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remove the support of old style input (#176)
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Co-authored-by: Han Wang <wang_han@iapcm.ac.cn>
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@wanghan-iapcm
wanghan-iapcm and Han Wang committed Oct 17, 2023
1 parent ebe7a17 commit 0c45f50
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Showing 3 changed files with 39 additions and 151 deletions.
1 change: 0 additions & 1 deletion dpgen2/entrypoint/args.py
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Original file line number Diff line number Diff line change
Expand Up @@ -147,7 +147,6 @@ def lmp_args():
)
doc_output_nopbc = "Remove pbc of the output configurations"
doc_convergence = "The method of convergence check."
doc_configuration_prefix = "The path prefix of lmp initial configurations"
doc_configuration = "A list of initial configurations."
doc_stages = (
"The definition of exploration stages of type `List[List[ExplorationTaskGroup]`. "
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14 changes: 0 additions & 14 deletions dpgen2/entrypoint/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,12 +86,6 @@ def main_parser() -> argparse.ArgumentParser:
parser_run.add_argument(
"CONFIG", help="the config file in json format defining the workflow."
)
parser_run.add_argument(
"-o",
"--old-compatible",
action="store_true",
help="compatible with old-style input script used in dpgen2 < 0.0.6.",
)

##########################################
# resubmit
Expand Down Expand Up @@ -124,12 +118,6 @@ def main_parser() -> argparse.ArgumentParser:
action="store_true",
help="if set then keep schedule of the old workflow. otherwise use the schedule defined in the input file",
)
parser_resubmit.add_argument(
"-o",
"--old-compatible",
action="store_true",
help="compatible with old-style input script used in dpgen2 < 0.0.6.",
)

##########################################
# show key
Expand Down Expand Up @@ -331,7 +319,6 @@ def main():
config = json.load(fp)
submit_concurrent_learning(
config,
old_style=args.old_compatible,
)
elif args.command == "resubmit":
with open(args.CONFIG) as fp:
Expand All @@ -342,7 +329,6 @@ def main():
wfid,
list_steps=args.list,
reuse=args.reuse,
old_style=args.old_compatible,
replace_scheduler=(not args.keep_schedule),
)
elif args.command == "status":
Expand Down
175 changes: 39 additions & 136 deletions dpgen2/entrypoint/submit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -197,36 +197,18 @@ def make_concurrent_learning_op(

def make_naive_exploration_scheduler(
config,
old_style=False,
):
# use npt task group
model_devi_jobs = (
config["model_devi_jobs"] if old_style else config["explore"]["stages"]
)
sys_configs = (
config["sys_configs"] if old_style else config["explore"]["configurations"]
)
sys_prefix = config["explore"].get("configuration_prefix")
if sys_prefix is not None:
for ii in range(len(sys_configs)):
if isinstance(sys_configs[ii], list):
sys_configs[ii] = [
os.path.join(sys_prefix, jj) for jj in sys_prefix[ii]
]
mass_map = config["mass_map"] if old_style else config["inputs"]["mass_map"]
type_map = config["type_map"] if old_style else config["inputs"]["type_map"]
numb_models = config["numb_models"] if old_style else config["train"]["numb_models"]
fp_task_max = config["fp_task_max"] if old_style else config["fp"]["task_max"]
max_numb_iter = (
config["max_numb_iter"] if old_style else config["explore"]["max_numb_iter"]
)
fatal_at_max = (
config.get("fatal_at_max", True)
if old_style
else config["explore"]["fatal_at_max"]
)
model_devi_jobs = config["explore"]["stages"]
sys_configs = config["explore"]["configurations"]
mass_map = config["inputs"]["mass_map"]
type_map = config["inputs"]["type_map"]
numb_models = config["train"]["numb_models"]
fp_task_max = config["fp"]["task_max"]
max_numb_iter = config["explore"]["max_numb_iter"]
fatal_at_max = config["explore"]["fatal_at_max"]
convergence = config["explore"]["convergence"]
output_nopbc = False if old_style else config["explore"]["output_nopbc"]
output_nopbc = config["explore"]["output_nopbc"]
scheduler = ExplorationScheduler()
# report
conv_style = convergence.pop("type")
Expand Down Expand Up @@ -359,93 +341,40 @@ def make_finetune_step(

