config.yaml

# --------------------------------------
#         U-Net CNN - conv update but distinguishing betweed drs
# --------------------------------------

seed: 42

wandb:
  project: hirise-prediction
  mode: disabled  # online | offline | disabled
  group: null

data:
  root: null  # repository root; override for external data
  patch_root: null  # relative manifest paths default to the CSV parent
  data_record: "files/data_record_alls.csv"
  normalisation_mode: global_robust
  global_stats: "files/global_stats.json"
  num_sets: 200000
  train_size: 0.7
  val_size:   0.1
  test_size:  0.2
  meta_cols: ['TDI', 'IEA_PWS_temp', 'Incidence_angle', 'Orbit_number', 'Local_time', 'Phase_angle', 'Solar_longitude', 'Solar_distance', 'FPA_negY_temp']
  # meta_cols: ['TDI']

architecture:
  name: unet_conv_b22
  version: 1.1
  args:
    base_ch: 16
    depth: 4
    kernel_size: 3
    p_drop: 0.0
    n_convs: 2
    n_res_blocks: 2
    align_corners: True

optim:
  epochs: 20
  batch_size: 64
  lr: 1.5e-3
  weight_decay: 5.0e-5
  early_stopping:
    enabled: True
    patience: 10
    min_delta: 0.001
    min_epochs: 12
    restore_best: True

loss:
  name: HiRISELoss    # HiRISELoss | MSELoss | L1Loss
  config:             # Only required for HiRISELoss
    mae: 0.35         # L1
    gdl: 0.15
    local_mae: 0.10
    mean_mae: 0.30
    lf_l1: 0.10

evals:
  eval_dr: "files/data_record_evals.csv"
  eval_cfg: "hipredict/configs/evals.yaml"
  edr_csv: files/metadata/EDR_df.csv

save:
  imgs: False
  imgs_indiv: False
  model: True
  loss_map: False
  model_dir: null  # defaults from hipredict.paths
  img_dir: null  # defaults from hipredict.paths
  evals_dir: null  # defaults from hipredict.paths
  maps_dir: null  # defaults from hipredict.paths
flags:
  evaluate: False  # requires a separate evaluation manifest
  test: False
  notrain: False