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

Summary:
Before the fix, running get_default_args(C: Callable) returns an unstructured DictConfig which causes Enums to be handled incorrectly. This is a fix.

WIP update: Currently tests still fail whenever a function signature contains an untyped argument: This needs to be somehow fixed.

Reviewed By: bottler

Differential Revision: D34932124

fbshipit-source-id: ecdc45c738633cfea5caa7480ba4f790ece931e8

Summary: Some directories in implicitron were missing __init__.py files.

Reviewed By: patricklabatut

Differential Revision: D35076364

fbshipit-source-id: f74442766efe8694fdd47954ac4882e7c4daac60

Summary: bin_size should be 0 not -1 for naive rasterization. See https://github.com/facebookresearch/pytorch3d/issues/1129

Reviewed By: patricklabatut

Differential Revision: D35077115

fbshipit-source-id: b81ff74f47c78429977802f7dcadfd1b96676f8c

Summary: Attempt to reduce nvcc trouble on windows by (1) avoiding flag for c++14 and (2) avoiding `torch/extension.h`, which introduces pybind11, in `.cu` files.

Reviewed By: patricklabatut

Differential Revision: D34969868

fbshipit-source-id: f3878d6a2ba9d644e87ae7b6377cb5008b4b6ce3

Summary: Using the API from D35012121 everywhere.

Reviewed By: bottler

Differential Revision: D35045870

fbshipit-source-id: dab112b5e04160334859bbe8fa2366344b6e0f70

Summary: We often want to iterate over frames in the sequence in temporal order. This diff provides the API to do that. `seq_to_idx` should probably be considered to have `protected` visibility.

Reviewed By: davnov134

Differential Revision: D35012121

fbshipit-source-id: 41896672ec35cd62f3ed4be3aa119efd33adada1

fbshipit-source-id: d20e2f3d7ae6ca8c4a1e72002c1be8d75217939d

fbshipit-source-id: 29b8a643c0218375bf90b9c1fb8853dedd0906fe

Co-authored-by: Jeremy Francis Reizenstein <bottler@users.noreply.github.com>

Summary:
Fixes required for MC rasterisation to work.
1) Wrong number of channels for background was used (derived from points dimensions, not features dimensions;
2) split of the results on the wrong dimension was done;
3) CORE CHANGE: blending in alpha compositor was assuming RGBA input.

Reviewed By: davnov134

Differential Revision: D34933673

fbshipit-source-id: a5cc9f201ea21e114639ab9e291a10888d495206

Summary: as subj

Reviewed By: davnov134

Differential Revision: D34758227

fbshipit-source-id: c22e7c4c6e69e9ef872b46c99ece901c58c23d71

Summary: Add builds for PyTorch 1.11.0.

Reviewed By: nikhilaravi

Differential Revision: D34861021

fbshipit-source-id: 1a1c46fac48719bc66c81872e65531a48ff538ed

Summary:
1. Fix https://github.com/facebookresearch/pytorch3d/issues/1115 Change the type annatations of three arguments in the initializer of `R2N2` class.
2. Fix https://github.com/facebookresearch/pytorch3d/issues/1118 Override two functions in `BlenderCamera` class reruired by subclassing `CamerasBase` class.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1124

Reviewed By: nikhilaravi

Differential Revision: D34890900

Pulled By: bottler

fbshipit-source-id: 65c385369a5964ecbb17ab28f279d5284614b487

Summary: Fix assumption that face indices are signed in the PLY file, as reported in #1104.

Reviewed By: nikhilaravi

Differential Revision: D34892598

fbshipit-source-id: a8b23bfac1357bdc11bbbf752098319142239804

Summary: Try to fix circleci again.

Reviewed By: nikhilaravi

Differential Revision: D34752188

fbshipit-source-id: 5966c585b61d77df1d8dd97c24383cf74dfb1fae