pytorch3d/projects/implicitron_trainer/configs/repro_singleseq_nerf_blender.yaml
Krzysztof Chalupka 1b0584f7bd Replace pluggable components to create a proper Configurable hierarchy.
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
2022-07-29 17:32:51 -07:00

39 lines
1.3 KiB
YAML

defaults:
- repro_singleseq_base
- _self_
exp_dir: "./data/nerf_blender_publ/${oc.env:BLENDER_SINGLESEQ_CLASS}"
data_source_ImplicitronDataSource_args:
data_loader_map_provider_SequenceDataLoaderMapProvider_args:
dataset_length_train: 100
dataset_map_provider_class_type: BlenderDatasetMapProvider
dataset_map_provider_BlenderDatasetMapProvider_args:
base_dir: ${oc.env:BLENDER_DATASET_ROOT}
object_name: ${oc.env:BLENDER_SINGLESEQ_CLASS}
path_manager_factory_class_type: PathManagerFactory
n_known_frames_for_test: null
path_manager_factory_PathManagerFactory_args:
silence_logs: true
model_factory_ImplicitronModelFactory_args:
model_GenericModel_args:
raysampler_AdaptiveRaySampler_args:
n_rays_per_image_sampled_from_mask: 4096
scene_extent: 2.0
renderer_MultiPassEmissionAbsorptionRenderer_args:
n_pts_per_ray_fine_training: 128
n_pts_per_ray_fine_evaluation: 128
loss_weights:
loss_rgb_mse: 1.0
loss_prev_stage_rgb_mse: 1.0
loss_mask_bce: 0.0
loss_prev_stage_mask_bce: 0.0
loss_autodecoder_norm: 0.00
optimizer_factory_ImplicitronOptimizerFactory_args:
exponential_lr_step_size: 2000
training_loop_ImplicitronTrainingLoop_args:
max_epochs: 2000
visualize_interval: 0
validation_interval: 30