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91 Commits
v0.7.4 ... export-D58

Author SHA1 Message Date
Jeremy Reizenstein
0eac8299d4 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

Differential Revision: D58685326
 2024-06-20 09:24:07 -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
Jeremy Reizenstein
2f11ddc5ee version 0.7.5 
Summary: update

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50806966

fbshipit-source-id: 95fd341c9e5e4e07b689eb71b3a729baff3b8192
 2023-10-31 09:27:49 -07:00
Jeremy Reizenstein
650cc09d22 update notebooks for 0.7.5 
Summary:
```
sed -i 's/startswith((\"1.13.\", \"2.0.\"))/startswith\(\"2.1.\"\)/' *b
```

Reviewed By: shapovalov

Differential Revision: D50806967

fbshipit-source-id: df19462564edb1f840753efeae96b516c7a9f764
 2023-10-31 09:27:49 -07:00
Jeremy Reizenstein
8c15afe71d fix warning from cross 
Summary: Don't call tensor.cross() without dim, to avoid new warning.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D49879590

fbshipit-source-id: e9ba83923b6dc3bcface6782b8b26729ab5b0a4c
 2023-10-30 11:50:23 -07:00
Jeremy Reizenstein
6b437e21a6 CI fixes (#1676) 
Summary:
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1676

Remove CUDA 10.2 build, remove sm35 from cuda12.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50790929

fbshipit-source-id: 2b8cd34493b633a97b4066e0fd61aff077f7ce0c
 2023-10-30 09:50:04 -07:00
Jeremy Reizenstein
03f17ca1ea missing cudaGetLastError 
Summary: Investigating a reported problem.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50791296

fbshipit-source-id: 8dc162b87d02debf05d16c2b4816fcd57234d7e0
 2023-10-30 09:35:08 -07:00
Aniket Patil
a8c70161a1 Fixed typo in cameras.py (#1656) 
Summary:
coodinates -> coordinates

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1656

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50325515

Pulled By: bottler

fbshipit-source-id: 406d2e286ead4fa5e9080092b4918a748495ee23
 2023-10-17 06:07:02 -07:00
Jeremy Reizenstein
28f914bf3b pytorch 2.1, drop mac builds 
Summary: Build updates for PyTorch 2.1

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50345762

fbshipit-source-id: 89bf4edf1c21566aa86a3abca9b4df7c4d1d17a2
 2023-10-17 06:04:06 -07:00
generatedunixname89002005307016
eaf0709d6a suppress errors in vision/fair/pytorch3d 
Differential Revision: D49531589

fbshipit-source-id: 61c28ae33d2e5f75fd1695f35dc99931a3aaf7d3
 2023-09-22 03:33:05 -07:00
Tristan Rice
b7f4ba097c VolumeSampler: expose padding_mode for inside out rendering (#1638) 
Summary:
This exposes a setting on VolumeSampler so you can change the padding_mode. This is very useful when using cameras inside a volume that doesn't cover the entire world. By setting the value to `border` you can get much better behavior than `zeros` which causes edge effects for things like the sky. Border emulates infinitely tall buildings instead.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1638

Test Plan:
Tested with torchdrive

Example before:
![image](https://github.com/facebookresearch/pytorch3d/assets/909104/e99ffb7c-c4ba-40f8-b15c-ad5d1b53f0df)

Example after:
![image](https://github.com/facebookresearch/pytorch3d/assets/909104/f8d9821b-93d5-44b5-b9d4-c1670711ddce)

Reviewed By: MichaelRamamonjisoa

Differential Revision: D49384383

Pulled By: bottler

fbshipit-source-id: 202b526e07320a18944c39a148beec94c0f5d68c
 2023-09-20 08:00:02 -07:00
Jeremy Reizenstein
6f2212da46 use less thrust, maybe help Windows 
Summary: I think we include more thrust than needed, and maybe removing it will help things like  https://github.com/facebookresearch/pytorch3d/issues/1610 with DebugSyncStream errors on Windows.

Reviewed By: shapovalov

Differential Revision: D48949888

fbshipit-source-id: add889c0acf730a039dc9ffd6bbcc24ded20ef27
 2023-09-05 04:40:24 -07:00
Richard Barnes
a3d99cab6b Del (object) from 200 inc vision/fair/mae_st/util/meters.py 
Summary: Python3 makes the use of `(object)` in class inheritance unnecessary. Let's modernize our code by eliminating this.

Reviewed By: itamaro

Differential Revision: D48673863

fbshipit-source-id: 032d6028371f0350252e6b731c74f0f5933c83cd
 2023-08-26 13:55:56 -07:00
Haritha Jayasinghe
d84f274a08 add None option for chamfer distance point reduction (#1605) 
Summary:
The `chamfer_distance` function currently allows `"sum"` or `"mean"` reduction, but does not support returning unreduced (per-point) loss terms. Unreduced losses could be useful if the user wishes to inspect individual losses, or perform additional modifications to loss terms before reduction. One example would be implementing a robust kernel over the loss.

This PR adds a `None` option to the `point_reduction` parameter, similar to `batch_reduction`. In case of bi-directional chamfer loss, both the forward and backward distances are returned (a tuple of Tensors of shape `[D, N]` is returned). If normals are provided, similar logic applies to normals as well.

This PR addresses issue https://github.com/facebookresearch/pytorch3d/issues/622.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1605

Reviewed By: jcjohnson

Differential Revision: D48313857

Pulled By: bottler

fbshipit-source-id: 35c824827a143649b04166c4817449e1341b7fd9
 2023-08-15 10:36:06 -07:00
generatedunixname89002005307016
099fc069fb suppress errors in vision/fair/pytorch3d 
Differential Revision: D47643182

fbshipit-source-id: 598de1526e0c717f2f7038c3f4873ac119c65bba
 2023-07-20 12:37:46 -07:00
Jeremy Reizenstein
57f6e79280 attempt to fix readthedocs 
Summary:
Something's wrong with recommonmark/CommonMark/six, let's see if this fixes it.

https://readthedocs.org/projects/pytorch3d/builds/21292632/

```
  File "/home/docs/checkouts/readthedocs.org/user_builds/pytorch3d/envs/latest/lib/python3.11/site-packages/sphinx/config.py", line 368, in eval_config_file
    execfile_(filename, namespace)
  File "/home/docs/checkouts/readthedocs.org/user_builds/pytorch3d/envs/latest/lib/python3.11/site-packages/sphinx/util/pycompat.py", line 150, in execfile_
    exec_(code, _globals)
  File "/home/docs/checkouts/readthedocs.org/user_builds/pytorch3d/checkouts/latest/docs/conf.py", line 25, in <module>
    from recommonmark.parser import CommonMarkParser
  File "/home/docs/checkouts/readthedocs.org/user_builds/pytorch3d/envs/latest/lib/python3.11/site-packages/recommonmark/parser.py", line 6, in <module>
    from CommonMark import DocParser, HTMLRenderer
  File "/home/docs/checkouts/readthedocs.org/user_builds/pytorch3d/envs/latest/lib/python3.11/site-packages/CommonMark/__init__.py", line 3, in <module>
    from CommonMark.CommonMark import HTMLRenderer
  File "/home/docs/checkouts/readthedocs.org/user_builds/pytorch3d/envs/latest/lib/python3.11/site-packages/CommonMark/CommonMark.py", line 18, in <module>
    HTMLunescape = html.parser.HTMLParser().unescape
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'HTMLParser' object has no attribute 'unescape'
```

Reviewed By: shapovalov

Differential Revision: D47471545

fbshipit-source-id: 48e121e20da535b3cc46b6bd2393d28869067b8b
 2023-07-14 09:49:09 -07:00
Jeremy Reizenstein
2883a07bfe update wheel scripts 
Summary: New versions of cuda etc. I haven't committed recent changes to this for a while

Reviewed By: shapovalov

Differential Revision: D47396136

fbshipit-source-id: d6c27f5056fa8f4a74a628fa1d831159000acf55
 2023-07-14 09:09:46 -07:00
Jeremy Reizenstein
6462aa60ea switch to readthedocs.yaml 
Summary: This is needed from september 2023. As a side effect, implicitron docs should build better because typing.get_args exists etc.

Reviewed By: shapovalov

Differential Revision: D47363855

fbshipit-source-id: a954c5b81b1e5a4435fca146a11aea0d2ca96f45
 2023-07-13 06:56:19 -07:00
Roman Shapovalov
d851bc3173 Read depth maps from OpenXR files 
Summary:
Blender uses OpenEXR to dump depth maps, so we have to support it.
OpenCV requires to explicitly accepth the vulnerabilities by setting the env var before exporting.
We can set it but I think it should be user’s responsibility.
OpenCV error reporting is adequate, so I don’t handle the error on our side.

Reviewed By: bottler

Differential Revision: D47403884

fbshipit-source-id: 2fcadd1df9d0efa0aea563bcfb2e3180b3c4d1d7
 2023-07-13 04:50:03 -07:00
Roman Shapovalov
8164ac4081 Fix: tensor vs array type correctness 
Summary:
For fg-masking depth, we assumed np.array but passed a Tensor; for defining the default depth_mask, vice versa.

Note that we change the intended behaviour for the latter, assuming that 0s are areas with empty depth. When loading depth masks, we replace NaNs with zeros, so it is sensible. It is not a BC change as that branch would crash if executed. Since there was no reports, I assume no one cared.

