DPGEN2 configurations

Op configs

RunDPTrain

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.

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_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_start_lr:

type: float, optional, default: 0.0001

argument path: init_model_start_lr

The start learning rate 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_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_v:

type: float, optional, default: 0.0

argument path: init_model_start_pref_v

The start virial prefactor in loss when init-model

RunLmp

command:

type: str, optional, default: lmp

argument path: command

The command of LAMMPS

teacher_model_path:

type: BinaryFileInput | NoneType | str, optional, default: None

argument path: teacher_model_path

The teacher model in Knowledge Distillation

shuffle_models:

type: bool, optional, default: False

argument path: shuffle_models

Randomly pick a model from the group of models to drive theexploration MD simulation

RunVasp

Alloy configs

Task group configs

task_group_configs:

type: dict

argument path: task_group_configs

Depending on the value of type, different sub args are accepted.

type:

type: str (flag key)

argument path: task_group_configs/type

possible choices: lmp-md, lmp-template

the type of the task group

When type is set to lmp-md (or its alias lmp-npt):

temps:

type: list, alias: Ts

argument path: task_group_configs[lmp-md]/temps

A list of temperatures in K. Also used to initialize the temperature

press:

type: list, optional, alias: Ps

argument path: task_group_configs[lmp-md]/press

A list of pressures in bar.

ens:

type: str, optional, default: nve, alias: ensemble

argument path: task_group_configs[lmp-md]/ens

The ensemble. Allowd options are ‘nve’, ‘nvt’, ‘npt’, ‘npt-a’, ‘npt-t’. ‘npt-a’ stands for anisotrpic box sampling and ‘npt-t’ stands for triclinic box sampling.

dt:

type: float, optional, default: 0.001

argument path: task_group_configs[lmp-md]/dt

The time step

nsteps:

type: int, optional, default: 100

argument path: task_group_configs[lmp-md]/nsteps

The number of steps

trj_freq:

type: int, optional, default: 10, aliases: t_freq, trj_freq, traj_freq

argument path: task_group_configs[lmp-md]/trj_freq

The number of steps

tau_t:

type: float, optional, default: 0.05

argument path: task_group_configs[lmp-md]/tau_t

The time scale of thermostat

tau_p:

type: float, optional, default: 0.5

argument path: task_group_configs[lmp-md]/tau_p

The time scale of barostat

pka_e:

type: NoneType | float, optional, default: None

argument path: task_group_configs[lmp-md]/pka_e

The energy of primary knock-on atom

neidelay:

type: int | NoneType, optional, default: None

argument path: task_group_configs[lmp-md]/neidelay

The delay of updating the neighbor list

no_pbc:

type: bool, optional, default: False

argument path: task_group_configs[lmp-md]/no_pbc

Not using the periodic boundary condition

use_clusters:

type: bool, optional, default: False

argument path: task_group_configs[lmp-md]/use_clusters

Calculate atomic model deviation

relative_f_epsilon:

type: NoneType | float, optional, default: None

argument path: task_group_configs[lmp-md]/relative_f_epsilon

Calculate relative force model deviation

relative_v_epsilon:

type: NoneType | float, optional, default: None

argument path: task_group_configs[lmp-md]/relative_v_epsilon

Calculate relative virial model deviation

When type is set to lmp-template:

lmp_template_fname:

type: str, aliases: lmp_template, lmp

argument path: task_group_configs[lmp-template]/lmp_template_fname

The file name of lammps input template

plm_template_fname:

type: str | NoneType, optional, default: None, aliases: plm_template, plm

argument path: task_group_configs[lmp-template]/plm_template_fname

The file name of plumed input template

revisions:

type: dict, optional, default: {}

argument path: task_group_configs[lmp-template]/revisions

traj_freq:

type: int, optional, default: 10, aliases: t_freq, trj_freq, trj_freq

argument path: task_group_configs[lmp-template]/traj_freq

The frequency of dumping configurations and thermodynamic states

Step configs

template_config:

type: dict, optional, default: {'image': 'dptechnology/dpgen2:latest'}

argument path: template_config

The configs passed to the PythonOPTemplate.

image:

type: str, optional, default: dptechnology/dpgen2:latest

argument path: template_config/image

The image to run the step.

timeout:

type: int | NoneType, optional, default: None

argument path: template_config/timeout

The time limit of the OP. Unit is second.

retry_on_transient_error:

type: int | NoneType, optional, default: None

argument path: template_config/retry_on_transient_error

The number of retry times if a TransientError is raised.

timeout_as_transient_error:

type: bool, optional, default: False

argument path: template_config/timeout_as_transient_error

Treat the timeout as TransientError.

envs:

type: NoneType | dict, optional, default: None

argument path: template_config/envs

The environmental variables.

template_slice_config:

type: dict, optional

argument path: template_slice_config

The configs passed to the Slices.

group_size:

type: int | NoneType, optional, default: None

argument path: template_slice_config/group_size

The number of tasks running on a single node. It is efficient for a large number of short tasks.

pool_size:

type: int | NoneType, optional, default: None

argument path: template_slice_config/pool_size

The number of tasks running at the same time on one node.

continue_on_failed:

type: bool, optional, default: False

argument path: continue_on_failed

If continue the the step is failed (FatalError, TransientError, A certain number of retrial is reached…).

continue_on_num_success:

type: int | NoneType, optional, default: None

argument path: continue_on_num_success

Only in the sliced OP case. Continue the workflow if a certain number of the sliced jobs are successful.

continue_on_success_ratio:

type: NoneType | float, optional, default: None

argument path: continue_on_success_ratio

Only in the sliced OP case. Continue the workflow if a certain ratio of the sliced jobs are successful.

parallelism:

type: int | NoneType, optional, default: None

argument path: parallelism

The parallelism for the step

executor:

type: NoneType | dict, optional, default: None

argument path: executor

The executor of the step.

Depending on the value of type, different sub args are accepted.

type:

type: str (flag key)

argument path: executor/type

possible choices: dispatcher

The type of the executor.

When type is set to dispatcher: