GitLab

Summary:
Similar to non square image rasterization for meshes, apply the same updates to the pointcloud rasterizer.

Main API Change:
- PointRasterizationSettings now accepts a tuple/list of (H, W) for the image size.

Reviewed By: jcjohnson

Differential Revision: D25465206

fbshipit-source-id: 7370d83c431af1b972158cecae19d82364623380

Summary:
Fix division by zero when alpha is 1.0
In this case, the nominator is already 0 and we need to make sure division with 0 does not occur which would produce nans

Reviewed By: nikhilaravi

Differential Revision: D21650478

fbshipit-source-id: bc457105b3050fef1c8bd4e58e7d6d15c0c81ffd

Summary:
Update the cuda kernels to:
- remove contiguous checks for the grad tensors and for cpu functions which use accessors
- for cuda implementations call `.contiguous()` on all tensors in the host function before invoking the kernel

Reviewed By: gkioxari

Differential Revision: D21598008

fbshipit-source-id: 9b97bda4582fd4269c8a00999874d4552a1aea2d

Summary:
Updates to:
- enable cuda kernel launches on any GPU (not just the default)
- cuda and contiguous checks for all kernels
- checks to ensure all tensors are on the same device
- error reporting in the cuda kernels
- cuda tests now run on a random device not just the default

Reviewed By: jcjohnson, gkioxari

Differential Revision: D21215280

fbshipit-source-id: 1bedc9fe6c35e9e920bdc4d78ed12865b1005519

Summary:
Use aten instead of torch interface in all cuda code. This allows the cuda build to work with pytorch 1.5 with GCC 5 (e.g. the compiler of ubuntu 16.04LTS). This wasn't working. It has been failing with errors like the below, perhaps due to a bug in nvcc.

```
torch/include/torch/csrc/api/include/torch/nn/cloneable.h:68:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >
```

Reviewed By: nikhilaravi

Differential Revision: D21204029

fbshipit-source-id: ca6bdbcecf42493365e1c23a33fe35e1759fe8b6

Summary: This is mostly replacing the old PackedTensorAccessor with the new PackedTensorAccessor64.

Reviewed By: gkioxari

Differential Revision: D21088773

fbshipit-source-id: 5973e5a29d934eafb7c70ec5ec154ca076b64d27

Summary:
Code for accumulating points in the z-buffer in three ways:
1. weighted sum
2. normalised weighted sum
3. alpha compositing

Pull Request resolved: https://github.com/fairinternal/pytorch3d/pull/4

Reviewed By: nikhilaravi

Differential Revision: D20522422

Pulled By: gkioxari

fbshipit-source-id: 5023baa05f15e338f3821ef08f5552c2dcbfc06c