GitLab

Summary:
Introduces the OverfitModel for NeRF-style training with overfitting to one scene.
It is a specific case of GenericModel. It has been disentangle to ease usage.

## General modification

1. Modularize a minimum GenericModel to introduce OverfitModel
2. Introduce OverfitModel and ensure through unit testing that it behaves like GenericModel.

## Modularization

The following methods have been extracted from GenericModel to allow modularity with ManyViewModel:
- get_objective is now a call to weighted_sum_losses
- log_loss_weights
- prepare_inputs

The generic methods have been moved to an utils.py file.

Simplify the code to introduce OverfitModel.

Private methods like chunk_generator are now public and can now be used by ManyViewModel.

Reviewed By: shapovalov

Differential Revision: D43771992

fbshipit-source-id: 6102aeb21c7fdd56aa2ff9cd1dd23fd9fbf26315

Summary:
Running:
- clearly points users to experiment.py/visualize_reconstruction.py
Reproducing:
- Adds NeRF training on Blender
- Adds CO3Dv2 configs

Reviewed By: bottler

Differential Revision: D41534315

fbshipit-source-id: e85f5f1eafed8c35c9e91d748a04f238509cf8ec

Summary:
Adds yaml configs to train selected methods on CO3Dv2.

Few more updates:
1) moved some fields to base classes so that we can check is_multisequence in experiment.py
2) skip loading all train cameras for multisequence datasets, without this, co3d-fewview is untrainable
3) fix bug in json index dataset provider v2

Reviewed By: kjchalup

Differential Revision: D38952755

fbshipit-source-id: 3edac6fc8e20775aa70400bd73a0e6d52b091e0c

Summary: Fixes the blender synthetic configs.

Reviewed By: kjchalup

Differential Revision: D38786095

fbshipit-source-id: 6d0784ced41a3f2904f074221108cdb56bd20e7f

Summary: Linear followed by exponential LR progression. Needed for making Blender scenes converge.

Reviewed By: kjchalup

Differential Revision: D38557007

fbshipit-source-id: ad630dbc5b8fabcb33eeb5bdeed5e4f31360bac2

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: continued - avoid duplicate inputs

Reviewed By: davnov134

Differential Revision: D38248827

fbshipit-source-id: 91ed398e304496a936f66e7a70ab3d189eeb5c70

Summary: continued - don't duplicate inputs

Reviewed By: kjchalup

Differential Revision: D38248829

fbshipit-source-id: 2d56418ecbec9cc597c3cf0c122199e274661516

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: Blender data doesn't have depths or crops.

Reviewed By: shapovalov

Differential Revision: D38345583

fbshipit-source-id: a19300daf666bbfd799d0038aeefa14641c559d7

Summary: Remove the dataset's need to provide the task type.

Reviewed By: davnov134, kjchalup

Differential Revision: D38314000

fbshipit-source-id: 3805d885b5d4528abdc78c0da03247edb9abf3f7

Summary:
This large diff rewrites a significant portion of Implicitron's config hierarchy. The new hierarchy, and some of the default implementation classes, are as follows:
```
Experiment
    data_source: ImplicitronDataSource
        dataset_map_provider
        data_loader_map_provider
    model_factory: ImplicitronModelFactory
        model: GenericModel
    optimizer_factory: ImplicitronOptimizerFactory
    training_loop: ImplicitronTrainingLoop
        evaluator: ImplicitronEvaluator
```

1) Experiment (used to be ExperimentConfig) is now a top-level Configurable and contains as members mainly (mostly new) high-level factory Configurables.
2) Experiment's job is to run factories, do some accelerate setup and then pass the results to the main training loop.
3) ImplicitronOptimizerFactory and ImplicitronModelFactory are new high-level factories that create the optimizer, scheduler, model, and stats objects.
4) TrainingLoop is a new configurable that runs the main training loop and the inner train-validate step.
5) Evaluator is a new configurable that TrainingLoop uses to run validation/test steps.
6) GenericModel is not the only model choice anymore. Instead, ImplicitronModelBase (by default instantiated with GenericModel) is a member of Experiment and can be easily replaced by a custom implementation by the user.

