Files
thermal-conduction-ml/experiments/config_autoregressive.yaml
Filippo Olivo 88bc5c05e4 transfer files
2025-11-25 19:19:31 +01:00

71 lines
1.7 KiB
YAML

# 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.autoregressive
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: 50
verbose: false
max_epochs: 1000
min_epochs: null
max_steps: -1
min_steps: null
overfit_batches: 0.0
log_every_n_steps: null
accumulate_grad_batches: 1
# reload_dataloaders_every_n_epochs: 1
default_root_dir: null
model:
class_path: ThermalSolver.autoregressive_module.GraphSolver
init_args:
model_class_path: ThermalSolver.model.learnable_finite_difference.CorrectionNet
model_init_args:
input_dim: 1
hidden_dim: 24
# output_dim: 1
n_layers: 1
start_unrolling_steps: 1
increase_every: 100000
increase_rate: 2
max_inference_iters: 300
max_unrolling_steps: 40
inner_steps: 1
data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name: "50_samples_easy"
batch_size: 64
train_size: 0.02
val_size: 0.02
test_size: 0.96
build_radial_graph: true
radius: 0.5
remove_boundary_edges: true
start_unrolling_steps: 1
optimizer: null
lr_scheduler: null
# ckpt_path: logs/test/version_0/checkpoints/best-checkpoint.ckpt