GitLab

Reviewed By: shapovalov

Differential Revision: D42545069

fbshipit-source-id: e25fb4049dcebd715df43bab3ce813ecb5f85abe

Summary: Optional[some_configurable] won't autogenerate the enabled flag

Reviewed By: shapovalov

Differential Revision: D41522104

fbshipit-source-id: 555ff6b343faf6f18aad2f92fbb7c341f5e991c6

Summary: Fix indexing of directions after filtering of points by scaffold.

Reviewed By: shapovalov

Differential Revision: D40853482

fbshipit-source-id: 9cfdb981e97cb82edcd27632c5848537ed2c6837

Summary:
Allows loading of multiple categories.
Multiple categories are provided in a comma-separated list of category names.

Reviewed By: bottler, shapovalov

Differential Revision: D40803297

fbshipit-source-id: 863938be3aa6ffefe9e563aede4a2e9e66aeeaa8

Reviewed By: shapovalov

Differential Revision: D40622304

fbshipit-source-id: 277515a55c46d9b8300058b439526539a7fe00a0

Summary:
Adds the ability to have different learning rates for different parts of the model. The trainable parts of the implicitron have a new member

       param_groups: dictionary where keys are names of individual parameters,
            or module’s members and values are the parameter group where the
            parameter/member will be sorted to. "self" key is used to denote the
            parameter group at the module level. Possible keys, including the "self" key
            do not have to be defined. By default all parameters are put into "default"
            parameter group and have the learning rate defined in the optimizer,
            it can be overriden at the:
                - module level with “self” key, all the parameters and child
                    module s parameters will be put to that parameter group
                - member level, which is the same as if the `param_groups` in that
                    member has key=“self” and value equal to that parameter group.
                    This is useful if members do not have `param_groups`, for
                    example torch.nn.Linear.
                - parameter level, parameter with the same name as the key
                    will be put to that parameter group.

And in the optimizer factory, parameters and their learning rates are recursively gathered.

Reviewed By: shapovalov

Differential Revision: D40145802

fbshipit-source-id: 631c02b8d79ee1c0eb4c31e6e42dbd3d2882078a

Summary:
Small config system fix. Allows get_default_args to work on an instance which has been created with a dict (instead of a DictConfig) as an args field. E.g.

```
gm = GenericModel(
        raysampler_AdaptiveRaySampler_args={"scene_extent": 4.0}
    )
    OmegaConf.structured(gm1)
```

Reviewed By: shapovalov

Differential Revision: D40341047

fbshipit-source-id: 587d0e8262e271df442a80858949a48e5d6db3df

Summary: Tensorf does relu or softmax after the density grid. This diff adds the ability to replicate that.

Reviewed By: bottler

Differential Revision: D40023228

fbshipit-source-id: 9f19868cd68460af98ab6e61c7f708158c26dc08

Summary:
TensoRF at step 2000 does volume croping and resizing.
At those steps it calculates part of the voxel grid which has density big enough to have objects and resizes the grid to fit that object.
Change is done on 3 levels:
- implicit function subscribes to epochs and at specific epochs finds the bounding box of the object and calls resizing of the color and density voxel grids to fit it
- VoxelGrid module calls cropping of the underlaying voxel grid and resizing to fit previous size it also adjusts its extends and translation to match wanted size
- Each voxel grid has its own way of cropping the underlaying data

Reviewed By: kjchalup

Differential Revision: D39854548

fbshipit-source-id: 5435b6e599aef1eaab980f5421d3369ee4829c50

Summary: Forward method is sped up using the scaffold, a low resolution voxel grid which is used to filter out the points in empty space. These points will be predicted as having 0 density and (0, 0, 0) color. The points which were not evaluated as empty space will be passed through the steps outlined above.

Reviewed By: kjchalup

Differential Revision: D39579671

fbshipit-source-id: 8eab8bb43ef77c2a73557efdb725e99a6c60d415

Summary: Avoid certain hardcoded paths in co3dv2 data

Reviewed By: davnov134

Differential Revision: D40209309

fbshipit-source-id: 0e83a15baa47d5bd07d2d23c6048cb4522c1ccba

Summary:
Changed ray_sampler and metrics to be able to use mixed frame raysampling.

Ray_sampler now has a new member which it passes to the pytorch3d raysampler.
If the raybundle is heterogeneous metrics now samples images by padding xys first. This reduces memory consumption.

Reviewed By: bottler, kjchalup

Differential Revision: D39542221

fbshipit-source-id: a6fec23838d3049ae5c2fd2e1f641c46c7c927e3

Summary: new implicitronRayBundle with added cameraIDs and camera counts. Added to enable a single raybundle inside Implicitron and easier extension in the future. Since RayBundle is named tuple and RayBundleHeterogeneous is dataclass and RayBundleHeterogeneous cannot inherit RayBundle. So if there was no ImplicitronRayBundle every function that uses RayBundle now would have to use Union[RayBundle, RaybundleHeterogeneous] which is confusing and unecessary complicated.

