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Add the OverfitModel

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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
This commit is contained in:
Emilien Garreau
2023-03-24 07:27:39 -07:00
committed by Facebook GitHub Bot
parent 7d8b029aae
commit 813e941de5
16 changed files with 2012 additions and 201 deletions
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2
projects/implicitron_trainer/experiment.py
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@@ -59,7 +59,7 @@ from pytorch3d.implicitron.dataset.data_source import (
DataSourceBase,
ImplicitronDataSource,
)
from pytorch3d.implicitron.models.generic_model import ImplicitronModelBase
from pytorch3d.implicitron.models.base_model import ImplicitronModelBase
from pytorch3d.implicitron.models.renderer.multipass_ea import (
MultiPassEmissionAbsorptionRenderer,