growth_recursive_using_c_defaults.yaml

trainer:
  accelerator: cpu
  max_epochs: 1
  min_epochs: 0
  max_time: 00:00:10:00
  precision: 32
  num_sanity_val_steps: 0
  limit_val_batches: 0
  logger:
    class_path: pytorch_lightning.loggers.WandbLogger
    init_args:
      offline: true # set to true to not upload during testing
      log_model: false # set to true to save the model at the end
      name: null # can set name or have it automatically generated
      project: transversality_examples
      group: null # can group related runs
      tags:
        - basic_example
  callbacks:
    - class_path: pytorch_lightning.callbacks.LearningRateMonitor
      init_args:
        logging_interval: step
        log_momentum: false
    - class_path: pytorch_lightning.callbacks.ModelCheckpoint
      init_args:
        filename: best
        monitor: train_loss
        verbose: false
        save_last: true
        save_top_k: 1
        save_weights_only: true
        mode: min
        auto_insert_metric_name: true
    - class_path: pytorch_lightning.callbacks.EarlyStopping
      init_args:
        monitor: train_loss
        min_delta: 0.0
        patience: 1000
        mode: min
        check_finite: true
        divergence_threshold: 1000000 # stops if larger
        stopping_threshold: 1.0e-6   # typically the binding stopping threshold
        check_on_train_epoch_end: true
optimizer:
  class_path: torch.optim.LBFGS
  init_args:
    lr: 1.0
    tolerance_grad: 1.0e-6
    max_iter: 200 
    line_search_fn: 'strong_wolfe' 
model:
  beta: 0.9
  alpha: 0.333333333333333
  delta: 0.1
  k_0: 0.4
  batch_size: 0
  shuffle_training: false
  k_sim_grid_points: 16
  z_sim_grid_points: 1
  k_grid_min: 0.8
  k_grid_max: 2.5
  z_grid_min: 1.0
  z_grid_max: 1.0
  max_T_test: 50 # set to 0 to ignore
  train_grid_test_multiplier: 2.0 # if > 0 this is the number of additional grid points to sample for generating residuals
  g: 0.0
  vfi_parameters: # used in the VFI solution for the comparison
    tol: 1.0e-9
    max_iter: 200
    c_solver_tol: 1e-7
    k_grid_size: 50
    k_min_multiplier: 0.9
    k_max_multiplier: 1.1  
    interpolation_kind: "cubic"
  # Settings for output
  verbose: false
  hpo_objective_name: k_abs_rel_error
  always_log_hpo_objective: false  
  print_metrics: false
  save_metrics: false
  save_test_results: false
  test_loss_success_threshold: 1e-2 # lax, see k_prime_abs_rel_error
  ml_model:
    class_path: econ_layers.layers.FlexibleSequential
    init_args:
      n_in: 2
      n_out: 1
      layers: 4
      hidden_dim: 128
      hidden_bias: true
      last_bias: true
      activator:
        class_path: torch.nn.Tanh
      last_activator:
        class_path: torch.nn.Softplus