# lightning.pytorch==2.5.5
seed_everything: 1999
trainer:
  accelerator: gpu
  strategy: auto
  devices: 1
  num_nodes: 1
  precision: null
  logger:
    - class_path: lightning.pytorch.loggers.WandbLogger
      init_args:
        save_dir: logs.autoregressive.wandb
        project: "thermal-conduction-unsteady-10.steps"
        name: "16_layer_16_hidden.refined"
  callbacks:
    # - class_path: lightning.pytorch.callbacks.ModelCheckpoint
    #   init_args:
    #     dirpath: logs.autoregressive.wandb/16_refined.10_steps/checkpoints
    #     monitor: val/loss
    #     mode: min
    #     save_top_k: 1
    #     filename: best-checkpoint
    # - class_path: lightning.pytorch.callbacks.EarlyStopping
    #   init_args:
    #     monitor: val/loss
    #     mode: min
    #     patience: 30
    #     verbose: false
    - class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
      init_args:
        increase_unrolling_steps_by: 4
        patience: 5
        last_patience: 15
        max_unrolling_steps: 10
        ckpt_path: logs.autoregressive.wandb/10_steps/basic.refined/16_layer_16_hidden/
  max_epochs: 1000
  min_epochs: null
  max_steps: -1
  min_steps: null
  overfit_batches: 0.0
  log_every_n_steps: 0
  accumulate_grad_batches: 1
  default_root_dir: null
  gradient_clip_val: 1.0

model: 
  class_path: ThermalSolver.autoregressive_module.GraphSolver
  init_args:
    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
    model_init_args: 
      input_dim: 1
      hidden_dim: 16
      output_dim: 1
      n_layers: 16
    unrolling_steps: 2
    
data: 
  class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
  init_args:
    hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
    split_name: "3_stripes.basic.refined"
    n_elements: 50
    batch_size: 24
    train_size: 0.7
    val_size: 0.2
    test_size: 0.1
    build_radial_graph: false
    remove_boundary_edges: true
    unrolling_steps: 2
    min_normalized_diff: 1e-4
optimizer: null
lr_scheduler: null