Reviewed By: bottler

Differential Revision: D47403588

fbshipit-source-id: 1094104176d7d767a5657b5bbc9f5a0cc9da0ede
 2023-07-13 04:50:03 -07:00
Emilien Garreau
9446d91fae Avoid to keep in memory lengths and bins for ImplicitronRayBundle 
Summary:
Convert ImplicitronRayBundle to a "classic" class instead of a dataclass. This change is introduced as a way to preserve the ImplicitronRayBundle interface while allowing two outcomes:
- init lengths arguments is now a Optional[torch.Tensor] instead of torch.Tensor
- lengths is now a property which returns a `torch.Tensor`. The lengths property will either recompute lengths from bins or return the stored _lengths. `_lenghts` is None if bins is set. It saves us a bit of memory.

Reviewed By: shapovalov

Differential Revision: D46686094

fbshipit-source-id: 3c75c0947216476ebff542b6f552d311024a679b
 2023-07-06 02:41:15 -07:00
Emilien Garreau
3d011a9198 Adapt RayPointRefiner and RayMarcher to support bins. 
Summary:
## Context

Bins are used in mipnerf to allow to manipulate easily intervals. For example, by doing the following, `bins[..., :-1]` you will obtain all the left coordinates of your intervals, while doing `bins[..., 1:]` is equals to the right coordinates of your intervals.

We introduce here the support of bins like in MipNerf implementation.

## RayPointRefiner

Small changes have been made to modify RayPointRefiner.
- If bins is None

```
mids = torch.lerp(ray_bundle.lengths[..., 1:], ray_bundle.lengths[…, :-1], 0.5)
z_samples = sample_pdf(
		mids, # [..., npt]
		weights[..., 1:-1], # [..., npt - 1]
               ….
            )
```

- If bins is not None
In the MipNerf implementation the sampling is done on all the bins. It allows us to use the full weights tensor without slashing it.

```
z_samples = sample_pdf(
		ray_bundle.bins, # [..., npt + 1]
		weights, # [..., npt]
               ...
            )
```

## RayMarcher

Add a ray_deltas optional argument. If None, keep the same deltas computation from ray_lengths.

Reviewed By: shapovalov

Differential Revision: D46389092

fbshipit-source-id: d4f1963310065bd31c1c7fac1adfe11cbeaba606
 2023-07-06 02:41:15 -07:00
Emilien Garreau
5910d81b7b Add blurpool following MIPNerf paper. 
Summary:
Add blurpool has defined in [MIP-NeRF](https://arxiv.org/abs/2103.13415).
It has been added has an option for RayPointRefiner.

Reviewed By: shapovalov

Differential Revision: D46356189

fbshipit-source-id: ad841bad86d2b591a68e1cb885d4f781cf26c111
 2023-07-06 02:20:53 -07:00
Emilien Garreau
ccf860f1db Add integrated position encoding based on MIPNerf implementation. 
Summary: Add a new implicit module Integral Position Encoding based on [MIP-NeRF](https://arxiv.org/abs/2103.13415).

Reviewed By: shapovalov

Differential Revision: D46352730

fbshipit-source-id: c6a56134c975d80052b3a11f5e92fd7d95cbff1e
 2023-07-06 02:20:53 -07:00
Emilien Garreau
29b8ebd802 Add utils to approximate the conical frustums as multivariate gaussians. 
Summary:
Introduce methods to approximate the radii of conical frustums along rays as described in [MipNerf](https://arxiv.org/abs/2103.13415):

- Two new attributes are added to ImplicitronRayBundle: bins and radii. Bins is of size n_pts_per_ray + 1. It allows us to manipulate easily and n_pts_per_ray intervals. For example we need the intervals coordinates in the radii computation for \(t_{\mu}, t_{\delta}\). Radii are used to store the radii of the conical frustums.

- Add 3 new methods to compute the radii:
   - approximate_conical_frustum_as_gaussians: It computes the mean along the ray direction, the variance of the
      conical frustum  with respect to t and variance of the conical frustum with respect to its radius. This
      implementation follows the stable computation defined in the paper.
   - compute_3d_diagonal_covariance_gaussian: Will leverage the two previously computed variances to find the
     diagonal covariance of the Gaussian.
   - conical_frustum_to_gaussian: Mix everything together to compute the means and the diagonal covariances along
     the ray of the Gaussians.

- In AbstractMaskRaySampler, introduces the attribute `cast_ray_bundle_as_cone`. If False it won't change the previous behaviour of the RaySampler. However if True, the samplers will sample `n_pts_per_ray +1` instead of `n_pts_per_ray`. This points are then used to set the bins attribute of ImplicitronRayBundle. The support of HeterogeneousRayBundle has not been added since the current code does not allow it. A safeguard has been added to avoid a silent bug in the future.

Reviewed By: shapovalov

Differential Revision: D45269190

fbshipit-source-id: bf22fad12d71d55392f054e3f680013aa0d59b78
 2023-07-06 01:55:41 -07:00
Emilien Garreau
4e7715ce66 Remove unused pyre-ignore or pyre-fixme 
Reviewed By: bottler

Differential Revision: D47223471

fbshipit-source-id: 8bdabf2a69dd7aec7202141122a9c69220ba7ef1
 2023-07-05 02:58:47 -07:00
Jeremy Reizenstein
f68371d398 lints 
Summary: simple

Reviewed By: shapovalov

Differential Revision: D46438865

fbshipit-source-id: 0f41cb3ddd7e7aca4513267d33299531f7e8d373
 2023-06-16 06:48:04 -07:00
Jeremy Reizenstein
dc2c7e489f docs build remove mock after D45600232 
Summary: We now use unittest.mock

Reviewed By: shapovalov

Differential Revision: D45868799

fbshipit-source-id: cd1042dc2c49c82c7b9e024f761c496049a31beb
 2023-06-16 04:50:30 -07:00
Jeremy Reizenstein
42e7de418c fix test_build internal 
Summary: Make test work in isolation, and when run internally make it not try the sqlalchemy files.

Reviewed By: shapovalov

Differential Revision: D46352513

fbshipit-source-id: 7417a25d7a5347d937631c9f56ae4e3242dd622e
 2023-06-16 04:49:02 -07:00
Richard Higgins
88429853b9 1-line tutorial notebook plotting change to fix blank figure problem (#1549) 
Summary:
Hi,

Not sure this is the best fix. But while running this notebook, I only ever saw a blank canvas when trying to visualize the dolphin. It might be that I have a broken dependency, like plotly. I also don't know what the visualization is "supposed" to look like.

But incase other people have this issue, this one line change solved the whole problem for me. Now I have a happy, rotatable dolphin.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1549

Reviewed By: shapovalov

Differential Revision: D46350930

Pulled By: bottler

fbshipit-source-id: e19aa71eb05a93e2955262a2c90d1f0d09576228
 2023-06-16 04:35:15 -07:00
Jeremy Reizenstein
009a3d3b3c projects/nerf subsampling fix for newish pytorch #1441 
Summary: Fix for https://github.com/facebookresearch/pytorch3d/issues/1441 where we were indexing with a tensor on the wrong device.

Reviewed By: shapovalov

Differential Revision: D46276449

fbshipit-source-id: 7750ed45ffecefa5d291fd1eadfe515310c2cf0d
 2023-06-16 04:33:24 -07:00
Roman Shapovalov
cd5db076d5 Adding SQL dataset classes to ImplicitronDataSource imports 
Summary: Making it easier for the clients to use these datasets.

Reviewed By: bottler

Differential Revision: D46727179

fbshipit-source-id: cf619aee4c4c0222a74b30ea590cf37f08f014cc
 2023-06-14 10:51:47 -07:00
Roman Shapovalov
3d886c32d5 Fix: subset filter in DatasetBase implementation 
Summary: In D42739669, I forgot to update the API of existing implementations of DatasetBase to take `subset_filter`. Looks like only one was missing.

Reviewed By: bottler

Differential Revision: D46724488

fbshipit-source-id: 13ab7a457f853278cf06955aad0cc2bab5fbcce6
 2023-06-14 08:48:14 -07:00
Roman Shapovalov
5592d25f68 Fix: changed deprecated matplotlib parameter 
Summary:
The parameter was renamed in MPL 3.5.0 in 2021, and the deprecated version is no longer supported.

https://matplotlib.org/stable/api/prev_api_changes/api_changes_3.5.0.html#the-first-parameter-of-axes-grid-and-axis-grid-has-been-renamed-to-visible

Reviewed By: bottler

Differential Revision: D46724242

fbshipit-source-id: 04e2ab6d63369d939ea4f0ce7d64693e0b95ee91
 2023-06-14 08:48:14 -07:00
Roman Shapovalov
09a99f2e6d Support limiting num sequences per category. 
Summary:
Adds stratified sampling of sequences within categories applied after category / sequence filters but before the num sequence limit.
It respects the insertion order into the sequence_annots table, i.e. takes top N sequences within each category.

