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64 Commits
v0.7.5 ... stable

Author SHA1 Message Date
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
Jeremy Reizenstein
f34104cf6e version 0.7.6 
Summary: New version

Reviewed By: cijose

Differential Revision: D53852987

fbshipit-source-id: 962ab9f61153883df9da0601356bd6b108dc5df7
 2024-02-19 03:28:54 -08:00
Jeremy Reizenstein
f247c86dc0 Update tutorials for 0.7.6 
Summary:
version number changed with
`sed -i "s/2.1\./2.2./" *b`

Reviewed By: cijose

Differential Revision: D53852986

fbshipit-source-id: 1662c8e6d671321887a3263bc3880d5c33d1f866
 2024-02-19 03:28:54 -08:00
Cijo Jose
ae9d8787ce Support color in cubify 
Summary: The diff support colors in cubify for align = "center"

Reviewed By: bottler

Differential Revision: D53777011

fbshipit-source-id: ccb2bd1e3d89be3d1ac943eff08f40e50b0540d9
 2024-02-16 08:19:12 -08:00
Jeremy Reizenstein
8772fe0de8 Make OpenGL optional in tests 
Summary: Add an option to run tests without the OpenGL Renderer.

Reviewed By: patricklabatut

Differential Revision: D53573400

fbshipit-source-id: 54a14e7b2f156d24e0c561fdb279f4a9af01b793
 2024-02-13 07:43:42 -08:00
Ada Martin
c292c71c1a c++ marching cubes fix 
Summary:
Fixes https://github.com/facebookresearch/pytorch3d/issues/1641. The bug was caused by the mistaken downcasting of an int64_t into int, causing issues only on inputs large enough to have hashes that escaped the bounds of an int32.

Also added a test case for this issue.

Reviewed By: bottler

Differential Revision: D53505370

fbshipit-source-id: 0fdd0efc6d259cc3b0263e7ff3a4ab2c648ec521
 2024-02-08 11:13:15 -08:00
Jeremy Reizenstein
d0d9cae9cd builds for PyTorch 2.1.1 2.1.2 2.2.0 
Summary: Build for new pytorch versions

Reviewed By: shapovalov

Differential Revision: D53266104

fbshipit-source-id: f7aaacaf39cab3839b24f45361c36f087d0ea7c9
 2024-02-07 11:56:52 -08:00
generatedunixname89002005287564
1f92c4e9d2 vision/fair 
Reviewed By: zsol

Differential Revision: D53258682

fbshipit-source-id: 3f006b5f31a2b1ffdc6323d3a3b08ac46c3162ce
 2024-01-31 07:43:49 -08:00
generatedunixname89002005307016
9b981f2c7e suppress errors in vision/fair/pytorch3d 
Differential Revision: D53152021

fbshipit-source-id: 78be99b00abe4d992db844ff5877a89d42d468af
 2024-01-26 19:10:37 -08:00
generatedunixname89002005307016
85eccbbf77 suppress errors in vision/fair/pytorch3d 
Differential Revision: D53111480

fbshipit-source-id: 0f506bf29cf908e40b058ae72f51e828cd597825
 2024-01-25 21:13:30 -08:00
generatedunixname89002005307016
b80ab0caf0 upgrade pyre version in fbcode/vision - batch 1 
Differential Revision: D53059851

fbshipit-source-id: f5d0951186c858f90ddf550323a163e4b6d42b68
 2024-01-24 23:56:06 -08:00
Dimitris Prountzos
1e817914b3 Fix compiler warning in knn.ku 
Summary: This change updates the type of p2_idx from size_t to int64_t to address compiler warnings related to signed/unsigned comparison.

Reviewed By: bottler

Differential Revision: D52879393

fbshipit-source-id: de5484d78a907fccdaae3ce036b5e4a1a0a4de70
 2024-01-18 12:27:16 -08:00
Ido Zachevsky
799c1cd21b Allow get_rgbd_point_cloud to take any #channels 
Summary: Fixed `get_rgbd_point_cloud` to take any number of image input channels.

Reviewed By: bottler

Differential Revision: D52796276

fbshipit-source-id: 3ddc0d1e337a6cc53fc86c40a6ddb136f036f9bc
 2024-01-16 03:38:26 -08:00
Abdelrahman Selim
292acc71a3 Update so3 operations for numerical stability 
Summary: Replace implementations of `so3_exp_map` and `so3_log_map` in so3.py with existing more-stable implementations.

Reviewed By: bottler

Differential Revision: D52513319

fbshipit-source-id: fbfc039643fef284d8baa11bab61651964077afe
 2024-01-04 02:26:56 -08:00
Jeremy Reizenstein
3621a36494 mac build fix 
Summary: Fix for https://github.com/facebookresearch/pytorch3d/issues/1708

Reviewed By: patricklabatut

Differential Revision: D52480756

fbshipit-source-id: 530c0f9413970fba042eec354e28318c96e35f42
 2024-01-03 07:46:54 -08:00
Abdelrahman Selim
3087ab7f62 Standardize matrix_to_quaternion output 
Summary:
An OSS user has pointed out in https://github.com/facebookresearch/pytorch3d/issues/1703 that the output of matrix_to_quaternion (in that file) can be non standardized.

