# 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.TensorBoardLogger
      init_args:
        save_dir: logs
        name: "test"
        version: null
  callbacks:
    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
      init_args:
        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: 25
        verbose: false
  max_epochs: 1000
  min_epochs: null
  max_steps: -1
  min_steps: null
  overfit_batches: 0.0
  log_every_n_steps: null
  # inference_mode: true
  default_root_dir: null
  # accumulate_grad_batches: 2
  # gradient_clip_val: 1.0
model: 
  class_path: ThermalSolver.graph_module.GraphSolver
  init_args:
    model_class_path: ThermalSolver.model.learnable_finite_difference.CorrectionNet
    curriculum_learning: true
    start_iters: 5
    increase_every: 10
    increase_rate: 2
    max_iters: 2000
    accumulation_iters: 320
data: 
  class_path: ThermalSolver.graph_datamodule.GraphDataModule
  init_args:
    hf_repo: "SISSAmathLab/thermal-conduction"
    split_name: "1000_40x30"
    batch_size: 32
    train_size: 0.8
    test_size: 0.1
    test_size: 0.1
    build_radial_graph: false
    radius: 0.6
    remove_boundary_edges: false
optimizer: null
lr_scheduler: null
# ckpt_path: logs/test/version_0/checkpoints/best-checkpoint.ckpt