project:
  name: Samudra
  default_model_name: samudra
  seed: 1

fake_data:
  time: 12
  height: 32
  width: 64

data:
  source_dir: ./data
  output_dir: ./data
  format: npz
  grid:
    height: 180
    width: 360
  depths_m: [2.5, 10.0, 22.5, 40.0, 65.0, 105.0, 165.0, 250.0, 375.0, 550.0, 775.0, 1050.0, 1400.0, 1850.0, 2400.0, 3100.0, 4000.0, 5000.0, 6000.0]
  time_step_days: 5
  input_state_steps: 2
  output_state_steps: 2
  recurrent_passes: 4

model:
  variant: thermo_dynamic
  input_channels: 158
  output_channels: 154
  state_channels: 77
  widths: [200, 250, 300, 400]
  dilations: [1, 2, 4, 8]
  bottleneck_width: 400
  bottleneck_dilation: 8
  checkpoint: null
  load_official_weights: false

training:
  batch_size: 2
  epochs: 10
  learning_rate: 0.0006
  weight_decay: 0.0
  num_workers: 0
  scheduler: cosine
  save_frequency: 5
  resume_checkpoint: null
  output_dir: ./data/checkpoints

inference:
  checkpoint: null
  rollout_steps: 6
  output_dir: ./result/output

visualization:
  output_dir: ./result