def workflow_concurrent_learning(
config: Dict,
old_style: bool = False,
) -> Tuple[Step, Optional[Step]]:
default_config = (
normalize_step_dict(config.get("default_config", {}))
if old_style
else config["default_step_config"]
)

train_style = (
config.get("train_style", "dp") if old_style else config["train"]["type"]
)
explore_style = (
config.get("explore_style", "lmp") if old_style else config["explore"]["type"]
)
fp_style = config.get("fp_style", "vasp") if old_style else config["fp"]["type"]
prep_train_config = (
normalize_step_dict(config.get("prep_train_config", default_config))
if old_style
else config["step_configs"]["prep_train_config"]
)
run_train_config = (
normalize_step_dict(config.get("run_train_config", default_config))
if old_style
else config["step_configs"]["run_train_config"]
)
prep_explore_config = (
normalize_step_dict(config.get("prep_explore_config", default_config))
if old_style
else config["step_configs"]["prep_explore_config"]
)
run_explore_config = (
normalize_step_dict(config.get("run_explore_config", default_config))
if old_style
else config["step_configs"]["run_explore_config"]
)
prep_fp_config = (
normalize_step_dict(config.get("prep_fp_config", default_config))
if old_style
else config["step_configs"]["prep_fp_config"]
)
run_fp_config = (
normalize_step_dict(config.get("run_fp_config", default_config))
if old_style
else config["step_configs"]["run_fp_config"]
)
select_confs_config = (
normalize_step_dict(config.get("select_confs_config", default_config))
if old_style
else config["step_configs"]["select_confs_config"]
)
collect_data_config = (
normalize_step_dict(config.get("collect_data_config", default_config))
if old_style
else config["step_configs"]["collect_data_config"]
)
cl_step_config = (
normalize_step_dict(config.get("cl_step_config", default_config))
if old_style
else config["step_configs"]["cl_step_config"]
)
default_config = config["default_step_config"]

train_style = config["train"]["type"]
explore_style = config["explore"]["type"]
fp_style = config["fp"]["type"]
prep_train_config = config["step_configs"]["prep_train_config"]
run_train_config = config["step_configs"]["run_train_config"]
prep_explore_config = config["step_configs"]["prep_explore_config"]
run_explore_config = config["step_configs"]["run_explore_config"]
prep_fp_config = config["step_configs"]["prep_fp_config"]
run_fp_config = config["step_configs"]["run_fp_config"]
select_confs_config = config["step_configs"]["select_confs_config"]
collect_data_config = config["step_configs"]["collect_data_config"]
cl_step_config = config["step_configs"]["cl_step_config"]
upload_python_packages = config.get("upload_python_packages", None)

if train_style == "dp":
init_models_paths = (
config.get("training_iter0_model_path", None)
if old_style
else config["train"].get("init_models_paths", None)
)
numb_models = (
config["numb_models"] if old_style else config["train"]["numb_models"]
)
init_models_paths = config["train"].get("init_models_paths", None)
numb_models = config["train"]["numb_models"]
if init_models_paths is not None and len(init_models_paths) != numb_models:
raise RuntimeError(
f"{len(init_models_paths)} init models provided, which does "
"not match numb_models={numb_models}"
)
elif train_style == "dp-dist" and not old_style:
elif train_style == "dp-dist":
init_models_paths = (
[config["train"]["student_model_path"]]
if "student_model_path" in config["train"]
else None
)
config["train"]["numb_models"] = 1
else:
raise RuntimeError(
f"unknown params, train_style: {train_style}, old_style: {old_style}"
)
raise RuntimeError(f"unknown params, train_style: {train_style}")

