| # @package _global_ | |
| # specify here default configuration | |
| # order of defaults determines the order in which configs override each other | |
| defaults: | |
| - data: pdb | |
| - model/architecture: foldingdit_100M | |
| - model/sampler: euler_maruyama | |
| - model/processor: protein_processor | |
| - model: simplefold | |
| - callbacks: default | |
| - logger: null # set logger here or use command line (e.g. `python train.py logger=tensorboard`) | |
| - trainer: default | |
| - paths: default | |
| - extras: default | |
| - hydra: default | |
| - _self_ | |
| # experiment configs allow for version control of specific hyperparameters | |
| # e.g. best hyperparameters for given model and datamodule | |
| - experiment: null | |
| # set False to skip model training | |
| train: True | |
| # evaluate on test set, using best model weights achieved during training | |
| # lightning chooses best weights based on the metric specified in checkpoint callback | |
| test: False | |
| # seed for random number generators in pytorch, numpy and python.random | |
| seed: null | |