mmf/projects/neural_rendering/configs/synsin_realestate10k/realestate10k_defaults.yaml [1:53]:
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model_config:
  mesh_renderer:
    loss_weights:
      mesh_laplacian: 0.005
    z_min: 0.2
    z_max: 100.
    z_pred_scaling: 1.0
    z_pred_offset: 0.0
    pred_inv_z: true
    pred_inv_z_synsin: false
    rendering:
      z_background: 2.5  # this number doesn't matter since depth supervision is not used
      background_color: [0.544606, 0.49547735, 0.4452502]  # SynSin RealEstate10K mean RGB
    metrics:
      uint8_conversion: true

optimizer:
  type: adam_w  # HuggingFace transformer's AdamW
  params:
    lr: 1e-4
    eps: 1e-8
    weight_decay: 1e-5

scheduler:
  type: multi_step
  params:
    use_warmup: true
    lr_steps:
    - 40000
    - 45000
    lr_ratio: 0.2
    warmup_iterations: 500
    warmup_factor: 0.25

training:
  num_workers: 2
  clip_norm_mode: all
  clip_gradients: true
  max_grad_l2_norm: 5
  lr_scheduler: true
  max_updates: 50000
  checkpoint_interval: 5000
  evaluation_interval: 5000
  log_interval: 20
  batch_size: 64
  early_stop:
    enabled: false
    criteria: synsin_realestate10k/no_grad_PSNR
    minimize: false
  stdout_capture: false
  find_unused_parameters: true
  log_format: json
  tensorboard: false
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projects/neural_rendering/configs/synsin_realestate10k/realestate10k_defaults.yaml [1:53]:
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model_config:
  mesh_renderer:
    loss_weights:
      mesh_laplacian: 0.005
    z_min: 0.2
    z_max: 100.
    z_pred_scaling: 1.0
    z_pred_offset: 0.0
    pred_inv_z: true
    pred_inv_z_synsin: false
    rendering:
      z_background: 2.5  # this number doesn't matter since depth supervision is not used
      background_color: [0.544606, 0.49547735, 0.4452502]  # SynSin RealEstate10K mean RGB
    metrics:
      uint8_conversion: true

optimizer:
  type: adam_w  # HuggingFace transformer's AdamW
  params:
    lr: 1e-4
    eps: 1e-8
    weight_decay: 1e-5

scheduler:
  type: multi_step
  params:
    use_warmup: true
    lr_steps:
    - 40000
    - 45000
    lr_ratio: 0.2
    warmup_iterations: 500
    warmup_factor: 0.25

training:
  num_workers: 2
  clip_norm_mode: all
  clip_gradients: true
  max_grad_l2_norm: 5
  lr_scheduler: true
  max_updates: 50000
  checkpoint_interval: 5000
  evaluation_interval: 5000
  log_interval: 20
  batch_size: 64
  early_stop:
    enabled: false
    criteria: synsin_realestate10k/no_grad_PSNR
    minimize: false
  stdout_capture: false
  find_unused_parameters: true
  log_format: json
  tensorboard: false
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