Reviewed By: bottler

Differential Revision: D46724002

fbshipit-source-id: 597cb2a795c3f3bc07f838fc51b4e95a4f981ad3
 2023-06-14 07:12:02 -07:00
Norman Mueller
5ffeb4d580 Single directional chamfer distance and non-absolute cosine similarity 
Summary: Single directional chamfer distance and option to use non-absolute cosine similarity

Reviewed By: bottler

Differential Revision: D46593980

fbshipit-source-id: b2e591706a0cdde1c2d361614cecebb84a581433
 2023-06-13 09:09:15 -07:00
generatedunixname89002005307016
573a42cd5f suppress errors in vision/fair/pytorch3d 
Differential Revision: D46685078

fbshipit-source-id: daf2e75f24b68d2eab74cddca8ab9446e96951e7
 2023-06-13 07:14:48 -07:00
Jeremy Reizenstein
928efdd640 fix camera plot for new matplotlib 
Summary: fixes https://github.com/facebookresearch/pytorch3d/issues/1554 , needed for Matplotlib 3.6+

Reviewed By: patricklabatut

Differential Revision: D46438822

fbshipit-source-id: f3c06ad5d8e881a635edd14f96d498dca73c169f
 2023-06-07 05:10:10 -07:00
Emilien Garreau
35badc0892 Fix inversion between fine and coarse implicit_functions 
Summary: Fine implicit function was called before the coarse implicit function.

Reviewed By: shapovalov

Differential Revision: D46224224

fbshipit-source-id: 6b1cc00cc823d3ea7a5b42774c9ec3b73a69edb5
 2023-05-26 08:33:54 -07:00
generatedunixname89002005307016
e0c3ca97ff upgrade pyre version in fbcode/vision - batch 2 
Differential Revision: D46119066

fbshipit-source-id: b766118b9dcc07075d328fba73f272419dc9fc38
 2023-05-23 20:34:54 -07:00
Roman Shapovalov
d2119c285f Serialising dynamic arrays in SQL; read-only SQLite connection in SQL Dataset 
Summary:
1. We may need to store arrays of unknown shape in the database. It implements and tests serialisation.

2. Previously, when an inexisting metadata file was passed to SqlIndexDataset, it would try to open it and create an empty file, then crash. We now open the file in a read-only mode, so the error message is more intuitive. Note that the implementation is SQLite specific.

Reviewed By: bottler

Differential Revision: D46047857

fbshipit-source-id: 3064ae4f8122b4fc24ad3d6ab696572ebe8d0c26
 2023-05-22 02:24:49 -07:00
Jeremy Reizenstein
ff80183fdb resources fix 
Summary: I don't know why RE tests sometimes fail here, but maybe it's a race condition. If that's right, this should fix it.

Reviewed By: shapovalov

Differential Revision: D46020054

fbshipit-source-id: 20b746b09ad9bd77c2601ac681047ccc6cc27ed9
 2023-05-19 06:41:33 -07:00
Roman Shapovalov
b0462598ac Refactor: FrameDataBuilder is more extensible. 
Summary:
This is mostly a refactoring diff to reduce friction in extending the frame data.

Slight functional changes: dataset getitem now accepts (seq_name, frame_number_as_singleton_tensor) as a non-advertised feature. Otherwise this code crashes:
```
item = dataset[0]
dataset[item.sequence_name, item.frame_number]
```

Reviewed By: bottler

Differential Revision: D45780175

fbshipit-source-id: 75b8e8d3dabed954a804310abdbd8ab44a8dea29
 2023-05-17 10:38:34 -07:00
Virendra Kumar Pathak
d08fe6d45a Softly deprecate the get_str=False flag. 
Summary: We don't want to use print directly in stats.print() method. Instead this method will return the output string to the caller.

Reviewed By: shapovalov

Differential Revision: D45356240

fbshipit-source-id: 2cabe3cdfb9206bf09aa7b3cdd2263148a5ba145
 2023-05-14 01:24:31 -07:00
294 changed files with 4993 additions and 1472 deletions
Expand all files Collapse all files

49
.circleci/config.in.yml
View File

@@ -64,7 +64,7 @@ jobs:
CUDA_VERSION: "11.3"
resource_class: gpu.nvidia.small.multi
machine:
image: ubuntu-2004:202101-01
image: linux-cuda-11:default
steps:
- checkout
- <<: *setupcuda
@@ -116,7 +116,7 @@ jobs:
# so we aren't running the tests.
- run:
name: build
no_output_timeout: 20m
no_output_timeout: 40m
command: MAX_JOBS=15 TEST_FLAG=--no-test python3 packaging/build_conda.py
- store_artifacts:
path: /opt/conda/conda-bld/linux-64
@@ -128,7 +128,7 @@ jobs:
binary_linux_conda_cuda:
<<: *binary_common
machine:
image: ubuntu-1604-cuda-10.2:202012-01
image: linux-cuda-11:default
resource_class: gpu.nvidia.small.multi
steps:
- checkout
@@ -145,7 +145,7 @@ jobs:
docker pull $TESTRUN_DOCKER_IMAGE
- run:
name: Build and run tests
no_output_timeout: 20m
no_output_timeout: 40m
command: |
set -e
@@ -156,24 +156,6 @@ jobs:
docker run --gpus all --ipc=host -v $(pwd):/remote -w /remote ${VARS_TO_PASS} ${TESTRUN_DOCKER_IMAGE} python3 ./packaging/build_conda.py
binary_macos_wheel:
<<: *binary_common
macos:
xcode: "13.4.1"
steps:
- checkout
- run:
# Cannot easily deduplicate this as source'ing activate
# will set environment variables which we need to propagate
# to build_wheel.sh
command: |
curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
sh conda.sh -b
source $HOME/miniconda3/bin/activate
packaging/build_wheel.sh
- store_artifacts:
path: dist
workflows:
version: 2
build_and_test:
@@ -182,23 +164,8 @@ workflows:
# context: DOCKERHUB_TOKEN
{{workflows()}}
- binary_linux_conda_cuda:
name: testrun_conda_cuda_py38_cu102_pyt190
name: testrun_conda_cuda_py310_cu117_pyt201
context: DOCKERHUB_TOKEN
python_version: "3.8"
pytorch_version: '1.9.0'
cu_version: "cu102"
- binary_macos_wheel:
cu_version: cpu
name: macos_wheel_py3.8_cpu
python_version: '3.8'
pytorch_version: '1.13.0'
- binary_macos_wheel:
cu_version: cpu
name: macos_wheel_py3.9_cpu
python_version: '3.9'
pytorch_version: '1.13.0'
- binary_macos_wheel:
cu_version: cpu
name: macos_wheel_py3.10_cpu
python_version: '3.10'
pytorch_version: '1.13.0'
python_version: "3.10"
pytorch_version: '2.0.1'
cu_version: "cu117"

