Summary: Update PyTorch3D version number

Differential Revision: D35980555

fbshipit-source-id: 637ccd33eef22d909985d2fce3958c78f3d0d551

Summary: Updates for version 0.6.2

Differential Revision: D35980557

fbshipit-source-id: e677a22d4f8a323376310dfb536133bee8045f1f

Summary: colab is now 1.11.0

Differential Revision: D35980556

fbshipit-source-id: 988a06c652518fb61ccbef2e7197e3422a706250

Summary: Updated to FoV cameras and added perspective_correct=False, otherwise it'll nan out.

Reviewed By: bottler

Differential Revision: D35970900

fbshipit-source-id: 569b8de0b124d415f4b841924ddc85585cee2dda

Summary: Most of the shaders copypaste exactly the same code into `__init__` and `to`. I will be adding a new shader in the next diff, so let's make it a bit easier.

Reviewed By: bottler

Differential Revision: D35767884

fbshipit-source-id: 0057e3e2ae3be4eaa49ae7e2bf3e4176953dde9d

Summary: Move from isort to usort now that usort supports sorting within lines.

Reviewed By: patricklabatut

Differential Revision: D35893280

fbshipit-source-id: 621c1cd285199d785408504430ee0bdf8683b21e

Summary: New function to check if a renderer needs the object mask.

Reviewed By: davnov134

Differential Revision: D35254009

fbshipit-source-id: 4c99e8a1c0f6641d910eb32bfd6cfae9d3463d50

Summary: Make method for SDF's use of object mask more general, so that a renderer can be given per-pixel values.

Reviewed By: shapovalov

Differential Revision: D35247412

fbshipit-source-id: 6aeccb1d0b5f1265a3f692a1453407a07e51a33c

Summary: For `pip install` without -e, we need to name the entry point functions in setup.py.

Reviewed By: patricklabatut

Differential Revision: D35933037

fbshipit-source-id: be15ae1a4bb7c5305ea2ba992d07f3279c452250

Summary: Repo has jpgs but docs/website want pngs.

Reviewed By: nikhilaravi

Differential Revision: D35596475

fbshipit-source-id: 4cafd405c06c0eb339001a8db2422dbbd1f8f28a

Summary:
Applies new import merging and sorting from µsort v1.0.

When merging imports, µsort will make a best-effort to move associated
comments to match merged elements, but there are known limitations due to
the diynamic nature of Python and developer tooling. These changes should
not produce any dangerous runtime changes, but may require touch-ups to
satisfy linters and other tooling.

Note that µsort uses case-insensitive, lexicographical sorting, which
results in a different ordering compared to isort. This provides a more
consistent sorting order, matching the case-insensitive order used when
sorting import statements by module name, and ensures that "frog", "FROG",
and "Frog" always sort next to each other.

For details on µsort's sorting and merging semantics, see the user guide:
https://usort.readthedocs.io/en/stable/guide.html#sorting

Reviewed By: bottler

Differential Revision: D35553814

fbshipit-source-id: be49bdb6a4c25264ff8d4db3a601f18736d17be1

Summary: D35513897 (https://github.com/facebookresearch/pytorch3d/commit/4b94649f7b7de4ce3a0597c5a17a7596928ad20b) was a pyre infer job which got some things wrong. Correct by adding the correct types, so these things shouldn't need worrying about again.

Reviewed By: patricklabatut

Differential Revision: D35546144

fbshipit-source-id: 89f6ea2b67be27aa0b0b14afff4347cccf23feb7

Summary: Add option to not rescale the features, giving more control. https://github.com/facebookresearch/pytorch3d/issues/1137

Reviewed By: nikhilaravi

Differential Revision: D35219577

fbshipit-source-id: cbbb643b91b71bc908cedc6dac0f63f6d1355c85

Summary:
Hello, I'm Seungoh from South Korea.

I'm finding typo while I'm learning tutorials.
Wrong numbers are changed to right numbers.

Thank you.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1163

Reviewed By: patricklabatut

Differential Revision: D35546843

Pulled By: bottler

fbshipit-source-id: b6e70cdf821fd4a108dfd416e8f4bcb3ecbeb449

Differential Revision: D35590813

fbshipit-source-id: 0f35d7193f839a41f3cac18bf20236b815368f19

Summary: In order to simplify the interface, we disallow passing None as vertex/face lists to textures.submeshes. This function would only ever get called from within meshes.submeshes where we can provide both arguments, even if they're not necessary for a specific submesh type.

Reviewed By: bottler

Differential Revision: D35581161

fbshipit-source-id: aeab99308a319b144e141ca85ca7515f855116da

Summary: Add submeshing capability for meshes with TexturesVertex.

