + 32];
min_dists[tid] = min_dists[tid + 32];
}
// AMD does not use explicit syncwarp and instead automatically inserts memory
// fences during compilation.
#if !defined(USE_ROCM)
__syncwarp();
#endif
// s = 16
if (min_dists[tid] > min_dists[tid + 16]) {
min_idxs[tid] = min_idxs[tid + 16];
min_dists[tid] = min_dists[tid + 16];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
// s = 8
if (min_dists[tid] > min_dists[tid + 8]) {
min_idxs[tid] = min_idxs[tid + 8];
min_dists[tid] = min_dists[tid + 8];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
// s = 4
if (min_dists[tid] > min_dists[tid + 4]) {
min_idxs[tid] = min_idxs[tid + 4];
min_dists[tid] = min_dists[tid + 4];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
// s = 2
if (min_dists[tid] > min_dists[tid + 2]) {
min_idxs[tid] = min_idxs[tid + 2];
min_dists[tid] = min_dists[tid + 2];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
// s = 1
if (min_dists[tid] > min_dists[tid + 1]) {
min_idxs[tid] = min_idxs[tid + 1];
min_dists[tid] = min_dists[tid + 1];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
}
template <typename scalar_t>
@@ -65,30 +79,42 @@ __device__ void WarpReduceMax(
dists[tid] = dists[tid + 32];
dists_idx[tid] = dists_idx[tid + 32];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
if (dists[tid] < dists[tid + 16]) {
dists[tid] = dists[tid + 16];
dists_idx[tid] = dists_idx[tid + 16];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
if (dists[tid] < dists[tid + 8]) {
dists[tid] = dists[tid + 8];
dists_idx[tid] = dists_idx[tid + 8];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
if (dists[tid] < dists[tid + 4]) {
dists[tid] = dists[tid + 4];
dists_idx[tid] = dists_idx[tid + 4];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
if (dists[tid] < dists[tid + 2]) {
dists[tid] = dists[tid + 2];
dists_idx[tid] = dists_idx[tid + 2];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
if (dists[tid] < dists[tid + 1]) {
dists[tid] = dists[tid + 1];
dists_idx[tid] = dists_idx[tid + 1];
}
#if !defined(USE_ROCM)
__syncwarp();
#endif
}

Some files were not shown because too many files have changed in this diff Show More