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add init_latest argument #375

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add init_latest argument #375

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15 changes: 15 additions & 0 deletions mace/cli/run_train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -446,6 +446,21 @@ def main() -> None:
)

start_epoch = 0
if args.init_latest:
try:
opt_start_epoch = checkpoint_handler.load_latest(
state=tools.CheckpointState(model, optimizer, lr_scheduler),
swa=True,
device=device,
model_only=True,
)
except Exception: # pylint: disable=W0703
opt_start_epoch = checkpoint_handler.load_latest(
state=tools.CheckpointState(model, optimizer, lr_scheduler),
swa=False,
device=device,
model_only=True,
)
if args.restart_latest:
try:
opt_start_epoch = checkpoint_handler.load_latest(
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9 changes: 8 additions & 1 deletion mace/tools/arg_parser.py
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Original file line number Diff line number Diff line change
Expand Up @@ -432,7 +432,14 @@ def build_default_arg_parser() -> argparse.ArgumentParser:
action="store_true",
default=False,
)
parser.add_argument(
parser_restart = parser.add_mutually_exclusive_group()
parser_restart.add_argument(
"--init_latest",
help="initialize model from latest checkpoint",
action="store_true",
default=False,
)
parser_restart.add_argument(
"--restart_latest",
help="restart optimizer from latest checkpoint",
action="store_true",
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10 changes: 6 additions & 4 deletions mace/tools/checkpoint.py
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Expand Up @@ -35,11 +35,12 @@ def create_checkpoint(state: CheckpointState) -> Checkpoint:

@staticmethod
def load_checkpoint(
state: CheckpointState, checkpoint: Checkpoint, strict: bool
state: CheckpointState, checkpoint: Checkpoint, strict: bool, model_only: bool=False
) -> None:
state.model.load_state_dict(checkpoint["model"], strict=strict) # type: ignore
state.optimizer.load_state_dict(checkpoint["optimizer"])
state.lr_scheduler.load_state_dict(checkpoint["lr_scheduler"])
if not model_only:
state.optimizer.load_state_dict(checkpoint["optimizer"])
state.lr_scheduler.load_state_dict(checkpoint["lr_scheduler"])


@dataclasses.dataclass
Expand Down Expand Up @@ -206,13 +207,14 @@ def load_latest(
swa: Optional[bool] = False,
device: Optional[torch.device] = None,
strict=False,
model_only: bool = False
) -> Optional[int]:
result = self.io.load_latest(swa=swa, device=device)
if result is None:
return None

checkpoint, epochs = result
self.builder.load_checkpoint(state=state, checkpoint=checkpoint, strict=strict)
self.builder.load_checkpoint(state=state, checkpoint=checkpoint, strict=strict, model_only=model_only)
return epochs

def load(
Expand Down