This diff solves the issue by adding a line of standardize at the end of the function

Reviewed By: bottler

Differential Revision: D52368721

fbshipit-source-id: c8d0426307fcdb7fd165e032572382d5ae360cde
 2023-12-21 13:43:29 -08:00
Tony Tan
e46ab49a34 Submeshing TexturesAtlas for PyTorch3D 3D Rendering 
Summary: Implement submeshing for TexturesAtlas and add associated test

Reviewed By: bottler

Differential Revision: D52334053

fbshipit-source-id: d54080e9af1f0c01551702736e858e3bd439ac58
 2023-12-21 11:08:01 -08:00
Hassan Lotfi
8a27590c5f Submeshing TexturesUV 
Summary: Implement `submeshes` for TexturesUV. Fix what Meshes.submeshes passes to the texture's submeshes function to make this possible.

Reviewed By: bottler

Differential Revision: D52192060

fbshipit-source-id: 526734962e3376aaf75654200164cdcebfff6997
 2023-12-19 06:48:06 -08:00
Eric Young
06cdc313a7 PyTorch3D - Avoid flip in TexturesAtlas 
Summary: Performance improvement: Use torch.lerp to map uv coordinates to the range needed for grid_sample (i.e. map [0, 1] to [-1, 1] and invert the y-axis)

Reviewed By: bottler

Differential Revision: D51961728

fbshipit-source-id: db19a5e3f482e9af7b96b20f88a1e5d0076dac43
 2023-12-11 12:49:17 -08:00
Roman Shapovalov
94da8841af Align_corners switch in Volumes 
Summary:
Porting this commit by davnov134 .
93a3a62800 (diff-a8e107ebe039de52ca112ac6ddfba6ebccd53b4f53030b986e13f019fe57a378)

Capability to interpret world/local coordinates with various align_corners semantics.

Reviewed By: bottler

Differential Revision: D51855420

fbshipit-source-id: 834cd220c25d7f0143d8a55ba880da5977099dd6
 2023-12-07 03:07:41 -08:00
generatedunixname89002005307016
fbc6725f03 upgrade pyre version in fbcode/vision - batch 2 
Differential Revision: D51902460

fbshipit-source-id: 3ffc5d7d2da5c5d4e971ee8275bd999c709e0b12
 2023-12-06 20:53:53 -08:00
Jeremy Reizenstein
6b8766080d Use cuda's make_float3 in pulsar 
Summary: Fixes github.com/facebookresearch/pytorch3d/issues/1680

Reviewed By: MichaelRamamonjisoa

Differential Revision: D51587889

fbshipit-source-id: e68ae32d7041fb9ea3e981cf2bde47f947a41ca2
 2023-12-05 03:15:02 -08:00
sewon.jeon
c373a84400 Use updated naming to remove warning (#1687) 
Summary:
diag_suppress is  deprecated from cuda

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1687

Reviewed By: MichaelRamamonjisoa

Differential Revision: D51495875

Pulled By: bottler

fbshipit-source-id: 6543a15e666238365719117bfcf5f7dac532aec1
 2023-12-05 03:15:02 -08:00
sewon.jeon
7606854ff7 Fix windows build (#1689) 
Summary:
Change the data type usage in the code to ensure cross-platform compatibility
long -> int64_t

<img width="628" alt="image" src="https://github.com/facebookresearch/pytorch3d/assets/6214316/40041f7f-3c09-4571-b9ff-676c625802e9">

Tested under
Win 11 and Ubuntu 22.04
with
CUDA 12.1.1 torch 2.1.1

Related issues & PR

https://github.com/facebookresearch/pytorch3d/pull/9

https://github.com/facebookresearch/pytorch3d/issues/1679

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1689

Reviewed By: MichaelRamamonjisoa

Differential Revision: D51521562

Pulled By: bottler

fbshipit-source-id: d8ea81e223c642e0e9fb283f5d7efc9d6ac00d93
 2023-12-05 03:14:06 -08:00
Jeremy Reizenstein
83bacda8fb lint 
Summary: Fix recent flake complaints

Reviewed By: MichaelRamamonjisoa

Differential Revision: D51811912

fbshipit-source-id: 65183f5bc7058da910e4d5a63b2250ce8637f1cc
 2023-12-04 13:43:34 -08:00
generatedunixname89002005307016
f74fc450e8 suppress errors in vision/fair/pytorch3d 
Differential Revision: D51645956

fbshipit-source-id: 1ae7279efa0a27bb9bc5255527bafebb84fdafd0
 2023-11-28 19:10:06 -08:00
Dan Johnson
3b4f8a4980 Adding reference and context to PointsRenderer 
Summary: User confusion (https://github.com/facebookresearch/pytorch3d/issues/1579) about how zbuf is used for alpha compositing. Added small description and reference to paper to help give some context.

Reviewed By: bottler

Differential Revision: D51374933

fbshipit-source-id: 8c489a5b5d0a81f0d936c1348b9ade6787c39c9a
 2023-11-16 08:58:08 -08:00
Aleksandrs Ecins
79b46734cb Fix lint in test_render_points 
Summary: Fixes lint in test_render_points in the PyTorch3D library.

