# saving model specifications
model_dir: /tmp/mattport_models/ 
steps_per_save: null
steps_per_test: 1000
max_num_iterations: 100000

# pretrained loading options
resume_train:
  load_dir: # pretrained model directory
  load_step: # pretrained model's step number

# NOTE(ethan): currently setting to nothing b/c we're still designing the config format...
network:
  _target_: mattport.nerf.graph.vanilla_nerf.NeRFGraph
  near_plane: 2.0
  far_plane: 6.0
  num_coarse_samples: 64
  num_importance_samples: 128

  loss_coefficients: # loss coefficients
    rgb_loss_coarse: 1.0
    rgb_loss_fine: 1.0

# optimizer options for network
param_groups:
  fields:
    optimizer:
      type: Adam
      lr: 5e-4
    scheduler:
      type: StepLR
      step_size: 30 #  Period of learning rate decay.
      gamma: 0.1 # Multiplicative factor of learning rate decay. Default: 0.1.
  cameras:
    optimizer:
      type: SGD
      lr: 1e-4
    scheduler:
      type: ExponentialLR
      gamma: 0.1