Oceanbench osse_gf_nadir_sst reproduce

config.yaml

train_patcher_kw: 
    patches: 
      time: 15
      lon: 200
      lat: 200
    strides: 
      time: 1
      lon: 50
      lat: 50
    domain_limits: 
      lat: 
        _target_: builtins.slice
        _args_: [33.0, 43.0] # img size of 200
      lon: 
        _target_: builtins.slice
        _args_: [-65.0, -55.0] # img size of 200
      time:
        _target_: builtins.slice
        _args_: ['2013-02-01', '2013-09-30'] # train times
  val_patcher_kw: 
    patches: 
      time: 15
      lon: 200
      lat: 200
    strides: 
      time: 1
      lon: 200
      lat: 200
    domain_limits: 
      lat: 
        _target_: builtins.slice
        _args_: [33.0, 43.0] # img size of 200
      lon: 
        _target_: builtins.slice
        _args_: [-65.0, -55.0] # img size of 200
      time:
        _target_: builtins.slice
        _args_: ['2013-01-01', '2013-02-01'] # val times
  test_patcher_kw: 
    patches: 
      time: 15
      lon: 200
      lat: 200
    strides: 
      time: 1
      lon: 200
      lat: 200
    domain_limits: 
      lat: 
        _target_: builtins.slice
        _args_: [33.0, 43.0] # img size of 200
      lon: 
        _target_: builtins.slice
        _args_: [-65.0, -55.0] # img size of 200
      time:
        _target_: builtins.slice
        _args_: ['2012-10-22', '2012-12-02'] # test times
        
        
 model:
  _target_: models.4dvarnet_model.Lit4dVarNet
  solver:
    _target_: models.4dvarnet_model.GradSolver
    n_step: 12
    lr_grad: 100
    prior_cost:
      _target_: models.4dvarnet_model.BilinAEPriorCost
      dim_in: 15
      dim_hidden: 64
      downsamp: 2
    obs_cost:
      _target_: models.4dvarnet_model.MultiModalObsCost
      dim_in: 15
      dim_hidden: 5
    grad_mod:
      _target_: models.4dvarnet_model.ConvLstmGradModel
      dim_in: 15
      dim_hidden: 96
  rec_weight:
    _target_: models.4dvarnet_utils.get_triang_time_wei
    patch_dims:
      time: 15
      lat: 200
      lon: 200
    crop:
      time: 0
      lat: 5
      lon: 5
    offset: 0
  opt_fn:
    _target_: torch.optim.Adam
    _partial_: true
    lr: 0.001

results.csv