Differential Revision: D51289841

fbshipit-source-id: 1eae621eb8e87b0fe5979f35acd878944f574a6a
 2023-11-14 11:07:28 -08:00
YangHai
55638f3bae Support reading uv and uv map for ply format if texture_uv exists in ply file (#1100) 
Summary:
When the ply format looks as follows:
  ```
comment TextureFile ***.png
element vertex 892
property double x
property double y
property double z
property double nx
property double ny
property double nz
property double texture_u
property double texture_v
```
`MeshPlyFormat` class will read uv from the ply file and read the uv map as commented as TextureFile.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1100

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50885176

Pulled By: bottler

fbshipit-source-id: be75b1ec9a17a1ed87dbcf846a9072ea967aec37
 2023-11-14 07:44:14 -08:00
Jeremy Reizenstein
f4f2209271 Fix for mask_points=False 
Summary: Remove unused argument `mask_points` from `get_rgbd_point_cloud` and fix `get_implicitron_sequence_pointcloud`, which assumed it was used.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50885848

fbshipit-source-id: c0b834764ad5ef560107bd8eab04952d000489b8
 2023-11-14 07:42:18 -08:00
Jeremy Reizenstein
f613682551 marching_cubes type fix 
Summary: fixes https://github.com/facebookresearch/pytorch3d/issues/1679

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50949933

fbshipit-source-id: 5c467de8bf84dd2a3d61748b3846678582d24ea3
 2023-11-14 07:38:54 -08:00
274 changed files with 2842 additions and 901 deletions
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658
.circleci/config.yml
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@@ -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
@@ -261,89 +177,103 @@ workflows:
python_version: '3.8'
pytorch_version: 2.1.0
- 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_pyt211
python_version: '3.8'
pytorch_version: 2.1.1
- 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
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- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda117
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cu_version: cu117
name: linux_conda_py39_cu117_pyt1131
python_version: '3.9'
pytorch_version: 1.13.1
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context: DOCKERHUB_TOKEN
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name: linux_conda_py39_cu117_pyt200
python_version: '3.9'
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name: linux_conda_py38_cu121_pyt211
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context: DOCKERHUB_TOKEN
cu_version: cu118
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conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu117
name: linux_conda_py39_cu117_pyt201
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context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py39_cu118_pyt201
python_version: '3.9'
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python_version: '3.8'
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- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py38_cu121_pyt220
python_version: '3.8'
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- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py38_cu118_pyt222
python_version: '3.8'
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python_version: '3.8'
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name: linux_conda_py38_cu118_pyt231
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context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py38_cu118_pyt240
python_version: '3.8'
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conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py38_cu121_pyt240
python_version: '3.8'
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- 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'
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- binary_linux_conda:
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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
@@ -359,89 +289,103 @@ workflows:
python_version: '3.9'
pytorch_version: 2.1.0
- 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_pyt211
python_version: '3.9'
pytorch_version: 2.1.1
- 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
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context: DOCKERHUB_TOKEN
cu_version: cu116
name: linux_conda_py310_cu116_pyt1130
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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_py39_cu118_pyt231
python_version: '3.9'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
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_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
@@ -456,6 +400,104 @@ workflows:
name: linux_conda_py310_cu121_pyt210
python_version: '3.10'
pytorch_version: 2.1.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt211
python_version: '3.10'
pytorch_version: 2.1.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py310_cu121_pyt211
python_version: '3.10'
pytorch_version: 2.1.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt212
python_version: '3.10'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py310_cu121_pyt212
python_version: '3.10'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py310_cu118_pyt220
python_version: '3.10'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
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
@@ -470,6 +512,174 @@ workflows:
name: linux_conda_py311_cu121_pyt210
python_version: '3.11'
pytorch_version: 2.1.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py311_cu118_pyt211
python_version: '3.11'
pytorch_version: 2.1.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py311_cu121_pyt211
python_version: '3.11'
pytorch_version: 2.1.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py311_cu118_pyt212
python_version: '3.11'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py311_cu121_pyt212
python_version: '3.11'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py311_cu118_pyt220
python_version: '3.11'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
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
cu_version: cu118
name: linux_conda_py312_cu118_pyt220
python_version: '3.12'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
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

23
.circleci/regenerate.py
View File

@@ -19,19 +19,18 @@ 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"],
}
def conda_docker_image_for_cuda(cuda_version):
if cuda_version in ("cu101", "cu102", "cu111"):
return None
if len(cuda_version) != 5:
raise ValueError("Unknown cuda version")
return "pytorch/conda-builder:cuda" + cuda_version[2:]
@@ -52,12 +51,18 @@ def pytorch_versions_for_python(python_version):
for i in CONDA_CUDA_VERSIONS
if version.Version(i) >= version.Version("2.1.0")
]
if python_version == "3.12":
return [
i
for i in CONDA_CUDA_VERSIONS
if version.Version(i) >= version.Version("2.2.0")
]
def workflows(prefix="", filter_branch=None, upload=False, indentation=6):
w = []
for btype in ["conda"]:
for python_version in ["3.8", "3.9", "3.10", "3.11"]:
for python_version in ["3.8", "3.9", "3.10", "3.11", "3.12"]:
for pytorch_version in pytorch_versions_for_python(python_version):
for cu_version in CONDA_CUDA_VERSIONS[pytorch_version]:
w += workflow_pair(

5
.flake8
View File

@@ -1,5 +1,8 @@
[flake8]
ignore = E203, E266, E501, W503, E221
# B028 No explicit stacklevel argument found.
# B907 'foo' is manually surrounded by quotes, consider using the `!r` conversion flag.
# B905 `zip()` without an explicit `strict=` parameter.
ignore = E203, E266, E501, W503, E221, B028, B905, B907
max-line-length = 88
max-complexity = 18
select = B,C,E,F,W,T4,B9

