mirror of
https://github.com/facebookresearch/pytorch3d.git
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c3f8dad55c
Summary: Stats are logically connected to the training loop, not to the model. Hence, moving to the training loop. Also removing resume_epoch from OptimizerFactory in favor of a single place - ModelFactory. This removes the need for config consistency checks etc. Reviewed By: kjchalup Differential Revision: D38313475 fbshipit-source-id: a1d188a63e28459df381ff98ad8acdcdb14887b7
82 lines
2.3 KiB
YAML
82 lines
2.3 KiB
YAML
defaults:
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- default_config
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- _self_
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exp_dir: ./data/exps/base/
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training_loop_ImplicitronTrainingLoop_args:
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visdom_port: 8097
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visualize_interval: 0
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max_epochs: 1000
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data_source_ImplicitronDataSource_args:
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data_loader_map_provider_class_type: SequenceDataLoaderMapProvider
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dataset_map_provider_class_type: JsonIndexDatasetMapProvider
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data_loader_map_provider_SequenceDataLoaderMapProvider_args:
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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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dataset_root: ${oc.env:CO3D_DATASET_ROOT}
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n_frames_per_sequence: -1
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test_on_train: true
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test_restrict_sequence_id: 0
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dataset_JsonIndexDataset_args:
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load_point_clouds: false
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mask_depths: false
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mask_images: false
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model_factory_ImplicitronModelFactory_args:
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model_GenericModel_args:
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loss_weights:
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loss_mask_bce: 1.0
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loss_prev_stage_mask_bce: 1.0
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loss_autodecoder_norm: 0.01
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loss_rgb_mse: 1.0
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loss_prev_stage_rgb_mse: 1.0
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output_rasterized_mc: false
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chunk_size_grid: 102400
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render_image_height: 400
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render_image_width: 400
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num_passes: 2
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implicit_function_NeuralRadianceFieldImplicitFunction_args:
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n_harmonic_functions_xyz: 10
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n_harmonic_functions_dir: 4
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n_hidden_neurons_xyz: 256
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n_hidden_neurons_dir: 128
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n_layers_xyz: 8
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append_xyz:
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- 5
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latent_dim: 0
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raysampler_AdaptiveRaySampler_args:
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n_rays_per_image_sampled_from_mask: 1024
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scene_extent: 8.0
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n_pts_per_ray_training: 64
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n_pts_per_ray_evaluation: 64
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stratified_point_sampling_training: true
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stratified_point_sampling_evaluation: false
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renderer_MultiPassEmissionAbsorptionRenderer_args:
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n_pts_per_ray_fine_training: 64
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n_pts_per_ray_fine_evaluation: 64
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append_coarse_samples_to_fine: true
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density_noise_std_train: 1.0
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view_pooler_args:
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view_sampler_args:
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masked_sampling: false
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image_feature_extractor_ResNetFeatureExtractor_args:
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stages:
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- 1
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- 2
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- 3
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- 4
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proj_dim: 16
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image_rescale: 0.32
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first_max_pool: false
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optimizer_factory_ImplicitronOptimizerFactory_args:
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breed: Adam
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weight_decay: 0.0
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lr_policy: MultiStepLR
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multistep_lr_milestones: []
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lr: 0.0005
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gamma: 0.1
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momentum: 0.9
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betas:
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- 0.9
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- 0.999
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