Skip to content

Fix fine-tuning entries bug when doing restart. #3616

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
iProzd merged 1 commit into from
Mar 28, 2024
Merged

Fix fine-tuning entries bug when doing restart. #3616

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
78 changes: 41 additions & 37 deletions deepmd/pt/train/training.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -558,46 +558,50 @@ def update_single_finetune_params(
]
self.wrapper.load_state_dict(state_dict)

def single_model_finetune(
_model,
_model_params,
_sample_func,
):
old_type_map, new_type_map = (
_model_params["type_map"],
_model_params["new_type_map"],
)
if isinstance(_model, EnergyModel):
_model.change_out_bias(
_sample_func,
bias_adjust_mode=_model_params.get(
"bias_adjust_mode", "change-by-statistic"
),
origin_type_map=new_type_map,
full_type_map=old_type_map,
)
else:
# need to updated
pass
if finetune_model is not None:

# finetune
if not self.multi_task:
single_model_finetune(
self.model, model_params, self.get_sample_func
)
else:
for model_key in self.model_keys:
if model_key in self.finetune_links:
log.info(
f"Model branch {model_key} will be fine-tuned. This may take a long time..."
)
single_model_finetune(
self.model[model_key],
model_params["model_dict"][model_key],
self.get_sample_func[model_key],
def single_model_finetune(
_model,
_model_params,
_sample_func,
):
old_type_map, new_type_map = (
_model_params["type_map"],
_model_params["new_type_map"],
)
if isinstance(_model, EnergyModel):
_model.change_out_bias(
_sample_func,
bias_adjust_mode=_model_params.get(
"bias_adjust_mode", "change-by-statistic"
),
origin_type_map=new_type_map,
full_type_map=old_type_map,
)
else:
log.info(f"Model branch {model_key} will resume training.")
# need to updated
pass

# finetune
if not self.multi_task:
single_model_finetune(
self.model, model_params, self.get_sample_func
)
else:
for model_key in self.model_keys:
if model_key in self.finetune_links:
log.info(
f"Model branch {model_key} will be fine-tuned. This may take a long time..."
)
single_model_finetune(
self.model[model_key],
model_params["model_dict"][model_key],
self.get_sample_func[model_key],
)
else:
log.info(
f"Model branch {model_key} will resume training."
)

if init_frz_model is not None:
frz_model = torch.jit.load(init_frz_model, map_location=DEVICE)
Expand Down