OP Configs

RunDPTrain

init_model_start_pref_v:

type: float, optional, default: 0.0

argument path: init_model_start_pref_v

The start virial prefactor in loss when init-model

init_model_start_pref_f:

type: int | float, optional, default: 100

argument path: init_model_start_pref_f

The start force prefactor in loss when init-model

init_model_start_pref_e:

type: float, optional, default: 0.1

argument path: init_model_start_pref_e

The start energy prefactor in loss when init-model

init_model_start_lr:

type: float, optional, default: 0.0001

argument path: init_model_start_lr

The start learning rate when init-model

init_model_numb_steps:

type: int, optional, default: 400000, alias: init_model_stop_batch

argument path: init_model_numb_steps

The number of training steps when init-model

init_model_old_ratio:

type: float, optional, default: 0.9

argument path: init_model_old_ratio

The frequency ratio of old data over new data

init_model_policy:

type: str, optional, default: no

argument path: init_model_policy

The policy of init-model training. It can be

• ‘no’: No init-model training. Traing from scratch.

• ‘yes’: Do init-model training.

• ‘old_data_larger_than:XXX’: Do init-model if the training data size of the previous model is larger than XXX. XXX is an int number.

RunLmp

command:

type: str, optional, default: lmp

argument path: command

The command of LAMMPS

RunVasp

out:

type: str, optional, default: data

argument path: out

The output dir name of labeled data. In deepmd/npy format provided by dpdata.

log:

type: str, optional, default: vasp.log

argument path: log

The log file name of VASP

command:

type: str, optional, default: vasp

argument path: command

The command of VASP