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 or 2.1.0.
- 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
```

6
README.md
View File

@@ -146,6 +146,12 @@ If you are using the pulsar backend for sphere-rendering (the `PulsarPointRender
Please see below for a timeline of the codebase updates in reverse chronological order. We are sharing updates on the releases as well as research projects which are built with PyTorch3D. The changelogs for the releases are available under [`Releases`](https://github.com/facebookresearch/pytorch3d/releases), and the builds can be installed using `conda` as per the instructions in [INSTALL.md](INSTALL.md).
**[Oct 31st 2023]:** PyTorch3D [v0.7.5](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.7.5) released.
**[May 10th 2023]:** PyTorch3D [v0.7.4](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.7.4) released.
**[Apr 5th 2023]:** PyTorch3D [v0.7.3](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.7.3) released.
**[Dec 19th 2022]:** PyTorch3D [v0.7.2](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.7.2) released.
**[Oct 23rd 2022]:** PyTorch3D [v0.7.1](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.7.1) released.

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/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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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(\"2.1.\") 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'"
]
},
{

8
packaging/build_conda.py
View File

@@ -80,6 +80,12 @@ def setup_cuda():
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(".", "")
@@ -117,7 +123,7 @@ def do_build(start_args: List[str]):
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")

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

4
packaging/pytorch3d/meta.yaml
View File

@@ -12,8 +12,9 @@ requirements:
host:
- python
- setuptools
{{ 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 +22,6 @@ requirements:
- python
- numpy >=1.11
- torchvision >=0.5
- fvcore
- iopath
{{ environ.get('CONDA_PYTORCH_CONSTRAINT') }}
{{ environ.get('CONDA_CUDATOOLKIT_CONSTRAINT') }}

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

8
projects/implicitron_trainer/experiment.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
""""
This file is the entry point for launching experiments with Implicitron.
@@ -97,7 +99,7 @@ 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 +120,16 @@ 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

5
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
@@ -43,7 +45,7 @@ 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 +61,7 @@ class ImplicitronModelFactory(ModelFactoryBase): # pyre-ignore [13]
"""
# pyre-fixme[13]: Attribute `model` is never initialized.
model: ImplicitronModelBase
model_class_type: str = "GenericModel"
resume: bool = True

3
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
@@ -121,7 +123,6 @@ class ImplicitronOptimizerFactory(OptimizerFactoryBase):
"""
# Get the parameters to optimize
if hasattr(model, "_get_param_groups"): # use the model function
# pyre-ignore[29]
p_groups = model._get_param_groups(self.lr, wd=self.weight_decay)
else:
p_groups = [

7
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"
@@ -110,6 +112,8 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
def __post_init__(self):
run_auto_creation(self)
# pyre-fixme[14]: `run` overrides method defined in `TrainingLoopBase`
# inconsistently.
def run(
self,
*,
@@ -391,7 +395,6 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
):
prefix = f"e{stats.epoch}_it{stats.it[trainmode]}"
if hasattr(model, "visualize"):
# pyre-ignore [29]
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

2
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

2
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

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:

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:

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__ = "0.7.5"
# 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

2
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

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

7
pytorch3d/csrc/ext.cpp
View File

@@ -7,11 +7,15 @@
*/
// clang-format off
#if !defined(USE_ROCM)
#include "./pulsar/global.h" // Include before <torch/extension.h>.
#endif
#include <torch/extension.h>
// clang-format on
#if !defined(USE_ROCM)
#include "./pulsar/pytorch/renderer.h"
#include "./pulsar/pytorch/tensor_util.h"
#endif
#include "ball_query/ball_query.h"
#include "blending/sigmoid_alpha_blend.h"
#include "compositing/alpha_composite.h"
@@ -99,6 +103,8 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("marching_cubes", &MarchingCubes);
// Pulsar.
// Pulsar not enabled on AMD.
#if !defined(USE_ROCM)
#ifdef PULSAR_LOGGING_ENABLED
c10::ShowLogInfoToStderr();
#endif
@@ -183,4 +189,5 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.attr("MAX_UINT") = py::int_(MAX_UINT);
m.attr("MAX_USHORT") = py::int_(MAX_USHORT);
m.attr("PULSAR_MAX_GRAD_SPHERES") = py::int_(MAX_GRAD_SPHERES);
#endif
}

4
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());
@@ -495,7 +495,7 @@ __global__ void KNearestNeighborBackwardKernel(
if ((p1_idx < num1) && (k < num2)) {
const float grad_dist = grad_dists[n * P1 * K + p1_idx * K + k];
// index of point in p2 corresponding to the k-th nearest neighbor
const size_t p2_idx = idxs[n * P1 * K + p1_idx * K + k];
const int64_t p2_idx = idxs[n * P1 * K + p1_idx * K + k];
// If the index is the pad value of -1 then ignore it
if (p2_idx == -1) {