587
.circleci/config.yml
View File

@@ -64,7 +64,7 @@ jobs:
CUDA_VERSION: "11.3"
resource_class: gpu.nvidia.small.multi
machine:
image: ubuntu-2004:202101-01
image: linux-cuda-11:default
steps:
- checkout
- <<: *setupcuda
@@ -116,7 +116,7 @@ jobs:
# so we aren't running the tests.
- run:
name: build
no_output_timeout: 20m
no_output_timeout: 40m
command: MAX_JOBS=15 TEST_FLAG=--no-test python3 packaging/build_conda.py
- store_artifacts:
path: /opt/conda/conda-bld/linux-64
@@ -128,7 +128,7 @@ jobs:
binary_linux_conda_cuda:
<<: *binary_common
machine:
image: ubuntu-1604-cuda-10.2:202012-01
image: linux-cuda-11:default
resource_class: gpu.nvidia.small.multi
steps:
- checkout
@@ -145,7 +145,7 @@ jobs:
docker pull $TESTRUN_DOCKER_IMAGE
- run:
name: Build and run tests
no_output_timeout: 20m
no_output_timeout: 40m
command: |
set -e
@@ -156,119 +156,12 @@ jobs:
docker run --gpus all --ipc=host -v $(pwd):/remote -w /remote ${VARS_TO_PASS} ${TESTRUN_DOCKER_IMAGE} python3 ./packaging/build_conda.py
binary_macos_wheel:
<<: *binary_common
macos:
xcode: "13.4.1"
steps:
- checkout
- run:
# Cannot easily deduplicate this as source'ing activate
# will set environment variables which we need to propagate
# to build_wheel.sh
command: |
curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
sh conda.sh -b
source $HOME/miniconda3/bin/activate
packaging/build_wheel.sh
- store_artifacts:
path: dist
workflows:
version: 2
build_and_test:
jobs:
# - main:
# context: DOCKERHUB_TOKEN
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt1100
python_version: '3.8'
pytorch_version: 1.10.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py38_cu111_pyt1100
python_version: '3.8'
pytorch_version: 1.10.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py38_cu113_pyt1100
python_version: '3.8'
pytorch_version: 1.10.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt1101
python_version: '3.8'
pytorch_version: 1.10.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py38_cu111_pyt1101
python_version: '3.8'
pytorch_version: 1.10.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py38_cu113_pyt1101
python_version: '3.8'
pytorch_version: 1.10.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt1102
python_version: '3.8'
pytorch_version: 1.10.2
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py38_cu111_pyt1102
python_version: '3.8'
pytorch_version: 1.10.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py38_cu113_pyt1102
python_version: '3.8'
pytorch_version: 1.10.2
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt1110
python_version: '3.8'
pytorch_version: 1.11.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py38_cu111_pyt1110
python_version: '3.8'
pytorch_version: 1.11.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py38_cu113_pyt1110
python_version: '3.8'
pytorch_version: 1.11.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda115
context: DOCKERHUB_TOKEN
cu_version: cu115
name: linux_conda_py38_cu115_pyt1110
python_version: '3.8'
pytorch_version: 1.11.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt1120
python_version: '3.8'
pytorch_version: 1.12.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
@@ -283,12 +176,6 @@ workflows:
name: linux_conda_py38_cu116_pyt1120
python_version: '3.8'
pytorch_version: 1.12.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt1121
python_version: '3.8'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
@@ -360,94 +247,89 @@ workflows:
python_version: '3.8'
pytorch_version: 2.0.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py39_cu102_pyt1100
python_version: '3.9'
pytorch_version: 1.10.0
cu_version: cu118
name: linux_conda_py38_cu118_pyt210
python_version: '3.8'
pytorch_version: 2.1.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py39_cu111_pyt1100
python_version: '3.9'
pytorch_version: 1.10.0
cu_version: cu121
name: linux_conda_py38_cu121_pyt210
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_pyt1100
python_version: '3.9'
pytorch_version: 1.10.0
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:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py39_cu102_pyt1101
python_version: '3.9'
pytorch_version: 1.10.1
cu_version: cu121
name: linux_conda_py38_cu121_pyt211
python_version: '3.8'
pytorch_version: 2.1.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py39_cu111_pyt1101
python_version: '3.9'
pytorch_version: 1.10.1
cu_version: cu118
name: linux_conda_py38_cu118_pyt212
python_version: '3.8'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py39_cu113_pyt1101
python_version: '3.9'
pytorch_version: 1.10.1
cu_version: cu121
name: linux_conda_py38_cu121_pyt212
python_version: '3.8'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py39_cu102_pyt1102
python_version: '3.9'
pytorch_version: 1.10.2
cu_version: cu118
name: linux_conda_py38_cu118_pyt220
python_version: '3.8'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py39_cu111_pyt1102
python_version: '3.9'
pytorch_version: 1.10.2
cu_version: cu121
name: linux_conda_py38_cu121_pyt220
python_version: '3.8'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py39_cu113_pyt1102
python_version: '3.9'
pytorch_version: 1.10.2
cu_version: cu118
name: linux_conda_py38_cu118_pyt222
python_version: '3.8'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py39_cu102_pyt1110
python_version: '3.9'
pytorch_version: 1.11.0
cu_version: cu121
name: linux_conda_py38_cu121_pyt222
python_version: '3.8'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py39_cu111_pyt1110
python_version: '3.9'
pytorch_version: 1.11.0
cu_version: cu118
name: linux_conda_py38_cu118_pyt231
python_version: '3.8'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu113
name: linux_conda_py39_cu113_pyt1110
python_version: '3.9'
pytorch_version: 1.11.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda115
context: DOCKERHUB_TOKEN
cu_version: cu115
name: linux_conda_py39_cu115_pyt1110
python_version: '3.9'
pytorch_version: 1.11.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py39_cu102_pyt1120
python_version: '3.9'
pytorch_version: 1.12.0
cu_version: cu121
name: linux_conda_py38_cu121_pyt231
python_version: '3.8'
pytorch_version: 2.3.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
@@ -462,12 +344,6 @@ workflows:
name: linux_conda_py39_cu116_pyt1120
python_version: '3.9'
pytorch_version: 1.12.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py39_cu102_pyt1121
python_version: '3.9'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
@@ -539,37 +415,89 @@ workflows:
python_version: '3.9'
pytorch_version: 2.0.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py310_cu102_pyt1110
python_version: '3.10'
pytorch_version: 1.11.0
cu_version: cu118
name: linux_conda_py39_cu118_pyt210
python_version: '3.9'
pytorch_version: 2.1.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu111
name: linux_conda_py310_cu111_pyt1110
python_version: '3.10'
pytorch_version: 1.11.0
cu_version: cu121
name: linux_conda_py39_cu121_pyt210
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_pyt1110
python_version: '3.10'
pytorch_version: 1.11.0
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:cuda115
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu115
name: linux_conda_py310_cu115_pyt1110
python_version: '3.10'
pytorch_version: 1.11.0
cu_version: cu121
name: linux_conda_py39_cu121_pyt211
python_version: '3.9'
pytorch_version: 2.1.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py310_cu102_pyt1120
python_version: '3.10'
pytorch_version: 1.12.0
cu_version: cu118
name: linux_conda_py39_cu118_pyt212
python_version: '3.9'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py39_cu121_pyt212
python_version: '3.9'
pytorch_version: 2.1.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py39_cu118_pyt220
python_version: '3.9'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py39_cu121_pyt220
python_version: '3.9'
pytorch_version: 2.2.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_py39_cu118_pyt222
python_version: '3.9'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
name: linux_conda_py39_cu121_pyt222
python_version: '3.9'
pytorch_version: 2.2.2
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
cu_version: cu118
name: linux_conda_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:cuda113
context: DOCKERHUB_TOKEN
@@ -584,12 +512,6 @@ workflows:
name: linux_conda_py310_cu116_pyt1120
python_version: '3.10'
pytorch_version: 1.12.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py310_cu102_pyt1121
python_version: '3.10'
pytorch_version: 1.12.1
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda113
context: DOCKERHUB_TOKEN
@@ -660,24 +582,219 @@ workflows:
name: linux_conda_py310_cu118_pyt201
python_version: '3.10'
pytorch_version: 2.0.1
- binary_linux_conda_cuda:
name: testrun_conda_cuda_py38_cu102_pyt190
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda118
context: DOCKERHUB_TOKEN
python_version: "3.8"
pytorch_version: '1.9.0'
cu_version: "cu102"
- binary_macos_wheel:
cu_version: cpu
name: macos_wheel_py3.8_cpu
python_version: '3.8'
pytorch_version: '1.13.0'
- binary_macos_wheel:
cu_version: cpu
name: macos_wheel_py3.9_cpu
python_version: '3.9'
pytorch_version: '1.13.0'
- binary_macos_wheel:
cu_version: cpu
name: macos_wheel_py3.10_cpu
cu_version: cu118
name: linux_conda_py310_cu118_pyt210
python_version: '3.10'
pytorch_version: '1.13.0'
pytorch_version: 2.1.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
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_py311_cu118_pyt210
python_version: '3.11'
pytorch_version: 2.1.0
- binary_linux_conda:
conda_docker_image: pytorch/conda-builder:cuda121
context: DOCKERHUB_TOKEN
cu_version: cu121
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_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_cuda:
name: testrun_conda_cuda_py310_cu117_pyt201
context: DOCKERHUB_TOKEN
python_version: "3.10"
pytorch_version: '2.0.1'
cu_version: "cu117"

31
.circleci/regenerate.py
View File

@@ -18,24 +18,23 @@ from packaging import version
# The CUDA versions which have pytorch conda packages available for linux for each
# version of pytorch.
# Pytorch 1.4 also supports cuda 10.0 but we no longer build for cuda 10.0 at all.
CONDA_CUDA_VERSIONS = {
"1.10.0": ["cu102", "cu111", "cu113"],
"1.10.1": ["cu102", "cu111", "cu113"],
"1.10.2": ["cu102", "cu111", "cu113"],
"1.11.0": ["cu102", "cu111", "cu113", "cu115"],
"1.12.0": ["cu102", "cu113", "cu116"],
"1.12.1": ["cu102", "cu113", "cu116"],
"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"],
}
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:]
@@ -50,12 +49,24 @@ def pytorch_versions_for_python(python_version):
for i in CONDA_CUDA_VERSIONS
if version.Version(i) >= version.Version("1.11.0")
]
if python_version == "3.11":
return [
i
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"]:
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

