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Add the OverfitModel
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
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defaults:
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- overfit_base
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- _self_
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data_source_ImplicitronDataSource_args:
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data_loader_map_provider_SequenceDataLoaderMapProvider_args:
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batch_size: 1
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dataset_length_train: 1000
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dataset_length_val: 1
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num_workers: 8
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dataset_map_provider_JsonIndexDatasetMapProvider_args:
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assert_single_seq: true
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n_frames_per_sequence: -1
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test_restrict_sequence_id: 0
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test_on_train: false
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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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render_image_height: 800
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render_image_width: 800
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log_vars:
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- loss_rgb_psnr_fg
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- loss_rgb_psnr
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- loss_eikonal
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- loss_prev_stage_rgb_psnr
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- loss_mask_bce
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- loss_prev_stage_mask_bce
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- loss_rgb_mse
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- loss_prev_stage_rgb_mse
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- loss_depth_abs
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- loss_depth_abs_fg
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- loss_kl
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- loss_mask_neg_iou
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- objective
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- epoch
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- sec/it
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optimizer_factory_ImplicitronOptimizerFactory_args:
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lr: 0.0005
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multistep_lr_milestones:
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- 200
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- 300
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training_loop_ImplicitronTrainingLoop_args:
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max_epochs: 400
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