data:
  time_steps: 3
  chip_dims: 128
  channels: "(WV):blue|green|red"
  # channels: "S2:(blue|green|red)"
  # channels: "S2:(blue|green|red),L8:(blue|green|red)"
  # channels: "(S2,L8):blue|green|red"
  # channels: blue|green|red
  # exclude_sensors:
  #   - S2
  #   - PD
  window_space_scale: 5GSD
  output_space_scale: 5GSD
  batch_size: 8
  chip_overlap: 0
  dist_weights: 0
  min_spacetime_weight: 0.5
  neg_to_pos_ratio: 0.25
  normalize_inputs: true
  normalize_perframe: false
  resample_invalid_frames: true
  temporal_dropout: 0.
  time_sampling: hardish3
  time_span: 5y
  upweight_centers: true
  use_centered_positives: false
  use_cloudmask: false
  use_grid_positives: true
  verbose: 1
optimizer:
  class_path: torch.optim.Adam
  init_args:
    lr: 1e-4
    weight_decay: 0.01
    betas:
      - 0.9
      - 0.98
    eps: 1e-12
profile: false
seed_everything: 1234
trainer:
  accumulate_grad_batches: 32
  callbacks: null
  check_val_every_n_epoch: 1
  enable_checkpointing: true
  enable_model_summary: true
  enable_progress_bar: true
  # gradient_clip_algorithm: norm
  # gradient_clip_val: 0.5
  log_every_n_steps: 5
  logger: true
  max_steps: 200000
  num_sanity_val_steps: 2
  replace_sampler_ddp: true
  track_grad_norm: 2