All the new Configurables are children of ReplaceableBase, and can be easily replaced with custom implementations.

In addition, I added support for the exponential LR schedule, updated the config files and the test, as well as added a config file that reproduces NERF results and a test to run the repro experiment.

Reviewed By: bottler

Differential Revision: D37723227

fbshipit-source-id: b36bee880d6aa53efdd2abfaae4489d8ab1e8a27

Summary: Add the conditioning types to the repro yaml files. In particular, this fixes test_conditioning_type.

Reviewed By: shapovalov

Differential Revision: D37914537

fbshipit-source-id: 621390f329d9da662d915eb3b7bc709206a20552

Summary: As part of removing Task, move camera difficulty bin breaks from hard code to the top level.

Reviewed By: davnov134

Differential Revision: D37491040

fbshipit-source-id: f2d6775ebc490f6f75020d13f37f6b588cc07a0b

Summary: Add facilities for dataloading non-sequential scenes.

Reviewed By: shapovalov

Differential Revision: D37291277

fbshipit-source-id: 0a33e3727b44c4f0cba3a2abe9b12f40d2a20447

Summary: Refactors autodecoders. Tests pass.

Reviewed By: bottler

Differential Revision: D37592429

fbshipit-source-id: 8f5c9eac254e1fdf0704d5ec5f69eb42f6225113

Summary: Make dataset type and args configurable on JsonIndexDatasetMapProvider.

Reviewed By: davnov134

Differential Revision: D36666705

fbshipit-source-id: 4d0a3781d9a956504f51f1c7134c04edf1eb2846

Summary: As subj.

Reviewed By: bottler

Differential Revision: D36705775

fbshipit-source-id: 7370710e863025dc07a140b41f77a7c752e3159f

Summary: replace dataloader_zoo with a pluggable DataLoaderMapProvider.

Reviewed By: shapovalov

Differential Revision: D36475441

fbshipit-source-id: d16abb190d876940434329928f2e3f2794a25416

Summary: replace dataset_zoo with a pluggable DatasetMapProvider. The logic is now in annotated_file_dataset_map_provider.

Reviewed By: shapovalov

Differential Revision: D36443965

fbshipit-source-id: 9087649802810055e150b2fbfcc3c197a761f28a

Summary:
Move dataset_args and dataloader_args from ExperimentConfig into a new member called datasource so that it can contain replaceables.

Also add enum Task for task type.

Reviewed By: shapovalov

Differential Revision: D36201719

fbshipit-source-id: 47d6967bfea3b7b146b6bbd1572e0457c9365871

Summary: Make ResNetFeatureExtractor be an implementation of FeatureExtractorBase.

Reviewed By: davnov134

Differential Revision: D35433098

fbshipit-source-id: 0664a9166a88e150231cfe2eceba017ae55aed3a

Summary:
1. Typo in the dataset path in the config.
2. Typo in num_frames.
3. Pick sequence was cached before it was modified for single-sequence.

Reviewed By: bottler

Differential Revision: D36417329

fbshipit-source-id: 6dcd75583de510412e1ae58f63db04bb4447403e

Summary:
This converts raysamplers to ReplaceableBase so that users can hack their own raysampling impls.

Context: Andrea tried to implement TensoRF within implicitron but could not due to the need to implement his own raysampler.

Reviewed By: shapovalov

Differential Revision: D36016318

fbshipit-source-id: ef746f3365282bdfa9c15f7b371090a5aae7f8da

Summary: Implements a ViewPooler that groups ViewSampler and FeatureAggregator.

Reviewed By: shapovalov

Differential Revision: D35852367

fbshipit-source-id: c1bcaf5a1f826ff94efce53aa5836121ad9c50ec

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