9
INSTALL.md
View File

@@ -9,7 +9,7 @@ The core library is written in PyTorch. Several components have underlying imple
- Linux or macOS or Windows
- Python 3.8, 3.9 or 3.10
- PyTorch 1.10.0, 1.10.1, 1.10.2, 1.11.0, 1.12.0, 1.12.1, 1.13.0, 2.0.0 or 2.0.1.
- PyTorch 1.12.0, 1.12.1, 1.13.0, 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2.2.2, 2.3.0 or 2.3.1.
- 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)
@@ -77,13 +77,8 @@ Or, to install a nightly (non-official, alpha) build:
# Anaconda Cloud
conda install pytorch3d -c pytorch3d-nightly
```
### 2. Install from PyPI, on Mac only.
This works with pytorch 1.13.0 only. The build is CPU only.
```
pip install pytorch3d
```
### 3. Install wheels for Linux
### 2. Install wheels for Linux
We have prebuilt wheels with CUDA for Linux for PyTorch 1.11.0, for each of the supported CUDA versions,
for Python 3.8 and 3.9. This is for ease of use on Google Colab.
These are installed in a special way.

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.

27
docs/.readthedocs.yaml Normal file
View File

@@ -0,0 +1,27 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# Read the Docs configuration file
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
# Required
version: 2
# Set the version of Python and other tools you might need
build:
os: ubuntu-22.04
tools:
python: "3.11"
# Build documentation in the docs/ directory with Sphinx
sphinx:
configuration: docs/conf.py
# We recommend specifying your dependencies to enable reproducible builds:
# https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
python:
install:
- requirements: docs/requirements.txt

2
docs/README.md
View File

@@ -3,7 +3,7 @@
### Install dependencies
```
pip install -U recommonmark mock sphinx sphinx_rtd_theme sphinx_markdown_tables
pip install -U recommonmark sphinx sphinx_rtd_theme sphinx_markdown_tables
```
### Add symlink to the root README.md

7
docs/requirements.txt
View File

@@ -1,12 +1,11 @@
docutils>=0.14
Sphinx>=1.7
recommonmark==0.4.0
recommonmark
sphinx_rtd_theme
sphinx_markdown_tables
mock
numpy
iopath
fvcore
https://download.pytorch.org/whl/cpu/torchvision-0.8.2%2Bcpu-cp37-cp37m-linux_x86_64.whl
https://download.pytorch.org/whl/cpu/torch-1.7.1%2Bcpu-cp37-cp37m-linux_x86_64.whl
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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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",

32
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((\"1.13.\", \"2.0.\")) 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 fvcore 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'"
]
},
{
@@ -262,7 +268,7 @@
" points = sample_points_from_meshes(mesh, 5000)\n",
" x, y, z = points.clone().detach().cpu().squeeze().unbind(1) \n",
" fig = plt.figure(figsize=(5, 5))\n",
" ax = Axes3D(fig)\n",
" ax = fig.add_subplot(111, projection='3d')\n",
" ax.scatter3D(x, z, -y)\n",
" ax.set_xlabel('x')\n",
" ax.set_ylabel('z')\n",

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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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((\"1.13.\", \"2.0.\")) 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 fvcore 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'"
]
},
{

2
docs/tutorials/utils/camera_visualization.py
View File

@@ -33,7 +33,7 @@ def plot_camera_scene(cameras, cameras_gt, status: str):
a string passed inside the `status` argument.
"""
fig = plt.figure()
ax = fig.gca(projection="3d")
ax = fig.add_subplot(projection="3d")
ax.clear()
ax.set_title(status)
handle_cam = plot_cameras(ax, cameras, color="#FF7D1E")

19
packaging/build_conda.py
View File

@@ -50,7 +50,6 @@ def setup_cuda():
os.environ["FORCE_CUDA"] = "1"
basic_nvcc_flags = (
"-gencode=arch=compute_35,code=sm_35 "
"-gencode=arch=compute_50,code=sm_50 "
"-gencode=arch=compute_60,code=sm_60 "
"-gencode=arch=compute_70,code=sm_70 "
@@ -58,13 +57,19 @@ def setup_cuda():
"-gencode=arch=compute_50,code=compute_50"
)
if CU_VERSION == "cu102":
nvcc_flags = basic_nvcc_flags
elif CU_VERSION == "cu110":
nvcc_flags = "-gencode=arch=compute_80,code=sm_80 " + basic_nvcc_flags
nvcc_flags = "-gencode=arch=compute_35,code=sm_35 " + basic_nvcc_flags
elif CU_VERSION < ("cu118"):
nvcc_flags = (
"-gencode=arch=compute_35,code=sm_35 "
+ "-gencode=arch=compute_80,code=sm_80 "
+ "-gencode=arch=compute_86,code=sm_86 "
+ basic_nvcc_flags
)
else:
nvcc_flags = (
"-gencode=arch=compute_80,code=sm_80 "
+ "-gencode=arch=compute_86,code=sm_86 "
+ "-gencode=arch=compute_90,code=sm_90 "
+ basic_nvcc_flags
)
@@ -75,6 +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(".", "")

14
packaging/linux_wheels/go.sh
View File

@@ -5,7 +5,13 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
sudo docker run --rm -v "$PWD/../../:/inside" pytorch/conda-cuda bash inside/packaging/linux_wheels/inside.sh
sudo docker run --rm -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu113 pytorch/conda-builder:cuda113 bash inside/packaging/linux_wheels/inside.sh
sudo docker run --rm -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu115 pytorch/conda-builder:cuda115 bash inside/packaging/linux_wheels/inside.sh
sudo docker run --rm -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu116 pytorch/conda-builder:cuda116 bash inside/packaging/linux_wheels/inside.sh
# Some directory to persist downloaded conda packages
conda_cache=/raid/$USER/building_conda_cache
mkdir -p "$conda_cache"
sudo docker run --rm -v "$conda_cache:/conda_cache" -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu113 pytorch/conda-builder:cuda113 bash inside/packaging/linux_wheels/inside.sh
sudo docker run --rm -v "$conda_cache:/conda_cache" -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu115 pytorch/conda-builder:cuda115 bash inside/packaging/linux_wheels/inside.sh
sudo docker run --rm -v "$conda_cache:/conda_cache" -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu116 pytorch/conda-builder:cuda116 bash inside/packaging/linux_wheels/inside.sh
sudo docker run --rm -v "$conda_cache:/conda_cache" -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu117 pytorch/conda-builder:cuda117 bash inside/packaging/linux_wheels/inside.sh
sudo docker run --rm -v "$conda_cache:/conda_cache" -v "$PWD/../../:/inside" -e SELECTED_CUDA=cu118 pytorch/conda-builder:cuda118 bash inside/packaging/linux_wheels/inside.sh

63
packaging/linux_wheels/inside.sh
View File

@@ -16,23 +16,32 @@ VERSION=$(python -c "exec(open('pytorch3d/__init__.py').read()); print(__version
export BUILD_VERSION=$VERSION
export FORCE_CUDA=1
export MAX_JOBS=8
export CONDA_PKGS_DIRS=/conda_cache
wget --no-verbose https://github.com/NVIDIA/cub/archive/1.10.0.tar.gz
tar xzf 1.10.0.tar.gz
CUB_HOME=$(realpath ./cub-1.10.0)
export CUB_HOME
echo "CUB_HOME is now $CUB_HOME"
if false
then
# We used to have to do this for old versions of CUDA
wget --no-verbose https://github.com/NVIDIA/cub/archive/1.10.0.tar.gz
tar xzf 1.10.0.tar.gz
CUB_HOME=$(realpath ./cub-1.10.0)
export CUB_HOME
echo "CUB_HOME is now $CUB_HOME"
fi
# As a rule, we want to build for any combination of dependencies which is supported by
# PyTorch3D and not older than the current Google Colab set up.
PYTHON_VERSIONS="3.7 3.8 3.9 3.10"
PYTHON_VERSIONS="3.8 3.9 3.10"
# the keys are pytorch versions
declare -A CONDA_CUDA_VERSIONS=(
["1.10.1"]="cu111 cu113"
["1.10.2"]="cu111 cu113"
["1.10.0"]="cu111 cu113"
["1.11.0"]="cu111 cu113 cu115"
# ["1.11.0"]="cu113"
# ["1.12.0"]="cu113"
# ["1.12.1"]="cu113"
# ["1.13.0"]="cu116"
# ["1.13.1"]="cu116 cu117"
# ["2.0.0"]="cu117 cu118"
["2.0.1"]="cu117 cu118"
)
@@ -41,39 +50,43 @@ for python_version in $PYTHON_VERSIONS
do
for pytorch_version in "${!CONDA_CUDA_VERSIONS[@]}"
do
if [[ "3.7 3.8" != *$python_version* ]] && [[ "1.7.0" == *$pytorch_version* ]]
then
#python 3.9 and later not supported by pytorch 1.7.0 and before
continue
fi
if [[ "3.7 3.8 3.9" != *$python_version* ]] && [[ "1.7.0 1.7.1 1.8.0 1.8.1 1.9.0 1.9.1 1.10.0 1.10.1 1.10.2" == *$pytorch_version* ]]
then
#python 3.10 and later not supported by pytorch 1.10.2 and before
continue
fi
extra_channel="-c conda-forge"
extra_channel="-c nvidia"
cudatools="pytorch-cuda"
if [[ "1.11.0" == "$pytorch_version" ]]
then
extra_channel=""
cudatools="cudatoolkit"
fi
if [[ "1.12.0" == "$pytorch_version" ]] || [[ "1.12.1" == "$pytorch_version" ]]
then
extra_channel="-c conda-forge"
cudatools="cudatoolkit"
fi
for cu_version in ${CONDA_CUDA_VERSIONS[$pytorch_version]}
do
if [[ "cu113 cu115 cu116" == *$cu_version* ]]
# ^^^ CUDA versions listed here have to be built
# in their own containers.
then
if [[ $SELECTED_CUDA != "$cu_version" ]]
then
continue
fi
elif [[ $SELECTED_CUDA != "" ]]
then
continue
fi
case "$cu_version" in
cu118)
export CUDA_HOME=/usr/local/cuda-11.8/
export CUDA_TAG=11.8
export NVCC_FLAGS="-gencode=arch=compute_35,code=sm_35 -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=sm_80 -gencode=arch=compute_86,code=sm_86 -gencode=arch=compute_50,code=compute_50"
;;
cu117)
export CUDA_HOME=/usr/local/cuda-11.7/
export CUDA_TAG=11.7
