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73 lines
1.6 KiB
YAML
73 lines
1.6 KiB
YAML
defaults:
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# This makes the logging module logs colorful
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- override hydra/job_logging: colorlog
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- override hydra/hydra_logging: colorlog
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hydra:
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run:
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# Configure output dir of each experiment programmatically from the arguments
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# Example "outputs/mnist/classifier/baseline/2021-03-10-141516"
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dir: outputs/${experiment_name}/${method_name}/${now:%Y-%m-%d_%H%M%S}
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experiment_name: blender_lego
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method_name: vanilla_nerf
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# pretrained loading options
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resume_train:
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load_dir: # pretrained model directory
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load_step: # pretrained model's step number
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max_num_iterations: 1000000
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steps_per_save: null
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steps_per_log: 10
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steps_per_test: 100
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model_dir: /tmp/mattport_models/
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# dataset options
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dataset:
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data_directory: data/blender/lego
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dataset_type: blender
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downscale_factor: 4
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# dataloader options
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dataloader:
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num_workers: 0
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shuffle: true
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num_images_to_sample_from: 8
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num_rays_per_batch: 1024
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# optimizer options
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param_groups:
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fields:
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optimizer:
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type: Adam
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lr: 1e-4
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scheduler:
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type: StepLR
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step_size: 30 # Period of learning rate decay.
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gamma: 0.1 # Multiplicative factor of learning rate decay. Default: 0.1.
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cameras:
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optimizer:
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type: SGD
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lr: 1e-4
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scheduler:
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type: ExponentialLR
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gamma: 0.1
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# machine options
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machine_config:
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num_gpus: 1
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num_machines: 1
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machine_rank: 0
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dist_url: auto
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# graph options
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graph:
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# NOTE(ethan): currently setting to nothing b/c we're still designing the config format...
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_target_: mattport.nerf.graph.vanilla_nerf.NeRFGraph
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near_plane: 1.0
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far_plane: 6.0
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num_coarse_samples: 64
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num_importance_samples: 64
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