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https://github.com/facebookresearch/pytorch3d.git
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813e941de5
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
57 lines
1.9 KiB
YAML
57 lines
1.9 KiB
YAML
defaults:
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- overfit_singleseq_base
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- _self_
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exp_dir: "./data/overfit_nerf_blender_repro/${oc.env:BLENDER_SINGLESEQ_CLASS}"
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data_source_ImplicitronDataSource_args:
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data_loader_map_provider_SequenceDataLoaderMapProvider_args:
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dataset_length_train: 100
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dataset_map_provider_class_type: BlenderDatasetMapProvider
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dataset_map_provider_BlenderDatasetMapProvider_args:
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base_dir: ${oc.env:BLENDER_DATASET_ROOT}/${oc.env:BLENDER_SINGLESEQ_CLASS}
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n_known_frames_for_test: null
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object_name: ${oc.env:BLENDER_SINGLESEQ_CLASS}
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path_manager_factory_class_type: PathManagerFactory
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path_manager_factory_PathManagerFactory_args:
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silence_logs: true
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model_factory_ImplicitronModelFactory_args:
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model_class_type: "OverfitModel"
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model_OverfitModel_args:
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mask_images: false
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raysampler_class_type: AdaptiveRaySampler
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raysampler_AdaptiveRaySampler_args:
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n_pts_per_ray_training: 64
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n_pts_per_ray_evaluation: 64
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n_rays_per_image_sampled_from_mask: 4096
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stratified_point_sampling_training: true
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stratified_point_sampling_evaluation: false
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scene_extent: 2.0
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scene_center:
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- 0.0
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- 0.0
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- 0.0
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renderer_MultiPassEmissionAbsorptionRenderer_args:
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density_noise_std_train: 0.0
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n_pts_per_ray_fine_training: 128
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n_pts_per_ray_fine_evaluation: 128
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raymarcher_EmissionAbsorptionRaymarcher_args:
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blend_output: false
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loss_weights:
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loss_rgb_mse: 1.0
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loss_prev_stage_rgb_mse: 1.0
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loss_mask_bce: 0.0
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loss_prev_stage_mask_bce: 0.0
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loss_autodecoder_norm: 0.00
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optimizer_factory_ImplicitronOptimizerFactory_args:
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exponential_lr_step_size: 3001
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lr_policy: LinearExponential
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linear_exponential_lr_milestone: 200
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training_loop_ImplicitronTrainingLoop_args:
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max_epochs: 6000
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metric_print_interval: 10
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store_checkpoints_purge: 3
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test_when_finished: true
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validation_interval: 100
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