Reviewed By: bottler, kjchalup

Differential Revision: D39262999

fbshipit-source-id: ece160e32f6c88c3977e408e966789bf8307af59

Summary:
`get_rotation_to_best_fit_xy` is useful to expose externally, however there was a bug (which we probably did not care about for our use case): it could return a rotation matrix with det(R) == −1.
The diff fixes that, and also makes centroid optional (it can be computed from points).

Reviewed By: bottler

Differential Revision: D39926791

fbshipit-source-id: 5120c7892815b829f3ddcc23e93d4a5ec0ca0013

Summary: Any module can be subscribed to step updates from the training loop. Once the training loop publishes a step the voxel grid changes its dimensions. During the construction of VoxelGridModule and its parameters it does not know which is the resolution that will be loaded from checkpoint, so before the checkpoint loading a hook runs which changes the VoxelGridModule's parameters to match shapes of the loaded checkpoint.

Reviewed By: bottler

Differential Revision: D39026775

fbshipit-source-id: 0d359ea5c8d2eda11d773d79c7513c83585d5f17

Summary: Call expand_args_field when instantiating an object.

Reviewed By: shapovalov

Differential Revision: D39541931

fbshipit-source-id: de8e1038927ff0112463394412d5d8c26c4a1e17

Summary: Add the ability to process arbitrary point shapes `[n_grids, ..., 3]` instead of  only `[n_grids, n_points, 3]`.

Reviewed By: bottler

Differential Revision: D39574373

fbshipit-source-id: 0a9ecafe9ea58cd8f909644de43a1185ecf934f4

Summary:
- indicate location of OmegaConf.structured failures
- split the data gathering from enable_get_default_args to ease experimenting with it.
- comment fixes.
- nicer error when a_class_type has weird type.

Reviewed By: kjchalup

Differential Revision: D39434447

fbshipit-source-id: b80c7941547ca450e848038ef5be95b7ebbe8f3e

Summary: Fixes bugs in render_flyaround

Reviewed By: bottler

Differential Revision: D39271932

fbshipit-source-id: 07e6c9ee07ba91feb437b725af0a8942fd98db0b

Summary:
Move the flyaround rendering function into core implicitron.
The unblocks an example in the facebookresearch/co3d repo.

Reviewed By: bottler

Differential Revision: D39257801

fbshipit-source-id: 6841a88a43d4aa364dd86ba83ca2d4c3cf0435a4

Summary: Currently some implicit functions in implicitron take a raybundle, others take ray_points_world. raybundle is what they really need. However, the raybundle is going to become a bit more flexible later, as it will contain different numbers of rays for each camera.

Reviewed By: bottler

Differential Revision: D39173751

fbshipit-source-id: ebc038e426d22e831e67a18ba64655d8a61e1eb9

Summary: Added replacable decoding functions which will be applied after the voxel grid to get color and density

Reviewed By: bottler

Differential Revision: D38829763

fbshipit-source-id: f21ce206c1c19548206ea2ce97d7ebea3de30a23

Summary: Simple wrapper around voxel grids to make them a module

Reviewed By: bottler

Differential Revision: D38829762

fbshipit-source-id: dfee85088fa3c65e396cc7d3bf7ebaaffaadb646

Summary: Added voxel grid classes from TensoRF, both in their factorized (CP and VM) and full form.

Reviewed By: bottler

Differential Revision: D38465419

fbshipit-source-id: 8b306338af58dc50ef47a682616022a0512c0047

Summary:
generic_model_args no longer exists. Update some references to it, mostly in doc.

This fixes the testing of all the yaml files in test_forward pass.

Reviewed By: shapovalov

Differential Revision: D38789202

fbshipit-source-id: f11417efe772d7f86368b3598aa66c52b1309dbf

Reviewed By: shapovalov

Differential Revision: D38794764

fbshipit-source-id: 140c8a935d760bab8569d903cc52ac3dd73cd553

Summary: Previously, "psnr" was evaluated between the masked g.t. image and the render. To avoid confusion, "psnr" is now renamed to "psnr_masked".

Reviewed By: bottler

Differential Revision: D38707511

fbshipit-source-id: 8ee881ab1a05453d6692dde9782333a47d8c1234

Summary: Adds additional source views to the eval batches for evaluating many-view models on CO3D Challenge

Reviewed By: bottler

Differential Revision: D38705904

fbshipit-source-id: cf7d00dc7db926fbd1656dd97a729674e9ff5adb

Summary: Reports also the PSNR between the unmasked G.T. image and the render.