continue;

76
pytorch3d/csrc/marching_cubes/marching_cubes.cu
View File

@@ -223,7 +223,7 @@ __global__ void CompactVoxelsKernel(
compactedVoxelArray,
const at::PackedTensorAccessor32<int, 1, at::RestrictPtrTraits>
voxelOccupied,
const at::PackedTensorAccessor32<int, 1, at::RestrictPtrTraits>
const at::PackedTensorAccessor32<int64_t, 1, at::RestrictPtrTraits>
voxelOccupiedScan,
uint numVoxels) {
uint id = blockIdx.x * blockDim.x + threadIdx.x;
@@ -255,7 +255,8 @@ __global__ void GenerateFacesKernel(
at::PackedTensorAccessor<int64_t, 1, at::RestrictPtrTraits> ids,
at::PackedTensorAccessor32<int, 1, at::RestrictPtrTraits>
compactedVoxelArray,
at::PackedTensorAccessor32<int, 1, at::RestrictPtrTraits> numVertsScanned,
at::PackedTensorAccessor32<int64_t, 1, at::RestrictPtrTraits>
numVertsScanned,
const uint activeVoxels,
const at::PackedTensorAccessor32<float, 3, at::RestrictPtrTraits> vol,
const at::PackedTensorAccessor32<int, 2, at::RestrictPtrTraits> faceTable,
@@ -381,6 +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
@@ -443,20 +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());
@@ -466,12 +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
int activeVoxels = d_voxelOccupiedScan[numVoxels].cpu().item<int>();
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);
@@ -486,23 +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_.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
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
int totalVerts = d_voxelVertsScan[numVoxels].cpu().item<int>();
int64_t totalVerts = 0;
auto d_voxelVertsScan = ExclusiveScanAndTotal(d_voxelVerts, &totalVerts);
// Execute "GenerateFacesKernel" kernel
// This runs only on the occupied voxels.
@@ -522,7 +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<int, 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>(),

4
pytorch3d/csrc/marching_cubes/marching_cubes_cpu.cpp
View File

@@ -71,8 +71,8 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCpu(
if ((j + 1) % 3 == 0 && ps[0] != ps[1] && ps[1] != ps[2] &&
ps[2] != ps[0]) {
for (int k = 0; k < 3; k++) {
int v = tri[k];
edge_id_to_v[tri.at(k)] = ps.at(k);
int64_t v = tri.at(k);
edge_id_to_v[v] = ps.at(k);
if (!uniq_edge_id.count(v)) {
uniq_edge_id[v] = verts.size();
verts.push_back(edge_id_to_v[v]);

12
pytorch3d/csrc/pulsar/global.h
View File

@@ -30,11 +30,18 @@
#define GLOBAL __global__
#define RESTRICT __restrict__
#define DEBUGBREAK()
#ifdef __NVCC_DIAG_PRAGMA_SUPPORT__
#pragma nv_diag_suppress 1866
#pragma nv_diag_suppress 2941
#pragma nv_diag_suppress 2951
#pragma nv_diag_suppress 2967
#else
#pragma diag_suppress = attribute_not_allowed
#pragma diag_suppress = 1866
#pragma diag_suppress = 2941
#pragma diag_suppress = 2951
#pragma diag_suppress = 2967
#endif
#else // __CUDACC__
#define INLINE inline
#define HOST
@@ -49,6 +56,7 @@
#pragma clang diagnostic pop
#ifdef WITH_CUDA
#include <ATen/cuda/CUDAContext.h>
#include <vector_functions.h>
#else
#ifndef cudaStream_t
typedef void* cudaStream_t;
@@ -65,8 +73,6 @@ struct float2 {
struct float3 {
float x, y, z;
};
#endif
namespace py = pybind11;
inline float3 make_float3(const float& x, const float& y, const float& z) {
float3 res;
res.x = x;
@@ -74,6 +80,8 @@ inline float3 make_float3(const float& x, const float& y, const float& z) {
res.z = z;
return res;
}
#endif
namespace py = pybind11;
inline bool operator==(const float3& a, const float3& b) {
return a.x == b.x && a.y == b.y && a.z == b.z;

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/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);

2
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) {

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;
}

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));

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
}

2
pytorch3d/datasets/__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 .r2n2 import BlenderCamera, collate_batched_R2N2, R2N2, render_cubified_voxels
from .shapenet import ShapeNetCore
from .utils import collate_batched_meshes

2
pytorch3d/datasets/r2n2/__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 .r2n2 import R2N2
from .utils import BlenderCamera, collate_batched_R2N2, render_cubified_voxels

2
pytorch3d/datasets/r2n2/r2n2.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 json
import warnings
from os import path

2
pytorch3d/datasets/r2n2/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 math
from typing import Dict, List

2
pytorch3d/datasets/shapenet/__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 .shapenet_core import ShapeNetCore

2
pytorch3d/datasets/shapenet/shapenet_core.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 json
import os
import warnings

2
pytorch3d/datasets/shapenet_base.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 warnings
from typing import Dict, List, Optional, Tuple

2
pytorch3d/datasets/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
from typing import Dict, List
from pytorch3d.renderer.mesh import TexturesAtlas

2
pytorch3d/implicitron/__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

2
pytorch3d/implicitron/dataset/__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

2
pytorch3d/implicitron/dataset/blender_dataset_map_provider.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
from pytorch3d.implicitron.tools.config import registry

2
pytorch3d/implicitron/dataset/data_loader_map_provider.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 dataclasses import dataclass
from enum import Enum
from typing import Iterator, List, Optional, Tuple

7
pytorch3d/implicitron/dataset/data_source.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, Tuple
from pytorch3d.implicitron.tools.config import (
@@ -39,7 +41,7 @@ class DataSourceBase(ReplaceableBase):
@registry.register
class ImplicitronDataSource(DataSourceBase): # pyre-ignore[13]
class ImplicitronDataSource(DataSourceBase):
"""
Represents the data used in Implicitron. This is the only implementation
of DataSourceBase provided.
@@ -50,8 +52,11 @@ class ImplicitronDataSource(DataSourceBase): # pyre-ignore[13]
data_loader_map_provider_class_type: identifies type for data_loader_map_provider.
"""
# pyre-fixme[13]: Attribute `dataset_map_provider` is never initialized.
dataset_map_provider: DatasetMapProviderBase
# pyre-fixme[13]: Attribute `dataset_map_provider_class_type` is never initialized.
dataset_map_provider_class_type: str
# pyre-fixme[13]: Attribute `data_loader_map_provider` is never initialized.
data_loader_map_provider: DataLoaderMapProviderBase
data_loader_map_provider_class_type: str = "SequenceDataLoaderMapProvider"

2
pytorch3d/implicitron/dataset/dataset_base.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 collections import defaultdict
from dataclasses import dataclass
from typing import (

2
pytorch3d/implicitron/dataset/dataset_map_provider.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 dataclasses import dataclass

15
pytorch3d/implicitron/dataset/frame_data.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
from abc import ABC, abstractmethod
from collections import defaultdict
@@ -274,6 +276,7 @@ class FrameData(Mapping[str, Any]):
image_size_hw=tuple(self.effective_image_size_hw), # pyre-ignore
)
crop_bbox_xywh = bbox_xyxy_to_xywh(clamp_bbox_xyxy)
self.crop_bbox_xywh = crop_bbox_xywh
if self.fg_probability is not None:
self.fg_probability = crop_around_box(
@@ -432,7 +435,7 @@ class FrameData(Mapping[str, Any]):
# TODO: don't store K; enforce working in NDC space
return join_cameras_as_batch(batch)
else:
return torch.utils.data._utils.collate.default_collate(batch)
return torch.utils.data.dataloader.default_collate(batch)
FrameDataSubtype = TypeVar("FrameDataSubtype", bound=FrameData)
@@ -576,11 +579,11 @@ class GenericFrameDataBuilder(FrameDataBuilderBase[FrameDataSubtype], ABC):
camera_quality_score=safe_as_tensor(
sequence_annotation.viewpoint_quality_score, torch.float
),
point_cloud_quality_score=safe_as_tensor(
point_cloud.quality_score, torch.float
)
if point_cloud is not None
else None,
point_cloud_quality_score=(
safe_as_tensor(point_cloud.quality_score, torch.float)
if point_cloud is not None
else None
),
)
fg_mask_np: Optional[np.ndarray] = None

8
pytorch3d/implicitron/dataset/json_index_dataset.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 copy
import functools
import gzip
@@ -124,9 +126,9 @@ class JsonIndexDataset(DatasetBase, ReplaceableBase):
dimension of the cropping bounding box, relative to box size.
"""
frame_annotations_type: ClassVar[
Type[types.FrameAnnotation]
] = types.FrameAnnotation
frame_annotations_type: ClassVar[Type[types.FrameAnnotation]] = (
types.FrameAnnotation
)
path_manager: Any = None
frame_annotations_file: str = ""

7
pytorch3d/implicitron/dataset/json_index_dataset_map_provider.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 json
import os
@@ -64,7 +66,7 @@ _NEED_CONTROL: Tuple[str, ...] = (
@registry.register
class JsonIndexDatasetMapProvider(DatasetMapProviderBase): # pyre-ignore [13]
class JsonIndexDatasetMapProvider(DatasetMapProviderBase):
"""
Generates the training / validation and testing dataset objects for
a dataset laid out on disk like Co3D, with annotations in json files.
@@ -93,6 +95,7 @@ class JsonIndexDatasetMapProvider(DatasetMapProviderBase): # pyre-ignore [13]
path_manager_factory_class_type: The class type of `path_manager_factory`.
"""
# pyre-fixme[13]: Attribute `category` is never initialized.
category: str
task_str: str = "singlesequence"
dataset_root: str = _CO3D_DATASET_ROOT
@@ -102,8 +105,10 @@ class JsonIndexDatasetMapProvider(DatasetMapProviderBase): # pyre-ignore [13]
test_restrict_sequence_id: int = -1
assert_single_seq: bool = False
only_test_set: bool = False
# pyre-fixme[13]: Attribute `dataset` is never initialized.
dataset: JsonIndexDataset
dataset_class_type: str = "JsonIndexDataset"
# pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
path_manager_factory: PathManagerFactory
path_manager_factory_class_type: str = "PathManagerFactory"

8
pytorch3d/implicitron/dataset/json_index_dataset_map_provider_v2.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 copy
import json
@@ -54,7 +56,7 @@ logger = logging.getLogger(__name__)
@registry.register
class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase): # pyre-ignore [13]
class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase):
"""
Generates the training, validation, and testing dataset objects for
a dataset laid out on disk like CO3Dv2, with annotations in gzipped json files.
@@ -169,7 +171,9 @@ class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase): # pyre-ignore [13]
path_manager_factory_class_type: The class type of `path_manager_factory`.
"""
# pyre-fixme[13]: Attribute `category` is never initialized.
category: str
# pyre-fixme[13]: Attribute `subset_name` is never initialized.
subset_name: str
dataset_root: str = _CO3DV2_DATASET_ROOT
@@ -181,8 +185,10 @@ class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase): # pyre-ignore [13]
n_known_frames_for_test: int = 0
dataset_class_type: str = "JsonIndexDataset"