export NVCC_FLAGS="-gencode=arch=compute_35,code=sm_35 -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=sm_80 -gencode=arch=compute_86,code=sm_86 -gencode=arch=compute_50,code=compute_50"
;;
cu116)
export CUDA_HOME=/usr/local/cuda-11.6/
export CUDA_TAG=11.6
@@ -130,7 +143,7 @@ do
conda create -y -n "$tag" "python=$python_version"
conda activate "$tag"
# shellcheck disable=SC2086
conda install -y -c pytorch $extra_channel "pytorch=$pytorch_version" "cudatoolkit=$CUDA_TAG" torchvision
conda install -y -c pytorch $extra_channel "pytorch=$pytorch_version" "$cudatools=$CUDA_TAG"
pip install fvcore iopath
echo "python version" "$python_version" "pytorch version" "$pytorch_version" "cuda version" "$cu_version" "tag" "$tag"

3
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') }}

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

2
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.

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

2
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

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 = [

10
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
@@ -21,7 +23,6 @@ from pytorch3d.implicitron.tools.config import (
run_auto_creation,
)
from pytorch3d.implicitron.tools.stats import Stats
from pytorch3d.renderer.cameras import CamerasBase
from torch.utils.data import DataLoader, Dataset
from .utils import seed_all_random_engines
@@ -111,6 +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,
*,
@@ -256,7 +259,6 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
list(log_vars),
plot_file=os.path.join(exp_dir, "train_stats.pdf"),
visdom_env=visdom_env_charts,
verbose=False,
visdom_server=self.visdom_server,
visdom_port=self.visdom_port,
)
@@ -382,7 +384,8 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
# print textual status update
if it % self.metric_print_interval == 0 or last_iter:
stats.print(stat_set=trainmode, max_it=n_batches)
std_out = stats.get_status_string(stat_set=trainmode, max_it=n_batches)
logger.info(std_out)
# visualize results
if (
@@ -392,7 +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

27
projects/implicitron_trainer/tests/experiment.yaml
View File

@@ -129,6 +129,19 @@ data_source_ImplicitronDataSource_args:
dataset_length_train: 0
dataset_length_val: 0
dataset_length_test: 0
data_loader_map_provider_TrainEvalDataLoaderMapProvider_args:
batch_size: 1
num_workers: 0
dataset_length_train: 0
dataset_length_val: 0
dataset_length_test: 0
train_conditioning_type: SAME
val_conditioning_type: SAME
test_conditioning_type: KNOWN
images_per_seq_options: []
sample_consecutive_frames: false
consecutive_frames_max_gap: 0
consecutive_frames_max_gap_seconds: 0.1
model_factory_ImplicitronModelFactory_args:
resume: true
model_class_type: GenericModel
@@ -203,6 +216,7 @@ model_factory_ImplicitronModelFactory_args:
n_rays_total_training: null
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
cast_ray_bundle_as_cone: false
scene_extent: 8.0
scene_center:
- 0.0
@@ -215,6 +229,7 @@ model_factory_ImplicitronModelFactory_args:
n_rays_total_training: null
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
cast_ray_bundle_as_cone: false
min_depth: 0.1
max_depth: 8.0
renderer_LSTMRenderer_args:
@@ -234,6 +249,8 @@ model_factory_ImplicitronModelFactory_args:
append_coarse_samples_to_fine: true
density_noise_std_train: 0.0
return_weights: false
blurpool_weights: false
sample_pdf_eps: 1.0e-05
raymarcher_CumsumRaymarcher_args:
surface_thickness: 1
bg_color:
@@ -346,6 +363,7 @@ model_factory_ImplicitronModelFactory_args:
n_hidden_neurons_dir: 128
input_xyz: true
xyz_ray_dir_in_camera_coords: false
use_integrated_positional_encoding: false
transformer_dim_down_factor: 2.0
n_hidden_neurons_xyz: 80
n_layers_xyz: 2
@@ -357,6 +375,7 @@ model_factory_ImplicitronModelFactory_args:
n_hidden_neurons_dir: 128
input_xyz: true
xyz_ray_dir_in_camera_coords: false
use_integrated_positional_encoding: false
transformer_dim_down_factor: 1.0
n_hidden_neurons_xyz: 256
n_layers_xyz: 8
@@ -629,6 +648,7 @@ model_factory_ImplicitronModelFactory_args:
n_rays_total_training: null
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
cast_ray_bundle_as_cone: false
scene_extent: 8.0
scene_center:
- 0.0
@@ -641,6 +661,7 @@ model_factory_ImplicitronModelFactory_args:
n_rays_total_training: null
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
cast_ray_bundle_as_cone: false
min_depth: 0.1
max_depth: 8.0
renderer_LSTMRenderer_args:
@@ -660,6 +681,8 @@ model_factory_ImplicitronModelFactory_args:
append_coarse_samples_to_fine: true
density_noise_std_train: 0.0
return_weights: false
blurpool_weights: false
sample_pdf_eps: 1.0e-05
raymarcher_CumsumRaymarcher_args:
surface_thickness: 1
bg_color:
@@ -724,6 +747,7 @@ model_factory_ImplicitronModelFactory_args:
n_hidden_neurons_dir: 128
input_xyz: true
xyz_ray_dir_in_camera_coords: false
use_integrated_positional_encoding: false
transformer_dim_down_factor: 2.0
n_hidden_neurons_xyz: 80
n_layers_xyz: 2
@@ -735,6 +759,7 @@ model_factory_ImplicitronModelFactory_args:
n_hidden_neurons_dir: 128
input_xyz: true
xyz_ray_dir_in_camera_coords: false
use_integrated_positional_encoding: false
transformer_dim_down_factor: 1.0
n_hidden_neurons_xyz: 256
n_layers_xyz: 8
@@ -962,6 +987,7 @@ model_factory_ImplicitronModelFactory_args:
n_hidden_neurons_dir: 128
input_xyz: true
xyz_ray_dir_in_camera_coords: false
use_integrated_positional_encoding: false
transformer_dim_down_factor: 2.0
n_hidden_neurons_xyz: 80
n_layers_xyz: 2
@@ -973,6 +999,7 @@ model_factory_ImplicitronModelFactory_args:
n_hidden_neurons_dir: 128
input_xyz: true
xyz_ray_dir_in_camera_coords: false
use_integrated_positional_encoding: false
transformer_dim_down_factor: 1.0
n_hidden_neurons_xyz: 256
n_layers_xyz: 8

9
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
@@ -132,6 +134,13 @@ class TestExperiment(unittest.TestCase):
# Check that the default config values, defined by Experiment and its
# members, is what we expect it to be.
cfg = OmegaConf.structured(experiment.Experiment)
# the following removes the possible effect of env variables
ds_arg = cfg.data_source_ImplicitronDataSource_args
ds_arg.dataset_map_provider_JsonIndexDatasetMapProvider_args.dataset_root = ""
ds_arg.dataset_map_provider_JsonIndexDatasetMapProviderV2_args.dataset_root = ""
if "dataset_map_provider_SqlIndexDatasetMapProvider_args" in ds_arg:
del ds_arg.dataset_map_provider_SqlIndexDatasetMapProvider_args
cfg.training_loop_ImplicitronTrainingLoop_args.visdom_port = 8097
yaml = OmegaConf.to_yaml(cfg, sort_keys=False)
if DEBUG:
(DATA_DIR / "experiment.yaml").write_text(yaml)

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:

6
projects/nerf/nerf/raysampler.py
View File

@@ -330,9 +330,9 @@ class NeRFRaysampler(torch.nn.Module):
if self.training:
# During training we randomly subsample rays.
sel_rays = torch.randperm(n_pixels, device=device)[
: self._mc_raysampler._n_rays_per_image
]
sel_rays = torch.randperm(
n_pixels, device=full_ray_bundle.lengths.device
)[: self._mc_raysampler._n_rays_per_image]
else:
# In case we test, we take only the requested chunk.
if chunksize is None:

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__ = "0.7.4"
# pyre-unsafe
__version__ = "0.7.6"

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

3
pytorch3d/common/datatypes.py
View File

@@ -4,7 +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.
import sys
# 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

2
pytorch3d/csrc/iou_box3d/iou_box3d.cu
View File

@@ -12,8 +12,6 @@
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <thrust/device_vector.h>
#include <thrust/tuple.h>
#include "iou_box3d/iou_utils.cuh"
// Parallelize over N*M computations which can each be done

1
pytorch3d/csrc/iou_box3d/iou_utils.cuh
View File

@@ -8,7 +8,6 @@
#include <float.h>
#include <math.h>
#include <thrust/device_vector.h>
#include <cstdio>
#include "utils/float_math.cuh"

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;

94
pytorch3d/csrc/marching_cubes/marching_cubes.cu
View File

@@ -9,8 +9,6 @@
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <c10/cuda/CUDAGuard.h>
#include <thrust/device_vector.h>
#include <thrust/scan.h>
#include <cstdio>
#include "marching_cubes/tables.h"
@@ -40,20 +38,6 @@ through" each cube in the grid.
// EPS: Used to indicate if two float values are close
__constant__ const float EPSILON = 1e-5;
// Thrust wrapper for exclusive scan
//
// Args:
// output: pointer to on-device output array
// input: pointer to on-device input array, where scan is performed
// numElements: number of elements for the input array
//
void ThrustScanWrapper(int* output, int* input, int numElements) {
thrust::exclusive_scan(
thrust::device_ptr<int>(input),
thrust::device_ptr<int>(input + numElements),
thrust::device_ptr<int>(output));
}
// Linearly interpolate the position where an isosurface cuts an edge
// between two vertices, based on their scalar values
//
@@ -239,7 +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;
@@ -271,7 +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,
@@ -397,6 +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
@@ -455,6 +478,9 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