Reviewed By: bottler

Differential Revision: D35448534

fbshipit-source-id: 6d16a31a5bfb24ce122cf3c300a7616bc58353d1

Summary:
Copypasting the docstring:
```
        Split a mesh into submeshes, defined by face indices of the original Meshes object.

        Args:
          face_indices:
            Let the original mesh have verts_list() of length N.
            Can be either
              - List of length N. The n-th element is a list of length num_submeshes_n
                (empty lists are allowed). Each element of the n-th sublist is a LongTensor
                of length num_faces.
              - List of length N. The n-th element is a possibly empty padded LongTensor of
                shape (num_submeshes_n, max_num_faces).

        Returns:
          Meshes object with selected submeshes. The submesh tensors are cloned.

        Currently submeshing only works with no textures or with the TexturesVertex texture.

        Example:

        Take a Meshes object `cubes` with 4 meshes, each a translated cube. Then:
            * len(cubes) is 4, len(cubes.verts_list()) is 4, len(cubes.faces_list()) is 4,
            * [cube_verts.size for cube_verts in cubes.verts_list()] is [8, 8, 8, 8],
            * [cube_faces.size for cube_faces in cubes.faces_list()] if [6, 6, 6, 6],

        Now let front_facet, top_and_bottom, all_facets be LongTensors of
        sizes (2), (4), and (12), each picking up a number of facets of a cube by specifying
        the appropriate triangular faces.

        Then let `subcubes = cubes.submeshes([[front_facet, top_and_bottom], [], [all_facets], []])`.
            * len(subcubes) is 3.
            * subcubes[0] is the front facet of the cube contained in cubes[0].
            * subcubes[1] is a mesh containing the (disconnected) top and bottom facets of cubes[0].
            * subcubes[2] is a clone of cubes[2].
            * There are no submeshes of cubes[1] and cubes[3] in subcubes.
            * subcubes[0] and subcubes[1] are not watertight. subcubes[2] is.
```

Reviewed By: bottler

Differential Revision: D35440657

fbshipit-source-id: 8a6d2d300ce226b5b9eb440688528b5e795195a1

Summary:
Sort a mesh's vertices in alphabetical order, and resort the face coords accordingly. Textured meshes are not supported yet, but will be added down the stack.

This, togehter with mesh equality, can be used to compare two meshes in a way invariant to vertex permutations, as shown in the unit tests.

We do not want the submeshing mechanism to guarantee any particular vertex order, leaving that up to the implementation, so we need this function for testing.

Reviewed By: bottler

Differential Revision: D35440656

fbshipit-source-id: 5a4dd921fdb00625a33da08b5fea79e20ac6402c

Summary: Adding a mesh equality operator. Two Meshes objects m1, m2 are equal iff their vertex lists, face lists, and normals lists are equal. Textures meshes are not supported yet, but will be added for vertex textures down the stack.

Reviewed By: bottler, nikhilaravi

Differential Revision: D35440655

fbshipit-source-id: 69974a59c091416afdb2892896859a189f5ebf3a

Summary:
The default behavior of Meshes (with verts=None, faces=None) throws an exception:
```
meshes = Meshes()
> ValueError: Verts and Faces must be either a list or a tensor with shape (batch_size, N, 3) where N is either the maximum number of verts or faces respectively.
```

Instead, let's default to an empty mesh, following e.g. PyTorch:
```
empty_tensor = torch.FloatTensor()
> torch.tensor([])
```

this change is backwards-compatible (you can still init with verts=[], faces=[]).

Reviewed By: bottler, nikhilaravi

Differential Revision: D35443453

fbshipit-source-id: d638a8fef49a089bf0da6dd2201727b94ceb21ec

Summary:
Added L1 norm for KNN and chamfer op
* The norm is now specified with a variable `norm` which can only be 1 or 2

Reviewed By: bottler

Differential Revision: D35419637

fbshipit-source-id: 77813fec650b30c28342af90d5ed02c89133e136

Reviewed By: shannonzhu

Differential Revision: D35513897

fbshipit-source-id: 1ca12671df1bd6608a7dce9193c145d5985c0b45

Differential Revision: D35455033

fbshipit-source-id: c4fe9577edd7beb9c40be1cb387f125d53a6a577

Summary: A new type of auto-expanded member of a Configurable: something of type Optional[X] where X is a Configurable. This works like X but its construction is controlled by a boolean membername_enabled.

Reviewed By: davnov134

Differential Revision: D35368269

fbshipit-source-id: 7e0c8a3e8c4930b0aa942fa1b325ce65336ebd5f

Summary:
Try again to solve https://github.com/facebookresearch/pytorch3d/issues/1144 pickling problem.
D35258561 (https://github.com/facebookresearch/pytorch3d/commit/24260130ce382640a89e978cd671298488ec6451) didn't work.

When writing a function or vanilla class C which you want people to be able to call get_default_args on, you must add the line enable_get_default_args(C) to it. This causes autogeneration of a hidden dataclass in the module.

