DPGEN2 configurations
Op configs
RunDPTrain
- impl:
- type:
str
, optional, default:tensorflow
, alias: backendargument path:impl
The implementation/backend of DP. It can be ‘tensorflow’ or ‘pytorch’. ‘tensorflow’ for default.
- 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_batchargument 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:
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
- init_model_with_finetune:
- type:
bool
, optional, default:False
argument path:init_model_with_finetune
Use finetune for init model
- finetune_args:
- type:
str
, optional, default: (empty string)argument path:finetune_args
Extra arguments for finetuning
- multitask:
- type:
bool
, optional, default:False
argument path:multitask
Do multitask training
- head:
- type:
str
|NoneType
, optional, default:None
argument path:head
Head to use in the multitask training
- multi_init_data_idx:
- type:
dict
|NoneType
, optional, default:None
argument path:multi_init_data_idx
A dict mapping from task name to list of indices in the init data
RunLmp
- command:
- type:
str
, optional, default:lmp
argument path:command
The command of LAMMPS
- teacher_model_path:
- type:
str
|BinaryFileInput
|NoneType
, 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
- head:
- type:
str
|NoneType
, optional, default:None
argument path:head
Select a head from multitask
RunVasp
Alloy configs
Task group configs
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:
NoneType
|int
, optional, default:None
argument path:template_config/timeout
The time limit of the OP. Unit is second.
- retry_on_transient_error:
- type:
NoneType
|int
, 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:
dict
|NoneType
, optional, default:None
argument path:template_config/envs
The environmental variables.
- template_slice_config:
- type:
dict
, optionalargument path:template_slice_config
The configs passed to the Slices.
- group_size:
- type:
NoneType
|int
, 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:
NoneType
|int
, 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:
NoneType
|int
, 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:
NoneType
|int
, optional, default:None
argument path:parallelism
The parallelism for the step