# pyre-fixme[13]: Attribute `dataset` is never initialized.
dataset: JsonIndexDataset
# pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
path_manager_factory: PathManagerFactory
path_manager_factory_class_type: str = "PathManagerFactory"

2
pytorch3d/implicitron/dataset/llff_dataset_map_provider.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 numpy as np
import torch

2
pytorch3d/implicitron/dataset/load_blender.py
View File

@@ -1,6 +1,8 @@
# @lint-ignore-every LICENSELINT
# Adapted from https://github.com/bmild/nerf/blob/master/load_blender.py
# Copyright (c) 2020 bmild
# pyre-unsafe
import json
import os

8
pytorch3d/implicitron/dataset/load_llff.py
View File

@@ -1,6 +1,8 @@
# @lint-ignore-every LICENSELINT
# Adapted from https://github.com/bmild/nerf/blob/master/load_llff.py
# Copyright (c) 2020 bmild
# pyre-unsafe
import logging
import os
import warnings
@@ -34,11 +36,7 @@ def _minify(basedir, path_manager, factors=(), resolutions=()):
imgdir = os.path.join(basedir, "images")
imgs = [os.path.join(imgdir, f) for f in sorted(_ls(path_manager, imgdir))]
imgs = [
f
for f in imgs
if any([f.endswith(ex) for ex in ["JPG", "jpg", "png", "jpeg", "PNG"]])
]
imgs = [f for f in imgs if f.endswith("JPG", "jpg", "png", "jpeg", "PNG")]
imgdir_orig = imgdir
wd = os.getcwd()

5
pytorch3d/implicitron/dataset/rendered_mesh_dataset_map_provider.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 os.path import dirname, join, realpath
from typing import Optional, Tuple
@@ -30,7 +32,7 @@ from .utils import DATASET_TYPE_KNOWN
@registry.register
class RenderedMeshDatasetMapProvider(DatasetMapProviderBase): # pyre-ignore [13]
class RenderedMeshDatasetMapProvider(DatasetMapProviderBase):
"""
A simple single-scene dataset based on PyTorch3D renders of a mesh.
Provides `num_views` renders of the mesh as train, with no val
@@ -74,6 +76,7 @@ class RenderedMeshDatasetMapProvider(DatasetMapProviderBase): # pyre-ignore [13
resolution: int = 128
use_point_light: bool = True
gpu_idx: Optional[int] = 0
# pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
path_manager_factory: PathManagerFactory
path_manager_factory_class_type: str = "PathManagerFactory"

2
pytorch3d/implicitron/dataset/scene_batch_sampler.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 warnings
from collections import Counter

6
pytorch3d/implicitron/dataset/single_sequence_dataset.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
# This file defines a base class for dataset map providers which
# provide data for a single scene.
@@ -81,7 +83,6 @@ class SingleSceneDataset(DatasetBase, Configurable):
return self.eval_batches
# pyre-fixme[13]: Uninitialized attribute
class SingleSceneDatasetMapProviderBase(DatasetMapProviderBase):
"""
Base for provider of data for one scene from LLFF or blender datasets.
@@ -98,8 +99,11 @@ class SingleSceneDatasetMapProviderBase(DatasetMapProviderBase):
testing frame.
"""
# pyre-fixme[13]: Attribute `base_dir` is never initialized.
base_dir: str
# pyre-fixme[13]: Attribute `object_name` is never initialized.
object_name: str
# pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
path_manager_factory: PathManagerFactory
path_manager_factory_class_type: str = "PathManagerFactory"
n_known_frames_for_test: Optional[int] = None

2
pytorch3d/implicitron/dataset/train_eval_data_loader_provider.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
from typing import Any, Dict, Optional, Tuple

2
pytorch3d/implicitron/dataset/types.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 dataclasses
import gzip

7
pytorch3d/implicitron/dataset/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 functools
import warnings
@@ -200,7 +202,7 @@ def resize_image(
mode: str = "bilinear",
) -> Tuple[torch.Tensor, float, torch.Tensor]:
if type(image) == np.ndarray:
if isinstance(image, np.ndarray):
image = torch.from_numpy(image)
if image_height is None or image_width is None:
@@ -346,6 +348,7 @@ def adjust_camera_to_image_scale_(
camera: PerspectiveCameras,
original_size_wh: torch.Tensor,
new_size_wh: torch.LongTensor,
# pyre-fixme[7]: Expected `PerspectiveCameras` but got implicit return value of `None`.
) -> PerspectiveCameras:
focal_length_px, principal_point_px = _convert_ndc_to_pixels(
camera.focal_length[0],
@@ -365,7 +368,7 @@ def adjust_camera_to_image_scale_(
image_size_wh_output,
)
camera.focal_length = focal_length_scaled[None]
camera.principal_point = principal_point_scaled[None] # pyre-ignore
camera.principal_point = principal_point_scaled[None]
# NOTE this cache is per-worker; they are implemented as processes.

11
pytorch3d/implicitron/dataset/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
from typing import cast, Optional, Tuple
import torch
@@ -88,10 +90,11 @@ def get_implicitron_sequence_pointcloud(
frame_data.camera,
frame_data.image_rgb,
frame_data.depth_map,
(cast(torch.Tensor, frame_data.fg_probability) > 0.5).float()
if frame_data.fg_probability is not None
else None,
mask_points=mask_points,
(
(cast(torch.Tensor, frame_data.fg_probability) > 0.5).float()
if mask_points and frame_data.fg_probability is not None
else None
),
)
return point_cloud, frame_data

2
pytorch3d/implicitron/eval_demo.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 dataclasses
import os

2
pytorch3d/implicitron/evaluation/__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

8
pytorch3d/implicitron/evaluation/evaluate_new_view_synthesis.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 copy
import warnings
@@ -282,9 +284,9 @@ def eval_batch(
image_rgb_masked=image_rgb_masked,
depth_render=cloned_render["depth_render"],