if upload_python_packages is not None and isinstance(upload_python_packages, str):
upload_python_packages = [upload_python_packages]
Expand All @@ -470,23 +399,17 @@ def workflow_concurrent_learning(
cl_step_config=cl_step_config,
upload_python_packages=upload_python_packages,
)
scheduler = make_naive_exploration_scheduler(config, old_style=old_style)

type_map = config["type_map"] if old_style else config["inputs"]["type_map"]
numb_models = config["numb_models"] if old_style else config["train"]["numb_models"]
template_script_ = (
config["default_training_param"]
if old_style
else config["train"]["template_script"]
)
scheduler = make_naive_exploration_scheduler(config)

type_map = config["inputs"]["type_map"]
numb_models = config["train"]["numb_models"]
template_script_ = config["train"]["template_script"]
if isinstance(template_script_, list):
template_script = [json.loads(Path(ii).read_text()) for ii in template_script_]
else:
template_script = json.loads(Path(template_script_).read_text())
train_config = {} if old_style else config["train"]["config"]
lmp_config = (
config.get("lmp_config", {}) if old_style else config["explore"]["config"]
)
train_config = config["train"]["config"]
lmp_config = config["explore"]["config"]
if (
"teacher_model_path" in lmp_config
and lmp_config["teacher_model_path"] is not None
Expand All @@ -498,19 +421,8 @@ def workflow_concurrent_learning(
lmp_config["teacher_model_path"], "pb"
)

fp_config = config.get("fp_config", {}) if old_style else {}
if old_style:
potcar_names = config["fp_pp_files"]
incar_template_name = config["fp_incar"]
kspacing, kgamma = get_kspacing_kgamma_from_incar(incar_template_name)
fp_inputs_config = {
"kspacing": kspacing,
"kgamma": kgamma,
"incar_template_name": incar_template_name,
"potcar_names": potcar_names,
}
else:
fp_inputs_config = config["fp"]["inputs_config"]
fp_config = {}
fp_inputs_config = config["fp"]["inputs_config"]
fp_inputs = fp_styles[fp_style]["inputs"](**fp_inputs_config)

fp_config["inputs"] = fp_inputs
Expand All @@ -526,14 +438,8 @@ def workflow_concurrent_learning(
fp_config["run"]["teacher_model_path"], "pb"
)

init_data_prefix = (
config.get("init_data_prefix")
if old_style
else config["inputs"]["init_data_prefix"]
)
init_data = (
config["init_data_sys"] if old_style else config["inputs"]["init_data_sys"]
)
init_data_prefix = config["inputs"]["init_data_prefix"]
init_data = config["inputs"]["init_data_sys"]
if init_data_prefix is not None:
init_data = [os.path.join(init_data_prefix, ii) for ii in init_data]
if isinstance(init_data, str):
Expand Down Expand Up @@ -670,7 +576,6 @@ def copy_scheduler_plans(
def submit_concurrent_learning(
wf_config,
reuse_step: Optional[List[ArgoStep]] = None,
old_style: bool = False,
replace_scheduler: bool = False,
no_submission: bool = False,
):
Expand All @@ -680,7 +585,7 @@ def submit_concurrent_learning(
global_config_workflow(wf_config)

dpgen_step, finetune_step = workflow_concurrent_learning(
wf_config, old_style=old_style
wf_config,
)

if reuse_step is not None and replace_scheduler:
Expand Down Expand Up @@ -788,7 +693,6 @@ def resubmit_concurrent_learning(
wfid,
list_steps=False,
reuse=None,
old_style=False,
replace_scheduler=False,
):
wf_config = normalize_args(wf_config)
Expand Down Expand Up @@ -816,7 +720,6 @@ def resubmit_concurrent_learning(
wf = submit_concurrent_learning(
wf_config,
reuse_step=reuse_step,
old_style=old_style,
replace_scheduler=replace_scheduler,
)

Expand Down

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