grid.x = 65535;
}
using at::indexing::None;
using at::indexing::Slice;
auto d_voxelVerts =
at::zeros({numVoxels}, at::TensorOptions().dtype(at::kInt))
.to(vol.device());
@@ -477,18 +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.
int64_t activeVoxels = 0;
auto d_voxelOccupiedScan =
at::zeros({numVoxels}, at::TensorOptions().dtype(at::kInt))
.to(vol.device());
ThrustScanWrapper(
d_voxelOccupiedScan.data_ptr<int>(),
d_voxelOccupied.data_ptr<int>(),
numVoxels);
// number of active voxels
int lastElement = d_voxelVerts[numVoxels - 1].cpu().item<int>();
int lastScan = d_voxelOccupiedScan[numVoxels - 1].cpu().item<int>();
int activeVoxels = lastElement + lastScan;
ExclusiveScanAndTotal(d_voxelOccupied, &activeVoxels);
const int device_id = vol.device().index();
auto opt = at::TensorOptions().dtype(at::kInt).device(at::kCUDA, device_id);
@@ -503,28 +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::zeros({numVoxels}, opt);
ThrustScanWrapper(
d_voxelVertsScan.data_ptr<int>(),
d_voxelVerts.data_ptr<int>(),
numVoxels);
// total number of vertices
lastElement = d_voxelVerts[numVoxels - 1].cpu().item<int>();
lastScan = d_voxelVertsScan[numVoxels - 1].cpu().item<int>();
int totalVerts = lastElement + lastScan;
int64_t totalVerts = 0;
auto d_voxelVertsScan = ExclusiveScanAndTotal(d_voxelVerts, &totalVerts);
// Execute "GenerateFacesKernel" kernel
// This runs only on the occupied voxels.
@@ -544,7 +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.forward.device.h
View File

@@ -102,6 +102,7 @@ void forward(
self->workspace_d,
self->workspace_size,
stream);
CHECKLAUNCH();
SORT_ASCENDING_WS(
self->min_depth_d,
self->min_depth_sorted_d,
@@ -111,6 +112,7 @@ void forward(
self->workspace_d,
self->workspace_size,
stream);
CHECKLAUNCH();
SORT_ASCENDING_WS(
self->min_depth_d,
self->min_depth_sorted_d,

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) {

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

@@ -37,7 +37,7 @@ inline void fill_cam_vecs(
res->pixel_dir_y.x = pixel_dir_y.data_ptr<float>()[0];
res->pixel_dir_y.y = pixel_dir_y.data_ptr<float>()[1];
res->pixel_dir_y.z = pixel_dir_y.data_ptr<float>()[2];
auto sensor_dir_z = pixel_dir_y.cross(pixel_dir_x);
auto sensor_dir_z = pixel_dir_y.cross(pixel_dir_x, -1);
sensor_dir_z /= sensor_dir_z.norm();
if (right_handed) {
sensor_dir_z *= -1.f;

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/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

12
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 (
@@ -72,6 +74,16 @@ class ImplicitronDataSource(DataSourceBase): # pyre-ignore[13]
from .rendered_mesh_dataset_map_provider import ( # noqa: F401
RenderedMeshDatasetMapProvider,
)
from .train_eval_data_loader_provider import ( # noqa: F401
TrainEvalDataLoaderMapProvider,
)
try:
from .sql_dataset_provider import ( # noqa: F401 # pyre-ignore
SqlIndexDatasetMapProvider,
)
except ModuleNotFoundError:
pass # environment without SQL dataset
finally:
pass

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

101
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
@@ -203,7 +205,10 @@ class FrameData(Mapping[str, Any]):
when no image has been loaded)
"""
if self.bbox_xywh is None:
raise ValueError("Attempted cropping by metadata with empty bounding box")
raise ValueError(
"Attempted cropping by metadata with empty bounding box. Consider either"
" to remove_empty_masks or turn off box_crop in the dataset config."
)
if not self._uncropped:
raise ValueError(
@@ -528,12 +533,7 @@ class GenericFrameDataBuilder(FrameDataBuilderBase[FrameDataSubtype], ABC):
"Make sure it is set in either FrameDataBuilder or Dataset params."
)
if self.path_manager is None:
dataset_root_exists = os.path.isdir(self.dataset_root) # pyre-ignore
else:
dataset_root_exists = self.path_manager.isdir(self.dataset_root)
if load_any_blob and not dataset_root_exists:
if load_any_blob and not self._exists_in_dataset_root(""):
raise ValueError(
f"dataset_root is passed but {self.dataset_root} does not exist."
)
@@ -578,16 +578,16 @@ 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
mask_annotation = frame_annotation.mask
if mask_annotation is not None:
fg_mask_np: Optional[np.ndarray] = None
if load_blobs and self.load_masks:
fg_mask_np, mask_path = self._load_fg_probability(frame_annotation)
frame_data.mask_path = mask_path
@@ -604,19 +604,32 @@ class GenericFrameDataBuilder(FrameDataBuilderBase[FrameDataSubtype], ABC):
frame_data.image_size_hw = image_size_hw # original image size
# image size after crop/resize
frame_data.effective_image_size_hw = image_size_hw
image_path = None
dataset_root = self.dataset_root
if frame_annotation.image.path is not None and dataset_root is not None:
image_path = os.path.join(dataset_root, frame_annotation.image.path)
frame_data.image_path = image_path
if load_blobs and self.load_images:
(
frame_data.image_rgb,
frame_data.image_path,
) = self._load_images(frame_annotation, frame_data.fg_probability)
if image_path is None:
raise ValueError("Image path is required to load images.")
if load_blobs and self.load_depths and frame_annotation.depth is not None:
image_np = load_image(self._local_path(image_path))
frame_data.image_rgb = self._postprocess_image(
image_np, frame_annotation.image.size, frame_data.fg_probability
)
if (
load_blobs
and self.load_depths
and frame_annotation.depth is not None
and frame_annotation.depth.path is not None
):
(
frame_data.depth_map,
frame_data.depth_path,
frame_data.depth_mask,
) = self._load_mask_depth(frame_annotation, frame_data.fg_probability)
) = self._load_mask_depth(frame_annotation, fg_mask_np)
if load_blobs and self.load_point_clouds and point_cloud is not None:
pcl_path = self._fix_point_cloud_path(point_cloud.path)
@@ -652,47 +665,45 @@ class GenericFrameDataBuilder(FrameDataBuilderBase[FrameDataSubtype], ABC):
return fg_probability, full_path
def _load_images(
def _postprocess_image(
self,
entry: types.FrameAnnotation,
image_np: np.ndarray,
image_size: Tuple[int, int],
fg_probability: Optional[torch.Tensor],
) -> Tuple[torch.Tensor, str]:
assert self.dataset_root is not None and entry.image is not None
path = os.path.join(self.dataset_root, entry.image.path)
image_rgb = load_image(self._local_path(path))
) -> torch.Tensor:
image_rgb = safe_as_tensor(image_np, torch.float)
if image_rgb.shape[-2:] != entry.image.size:
raise ValueError(
f"bad image size: {image_rgb.shape[-2:]} vs {entry.image.size}!"
)
if image_rgb.shape[-2:] != image_size:
raise ValueError(f"bad image size: {image_rgb.shape[-2:]} vs {image_size}!")
if self.mask_images:
assert fg_probability is not None
image_rgb *= fg_probability
return image_rgb, path
return image_rgb
def _load_mask_depth(
self,
entry: types.FrameAnnotation,
fg_probability: Optional[torch.Tensor],
fg_mask: Optional[np.ndarray],
) -> Tuple[torch.Tensor, str, torch.Tensor]:
entry_depth = entry.depth
assert self.dataset_root is not None and entry_depth is not None
path = os.path.join(self.dataset_root, entry_depth.path)
dataset_root = self.dataset_root
assert dataset_root is not None
assert entry_depth is not None and entry_depth.path is not None
path = os.path.join(dataset_root, entry_depth.path)
depth_map = load_depth(self._local_path(path), entry_depth.scale_adjustment)
if self.mask_depths:
assert fg_probability is not None
depth_map *= fg_probability
assert fg_mask is not None
depth_map *= fg_mask
if self.load_depth_masks:
assert entry_depth.mask_path is not None
# pyre-ignore
mask_path = os.path.join(self.dataset_root, entry_depth.mask_path)
mask_path = entry_depth.mask_path
if self.load_depth_masks and mask_path is not None:
mask_path = os.path.join(dataset_root, mask_path)
depth_mask = load_depth_mask(self._local_path(mask_path))
else:
depth_mask = torch.ones_like(depth_map)
depth_mask = (depth_map > 0.0).astype(np.float32)
return torch.tensor(depth_map), path, torch.tensor(depth_mask)
@@ -745,6 +756,16 @@ class GenericFrameDataBuilder(FrameDataBuilderBase[FrameDataSubtype], ABC):
return path
return self.path_manager.get_local_path(path)
def _exists_in_dataset_root(self, relpath) -> bool:
if not self.dataset_root:
return False
full_path = os.path.join(self.dataset_root, relpath)
if self.path_manager is None:
return os.path.exists(full_path)
else:
return self.path_manager.exists(full_path)
@registry.register
class FrameDataBuilder(GenericWorkaround, GenericFrameDataBuilder[FrameData]):

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 = ""

2
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

2
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

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()

32
pytorch3d/implicitron/dataset/orm_types.py
View File

@@ -33,7 +33,35 @@ from sqlalchemy.types import TypeDecorator
# these produce policies to serialize structured types to blobs
def ArrayTypeFactory(shape):
def ArrayTypeFactory(shape=None):
if shape is None:
class VariableShapeNumpyArrayType(TypeDecorator):
impl = LargeBinary
def process_bind_param(self, value, dialect):
if value is None:
return None
ndim_bytes = np.int32(value.ndim).tobytes()
shape_bytes = np.array(value.shape, dtype=np.int64).tobytes()
