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:
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: 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:
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: 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: Make dataset type and args configurable on JsonIndexDatasetMapProvider.
Reviewed By: davnov134
Differential Revision: D36666705
fbshipit-source-id: 4d0a3781d9a956504f51f1c7134c04edf1eb2846
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
