| exp_name: deeponet_foil | |
| gpu: 0 | |
| seed: 1234567 | |
| results_path: ./results/ | |
| # data | |
| dataset_name: foil | |
| dataset_root: /wutailin/real_benchmark/ | |
| num_workers: 12 | |
| normalizer: gaussian # none, gaussian, range | |
| # data parameters for training | |
| mask_prob: 0.1 | |
| noise_scale: 0.1 # only applicable for numerical data | |
| # model | |
| model_name: deeponet | |
| checkpoint_path: ./results/deeponet/deeponet_foil_numerical_False/2025-09-19_01-39-51/model_0160.pth | |
| p: 256 | |
| dropout_rate: 0 | |
| # training | |
| is_use_tb: true | |
| scheduler: cosine # step, cosine | |
| step_size: 1000 # only applicable for step scheduler | |
| num_update: 4000 | |
| train_batch_size: 32 | |
| test_batch_size: 64 | |
| lr: 0.0001 | |
| clip_grad_norm: 0. | |
| # evaluation | |
| N_autoregressive: 1 | |
| N_plot: 1 | |