value_bytes = value.astype(np.float32).tobytes()
return ndim_bytes + shape_bytes + value_bytes
def process_result_value(self, value, dialect):
if value is None:
return None
ndim = np.frombuffer(value[:4], dtype=np.int32)[0]
value_start = 4 + 8 * ndim
shape = np.frombuffer(value[4:value_start], dtype=np.int64)
assert shape.shape == (ndim,)
return np.frombuffer(value[value_start:], dtype=np.float32).reshape(
shape
)
return VariableShapeNumpyArrayType
class NumpyArrayType(TypeDecorator):
impl = LargeBinary
@@ -158,4 +186,4 @@ class SqlSequenceAnnotation(Base):
mapped_column("_point_cloud_n_points", nullable=True),
)
# the bigger the better
viewpoint_quality_score: Mapped[Optional[float]] = mapped_column(default=None)
viewpoint_quality_score: Mapped[Optional[float]] = mapped_column()

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

@@ -4,15 +4,13 @@
# 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
import torch
from pytorch3d.implicitron.tools.config import (
expand_args_fields,
registry,
run_auto_creation,
)
from pytorch3d.implicitron.tools.config import registry, run_auto_creation
from pytorch3d.io import IO
from pytorch3d.renderer import (
AmbientLights,

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

11
pytorch3d/implicitron/dataset/single_sequence_dataset.py
View File

@@ -4,12 +4,14 @@
# 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.
from dataclasses import field
from typing import Iterable, Iterator, List, Optional, Tuple
from typing import Iterable, Iterator, List, Optional, Sequence, Tuple
import numpy as np
import torch
@@ -47,13 +49,12 @@ class SingleSceneDataset(DatasetBase, Configurable):
def __len__(self) -> int:
return len(self.poses)
# pyre-fixme[14]: `sequence_frames_in_order` overrides method defined in
# `DatasetBase` inconsistently.
def sequence_frames_in_order(
self, seq_name: str
self, seq_name: str, subset_filter: Optional[Sequence[str]] = None
) -> Iterator[Tuple[float, int, int]]:
for i in range(len(self)):
yield (0.0, i, i)
if subset_filter is None or self.frame_types[i] in subset_filter:
yield 0.0, i, i
def __getitem__(self, index) -> FrameData:
if index >= len(self):

48
pytorch3d/implicitron/dataset/sql_dataset.py
View File

@@ -89,6 +89,9 @@ class SqlIndexDataset(DatasetBase, ReplaceableBase): # pyre-ignore
pick_categories: Restrict the dataset to the given list of categories.
pick_sequences: A Sequence of sequence names to restrict the dataset to.
exclude_sequences: A Sequence of the names of the sequences to exclude.
limit_sequences_per_category_to: Limit the dataset to the first up to N
sequences within each category (applies after all other sequence filters
but before `limit_sequences_to`).
limit_sequences_to: Limit the dataset to the first `limit_sequences_to`
sequences (after other sequence filters have been applied but before
frame-based filters).
@@ -115,6 +118,7 @@ class SqlIndexDataset(DatasetBase, ReplaceableBase): # pyre-ignore
pick_sequences: Tuple[str, ...] = ()
exclude_sequences: Tuple[str, ...] = ()
limit_sequences_per_category_to: int = 0
limit_sequences_to: int = 0
limit_to: int = 0
n_frames_per_sequence: int = -1
@@ -142,8 +146,10 @@ class SqlIndexDataset(DatasetBase, ReplaceableBase): # pyre-ignore
run_auto_creation(self)
self.frame_data_builder.path_manager = self.path_manager
# pyre-ignore
self._sql_engine = sa.create_engine(f"sqlite:///{self.sqlite_metadata_file}")
# pyre-ignore # NOTE: sqlite-specific args (read-only mode).
self._sql_engine = sa.create_engine(
f"sqlite:///file:{self.sqlite_metadata_file}?mode=ro&uri=true"
)
sequences = self._get_filtered_sequences_if_any()
@@ -210,6 +216,9 @@ class SqlIndexDataset(DatasetBase, ReplaceableBase): # pyre-ignore
seq, frame = self._index.index[frame_idx]
else:
seq, frame, *rest = frame_idx
if isinstance(frame, torch.LongTensor):
frame = frame.item()
if (seq, frame) not in self._index.index:
raise IndexError(
f"Sequence-frame index {frame_idx} not found; was it filtered out?"
@@ -368,6 +377,7 @@ class SqlIndexDataset(DatasetBase, ReplaceableBase): # pyre-ignore
self.remove_empty_masks
or self.limit_to > 0
or self.limit_sequences_to > 0
or self.limit_sequences_per_category_to > 0
or len(self.pick_sequences) > 0
or len(self.exclude_sequences) > 0
or len(self.pick_categories) > 0
@@ -375,20 +385,38 @@ class SqlIndexDataset(DatasetBase, ReplaceableBase): # pyre-ignore
)
def _get_filtered_sequences_if_any(self) -> Optional[pd.Series]:
# maximum possible query: WHERE category IN 'self.pick_categories'
# maximum possible filter (if limit_sequences_per_category_to == 0):
# WHERE category IN 'self.pick_categories'
# AND sequence_name IN 'self.pick_sequences'
# AND sequence_name NOT IN 'self.exclude_sequences'
# LIMIT 'self.limit_sequence_to'
stmt = sa.select(SqlSequenceAnnotation.sequence_name)
where_conditions = [
*self._get_category_filters(),
*self._get_pick_filters(),
*self._get_exclude_filters(),
]
if where_conditions:
stmt = stmt.where(*where_conditions)
def add_where(stmt):
return stmt.where(*where_conditions) if where_conditions else stmt
if self.limit_sequences_per_category_to <= 0:
stmt = add_where(sa.select(SqlSequenceAnnotation.sequence_name))
else:
subquery = sa.select(
SqlSequenceAnnotation.sequence_name,
sa.func.row_number()
.over(
order_by=sa.text("ROWID"), # NOTE: ROWID is SQLite-specific
partition_by=SqlSequenceAnnotation.category,
)
.label("row_number"),
)
subquery = add_where(subquery).subquery()
stmt = sa.select(subquery.c.sequence_name).where(
subquery.c.row_number <= self.limit_sequences_per_category_to
)
if self.limit_sequences_to > 0:
logger.info(
@@ -397,7 +425,11 @@ class SqlIndexDataset(DatasetBase, ReplaceableBase): # pyre-ignore
# NOTE: ROWID is SQLite-specific
stmt = stmt.order_by(sa.text("ROWID")).limit(self.limit_sequences_to)
if not where_conditions and self.limit_sequences_to <= 0:
if (
not where_conditions
and self.limit_sequences_to <= 0
and self.limit_sequences_per_category_to <= 0
):
# we will not need to filter by sequences
return 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

39
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:
@@ -225,26 +227,41 @@ def resize_image(
return imre_, minscale, mask
def transpose_normalize_image(image: np.ndarray) -> np.ndarray:
im = np.atleast_3d(image).transpose((2, 0, 1))
return im.astype(np.float32) / 255.0
def load_image(path: str) -> np.ndarray:
with Image.open(path) as pil_im:
im = np.array(pil_im.convert("RGB"))
im = im.transpose((2, 0, 1))
im = im.astype(np.float32) / 255.0
return im
return transpose_normalize_image(im)
def load_mask(path: str) -> np.ndarray:
with Image.open(path) as pil_im:
mask = np.array(pil_im)
mask = mask.astype(np.float32) / 255.0
return mask[None] # fake feature channel
return transpose_normalize_image(mask)
def load_depth(path: str, scale_adjustment: float) -> np.ndarray:
if not path.lower().endswith(".png"):
if path.lower().endswith(".exr"):
# NOTE: environment variable OPENCV_IO_ENABLE_OPENEXR must be set to 1
# You will have to accept these vulnerabilities by using OpenEXR:
# https://github.com/opencv/opencv/issues/21326
import cv2
d = cv2.imread(path, cv2.IMREAD_ANYCOLOR | cv2.IMREAD_ANYDEPTH)[..., 0]
d[d > 1e9] = 0.0
elif path.lower().endswith(".png"):
d = load_16big_png_depth(path)
else:
raise ValueError('unsupported depth file name "%s"' % path)
d = load_16big_png_depth(path) * scale_adjustment
d = d * scale_adjustment
d[~np.isfinite(d)] = 0.0
return d[None] # fake feature channel
@@ -312,7 +329,7 @@ def adjust_camera_to_bbox_crop_(
focal_length_px, principal_point_px = _convert_ndc_to_pixels(
camera.focal_length[0],
camera.principal_point[0], # pyre-ignore
camera.principal_point[0],
image_size_wh,
)
principal_point_px_cropped = principal_point_px - clamp_bbox_xywh[:2]
@@ -324,7 +341,7 @@ def adjust_camera_to_bbox_crop_(
)
camera.focal_length = focal_length[None]
camera.principal_point = principal_point_cropped[None] # pyre-ignore
camera.principal_point = principal_point_cropped[None]
def adjust_camera_to_image_scale_(
@@ -334,7 +351,7 @@ def adjust_camera_to_image_scale_(
) -> PerspectiveCameras:
focal_length_px, principal_point_px = _convert_ndc_to_pixels(
camera.focal_length[0],
camera.principal_point[0], # pyre-ignore
camera.principal_point[0],
original_size_wh,
)

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

10
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,
)
@@ -339,6 +341,8 @@ def eval_batch(
):
results[rgb_metric_name] = rgb_metric_fun(
image_render,
# pyre-fixme[6]: For 2nd argument expected `Tensor` but got
# `Optional[Tensor]`.
image_rgb,
mask=mask_crop,
)

4
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
@@ -14,8 +16,6 @@ from typing import Any, Dict, List, Optional, Tuple
import torch
import tqdm
from pytorch3d.implicitron.dataset import utils as ds_utils
from pytorch3d.implicitron.evaluation import evaluate_new_view_synthesis as evaluate
from pytorch3d.implicitron.models.base_model import EvaluationMode, ImplicitronModelBase
from pytorch3d.implicitron.tools.config import (

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

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