mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-01 03:12:49 +08:00
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
43 lines
1.0 KiB
YAML
43 lines
1.0 KiB
YAML
defaults:
|
|
- overfit_base
|
|
- _self_
|
|
data_source_ImplicitronDataSource_args:
|
|
data_loader_map_provider_SequenceDataLoaderMapProvider_args:
|
|
batch_size: 1
|
|
dataset_length_train: 1000
|
|
dataset_length_val: 1
|
|
num_workers: 8
|
|
dataset_map_provider_JsonIndexDatasetMapProvider_args:
|
|
assert_single_seq: true
|
|
n_frames_per_sequence: -1
|
|
test_restrict_sequence_id: 0
|
|
test_on_train: false
|
|
model_factory_ImplicitronModelFactory_args:
|
|
model_class_type: "OverfitModel"
|
|
model_OverfitModel_args:
|
|
render_image_height: 800
|
|
render_image_width: 800
|
|
log_vars:
|
|
- loss_rgb_psnr_fg
|
|
- loss_rgb_psnr
|
|
- loss_eikonal
|
|
- loss_prev_stage_rgb_psnr
|
|
- loss_mask_bce
|
|
- loss_prev_stage_mask_bce
|
|
- loss_rgb_mse
|
|
- loss_prev_stage_rgb_mse
|
|
- loss_depth_abs
|
|
- loss_depth_abs_fg
|
|
- loss_kl
|
|
- loss_mask_neg_iou
|
|
- objective
|
|
- epoch
|
|
- sec/it
|
|
optimizer_factory_ImplicitronOptimizerFactory_args:
|
|
lr: 0.0005
|
|
multistep_lr_milestones:
|
|
- 200
|
|
- 300
|
|
training_loop_ImplicitronTrainingLoop_args:
|
|
max_epochs: 400
|