depth_map=frame_data.depth_map,
depth_mask=frame_data.depth_mask[:1]
if frame_data.depth_mask is not None
else None,
depth_mask=(
frame_data.depth_mask[:1] if frame_data.depth_mask is not None else None
),
visdom_env=visualize_visdom_env,
)

2
pytorch3d/implicitron/evaluation/evaluator.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 copy
import json
import logging

2
pytorch3d/implicitron/models/__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
# Allows to register the models
# see: pytorch3d.implicitron.tools.config.registry:register
from pytorch3d.implicitron.models.generic_model import GenericModel

2
pytorch3d/implicitron/models/base_model.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 dataclasses import dataclass, field
from typing import Any, Dict, List, Optional

2
pytorch3d/implicitron/models/feature_extractor/__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.
# pyre-unsafe
from .feature_extractor import FeatureExtractorBase

2
pytorch3d/implicitron/models/feature_extractor/feature_extractor.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 Any, Dict, Optional
import torch

2
pytorch3d/implicitron/models/feature_extractor/resnet_feature_extractor.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 math
from typing import Any, Dict, Optional, Tuple

29
pytorch3d/implicitron/models/generic_model.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
# Note: The #noqa comments below are for unused imports of pluggable implementations
# which are part of implicitron. They ensure that the registry is prepopulated.
@@ -63,7 +65,7 @@ logger = logging.getLogger(__name__)
@registry.register
class GenericModel(ImplicitronModelBase): # pyre-ignore: 13
class GenericModel(ImplicitronModelBase):
"""
GenericModel is a wrapper for the neural implicit
rendering and reconstruction pipeline which consists
@@ -224,34 +226,42 @@ class GenericModel(ImplicitronModelBase): # pyre-ignore: 13
# ---- global encoder settings
global_encoder_class_type: Optional[str] = None
# pyre-fixme[13]: Attribute `global_encoder` is never initialized.
global_encoder: Optional[GlobalEncoderBase]
# ---- raysampler
raysampler_class_type: str = "AdaptiveRaySampler"
# pyre-fixme[13]: Attribute `raysampler` is never initialized.
raysampler: RaySamplerBase
# ---- renderer configs
renderer_class_type: str = "MultiPassEmissionAbsorptionRenderer"
# pyre-fixme[13]: Attribute `renderer` is never initialized.
renderer: BaseRenderer
# ---- image feature extractor settings
# (This is only created if view_pooler is enabled)
# pyre-fixme[13]: Attribute `image_feature_extractor` is never initialized.
image_feature_extractor: Optional[FeatureExtractorBase]
image_feature_extractor_class_type: Optional[str] = None
# ---- view pooler settings
view_pooler_enabled: bool = False
# pyre-fixme[13]: Attribute `view_pooler` is never initialized.
view_pooler: Optional[ViewPooler]
# ---- implicit function settings
implicit_function_class_type: str = "NeuralRadianceFieldImplicitFunction"
# This is just a model, never constructed.
# The actual implicit functions live in self._implicit_functions
# pyre-fixme[13]: Attribute `implicit_function` is never initialized.
implicit_function: ImplicitFunctionBase
# ----- metrics
# pyre-fixme[13]: Attribute `view_metrics` is never initialized.
view_metrics: ViewMetricsBase
view_metrics_class_type: str = "ViewMetrics"
# pyre-fixme[13]: Attribute `regularization_metrics` is never initialized.
regularization_metrics: RegularizationMetricsBase
regularization_metrics_class_type: str = "RegularizationMetrics"
@@ -395,9 +405,11 @@ class GenericModel(ImplicitronModelBase): # pyre-ignore: 13
n_targets = (
1
if evaluation_mode == EvaluationMode.EVALUATION
else batch_size
if self.n_train_target_views <= 0
else min(self.n_train_target_views, batch_size)
else (
batch_size
if self.n_train_target_views <= 0
else min(self.n_train_target_views, batch_size)
)
)
# A helper function for selecting n_target first elements from the input
@@ -422,9 +434,12 @@ class GenericModel(ImplicitronModelBase): # pyre-ignore: 13
ray_bundle: ImplicitronRayBundle = self.raysampler(
target_cameras,
evaluation_mode,
mask=mask_crop[:n_targets]
if mask_crop is not None and sampling_mode == RenderSamplingMode.MASK_SAMPLE
else None,
mask=(
mask_crop[:n_targets]
if mask_crop is not None
and sampling_mode == RenderSamplingMode.MASK_SAMPLE
else None
),
)
# custom_args hold additional arguments to the implicit function.

2
pytorch3d/implicitron/models/global_encoder/__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

2
pytorch3d/implicitron/models/global_encoder/autodecoder.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 warnings
from collections import defaultdict
from typing import Dict, List, Optional, Union

5
pytorch3d/implicitron/models/global_encoder/global_encoder.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 List, Optional, Union
import torch
@@ -57,12 +59,13 @@ class GlobalEncoderBase(ReplaceableBase):
# TODO: probabilistic embeddings?
@registry.register
class SequenceAutodecoder(GlobalEncoderBase, torch.nn.Module): # pyre-ignore: 13
class SequenceAutodecoder(GlobalEncoderBase, torch.nn.Module):
"""
A global encoder implementation which provides an autodecoder encoding
of the frame's sequence identifier.
"""
# pyre-fixme[13]: Attribute `autodecoder` is never initialized.
autodecoder: Autodecoder
def __post_init__(self):

2
pytorch3d/implicitron/models/implicit_function/__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

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