Reviewed By: davnov134

Differential Revision: D35364410

fbshipit-source-id: 53f6e6fff43e7142ae18ca3b06de7d0c849ef965

Summary:
Error Reproduction:

python=3.8.12
pytorch=1.9.1
pytorch3d=0.6.1
cudatoolkit=11.1.74

test.py:
```python
import torch
from pytorch3d.ops import cubify
voxels = torch.Tensor([[[[0,1], [0,0]], [[0,1], [0,0]]]]).float()
meshes = cubify(voxels, 0.5, device="cpu")
```

The error appears when `device="cpu"` and `pytorch=1.9.1` (works fine with pytorch=1.10.2)

Error message:
```console
/home/kyle/anaconda3/envs/adapt-net/lib/python3.8/site-packages/torch/_tensor.py:575: UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values.
To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at  /opt/conda/conda-bld/pytorch_1631630839582/work/aten/src/ATen/native/BinaryOps.cpp:467.)
  return torch.floor_divide(self, other)
Traceback (most recent call last):
  File "test.py", line 5, in <module>
    meshes = cubify(voxels, 0.5, device="cpu")
  File "/home/kyle/anaconda3/envs/adapt-net/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
    return func(*args, **kwargs)
  File "/home/kyle/Desktop/pytorch3d/pytorch3d/ops/cubify.py", line 227, in cubify
    idleverts.scatter_(0, grid_faces.flatten(), 0)
RuntimeError: Expected index [60] to be smaller than self [27] apart from dimension 0 and to be smaller size than src [27]
```

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1067

Reviewed By: nikhilaravi

Differential Revision: D34893567

Pulled By: bottler

fbshipit-source-id: aa95980f7319302044141f7821ef48129cfa37a6

Summary: This is required to suppress a huge stdout full of warnings about overflown bins.

Reviewed By: bottler

Differential Revision: D35359824

fbshipit-source-id: 39214b1bdcb4a5d5debf8ed498b2ca81fa43d210

Summary: Aid reflection by adding the original declared types of replaced members of a configurable as values in _processed_members.

Reviewed By: davnov134

Differential Revision: D35358422

fbshipit-source-id: 80ef3266144c51c1c2105f349e0dd3464e230429

Summary: Use logging instead of printing in the internals of implicitron.

Reviewed By: davnov134

Differential Revision: D35247581

fbshipit-source-id: be5ddad5efe1409adbae0575d35ade6112b3be63

Summary: This might make the implicitron tests work better on RE.

Reviewed By: davnov134

Differential Revision: D35283131

fbshipit-source-id: 4dda9684f632ab6e9cebcbf1e6e4a8243ec00c85

Summary: Optional[not_a_type] was causing errors.

Reviewed By: davnov134

Differential Revision: D35355530

fbshipit-source-id: e9b52cfd6347ffae0fe688ef30523a4092ccf9fd

Summary: Pyre expects Mapping for ** operator.

Reviewed By: bottler

Differential Revision: D35288632

fbshipit-source-id: 34d6f26ad912b3a5046f440922bb6ed2fd86f533

Summary:
ListConfig and DictConfig members of get_default_args(X) when X is a callable will contain references to a temporary dataclass and therefore be unpicklable. Avoid this in a few cases.

Fixes https://github.com/facebookresearch/pytorch3d/issues/1144

Reviewed By: shapovalov

Differential Revision: D35258561

fbshipit-source-id: e52186825f52accee9a899e466967a4ff71b3d25

Summary: as subj

Reviewed By: davnov134

Differential Revision: D35194863

fbshipit-source-id: c8e8f234083d4f0f93dca8d93e090ca0e1e1972d

Summary:
Previously, dtypes were not propagated correctly in composed transforms, resulting in errors when different dtypes were mixed. Even specifying a dtype in the constructor does not fix this. Neither does specifying the dtype for each composition function invocation (e.g. as a `kwarg` in `rotate_axis_angle`).

With the change, I also had to modify the default dtype of `RotateAxisAngle`, which was `torch.float64`; it is now `torch.float32` like for all other transforms. This was required because the fix in propagation broke some tests due to dtype mismatches.

This change in default dtype in turn broke two tests due to precision changes (calculations that were previously done in `torch.float64` were now done in `torch.float32`), so I changed the precision tolerances to be less strict. I chose the lowest power of ten that passed the tests here.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1141

Reviewed By: patricklabatut

Differential Revision: D35192970

Pulled By: bottler

fbshipit-source-id: ba0293e8b3595dfc94b3cf8048e50b7a5e5ed7cf

Summary: Allow things like `renderer:Optional[BaseRenderer]` in configurables.

Reviewed By: davnov134

Differential Revision: D35118339

fbshipit-source-id: 1219321b2817ed4b26fe924c6d6f73887095c985

Summary: To ensure that tests outside implicitron/ don't use implicitron, split the test for recursive includes in to two. License header checking is not needed here any more.

Reviewed By: shapovalov

Differential Revision: D35077830

fbshipit-source-id: 2ebe7436a6dcc5d21a116434f6ddd08705dfab34

Summary: Enable `pytorch3d_implicitron_runner` executable

Reviewed By: shapovalov

Differential Revision: D34754902

fbshipit-source-id: 213f3e9183e3f7dd7b4df16ad77d95fbc971d625

Summary: Attempt to solve an internal issue

Reviewed By: shapovalov

Differential Revision: D35143263

fbshipit-source-id: b4fd9ee441d85f0a3ee08f2f1e7febd1c1ccbe86