Reviewed By: bottler

Differential Revision: D38655943

fbshipit-source-id: 1603a2d02116ea1ce037e5530abe1afc65a2ba93

Summary:
LLFF (and most/all non-synth datasets) will have no background/foreground distinction. Add support for data with no fg mask.

Also, we had a bug in stats loading, like this:
  * Load stats
  * One of the stats has a history of length 0
  * That's fine, e.g. maybe it's fg_error but the dataset has no notion of fg/bg. So leave it as len 0
  * Check whether all the stats have the same history length as an arbitrarily chosen "reference-stat"
  * Ooops the reference-stat happened to be the stat with length 0
  * assert (legit_stat_len == reference_stat_len (=0)) ---> failed assert

Also some minor fixes (from Jeremy's other diff) to support LLFF

Reviewed By: davnov134

Differential Revision: D38475272

fbshipit-source-id: 5b35ac86d1d5239759f537621f41a3aa4eb3bd68

Summary: remove n_instances==0 special case, standardise args for GlobalEncoderBase's forward.

Reviewed By: shapovalov

Differential Revision: D37817340

fbshipit-source-id: 0aac5fbc7c336d09be9d412cffff5712bda27290

Summary: continued - avoid duplicate inputs

Reviewed By: davnov134

Differential Revision: D38248827

fbshipit-source-id: 91ed398e304496a936f66e7a70ab3d189eeb5c70

Summary: Don't copy from one part of config to another, rather do the copy within GenericModel.

Reviewed By: davnov134

Differential Revision: D38248828

fbshipit-source-id: ff8af985c37ea1f7df9e0aa0a45a58df34c3f893

Summary: Made the config system call open_dict when it calls the tweak function.

Reviewed By: shapovalov

Differential Revision: D38315334

fbshipit-source-id: 5924a92d8d0bf399bbf3788247f81fc990e265e7

Summary:
Stats are logically connected to the training loop, not to the model. Hence, moving to the training loop.

Also removing resume_epoch from OptimizerFactory in favor of a single place - ModelFactory. This removes the need for config consistency checks etc.

Reviewed By: kjchalup

Differential Revision: D38313475

fbshipit-source-id: a1d188a63e28459df381ff98ad8acdcdb14887b7

Summary: Simple DataLoaderMapProvider instance

Reviewed By: davnov134

Differential Revision: D38326719

fbshipit-source-id: 58556833e76fae5790d25a59bea0aac4ce046bf1

Summary:
Added _NEED_CONTROL
 to JsonIndexDatasetMapProviderV2 and made dataset_tweak_args use it.

Reviewed By: bottler

Differential Revision: D38313914

fbshipit-source-id: 529847571065dfba995b609a66737bd91e002cfe

Summary: Make a dummy single-scene dataset using the code from generate_cow_renders (used in existing NeRF tutorials)

Reviewed By: kjchalup

Differential Revision: D38116910

fbshipit-source-id: 8db6df7098aa221c81d392e5cd21b0e67f65bd70

Summary:
This is an internal change in the config systen. It allows redefining a pluggable implementation with new default values. This is useful in notebooks / interactive use. For example, this now works.

        class A(ReplaceableBase):
            pass

        registry.register
        class B(A):
            i: int = 4

        class C(Configurable):
            a: A
            a_class_type: str = "B"

            def __post_init__(self):
                run_auto_creation(self)

        expand_args_fields(C)

        registry.register
        class B(A):
            i: int = 5

        c = C()

        assert c.a.i == 5

Reviewed By: shapovalov

Differential Revision: D38219371

fbshipit-source-id: 72911a9bd3426d3359cf8802cc016fc7f6d7713b

Summary:
Adding MeshRasterizerOpenGL, a faster alternative to MeshRasterizer. The new rasterizer follows the ideas from "Differentiable Surface Rendering via non-Differentiable Sampling".

The new rasterizer 20x faster on a 2M face mesh (try pose optimization on Nefertiti from https://www.cs.cmu.edu/~kmcrane/Projects/ModelRepository/!). The larger the mesh, the larger the speedup.

There are two main disadvantages:
* The new rasterizer works with an OpenGL backend, so requires pycuda.gl and pyopengl installed (though we avoided writing any C++ code, everything is in Python!)
* The new rasterizer is non-differentiable. However, you can still differentiate the rendering function if you use if with the new SplatterPhongShader which we recently added to PyTorch3D (see the original paper cited above).

Reviewed By: patricklabatut, jcjohnson

Differential Revision: D37698816

fbshipit-source-id: 54d120639d3cb001f096237807e54aced0acda25