feat : add distributed checkpoint via executor checkpoint_context

- Add checkpoint_context context manager to BaseExecutor with entry/exit barrier
- Add _gather_state_dict hook overridden per executor (template method)
- DDPExecutor skips unwrap on non-rank-0 to avoid redundant state_dict gather
- FSDPExecutor uses rank0_only=True to reduce memory on non-writers
- Remove redundant rank-0 guard from Checkpoint.save and manual barrier from Callback
This commit is contained in:
2026-07-13 12:27:09 +08:00
parent 9bcd696580
commit b092316385
3 changed files with 42 additions and 22 deletions
+24 -1
View File
@@ -7,6 +7,7 @@ from contextlib import contextmanager
from typing import Optional, Tuple
import torch
import torch.distributed as dist
import torch.nn as nn
from torch.distributed.fsdp import FullStateDictConfig, StateDictType
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
@@ -120,6 +121,21 @@ class BaseExecutor:
def unwrap_model(self, model: nn.Module):
return model.state_dict()
@contextmanager
def checkpoint_context(self, model: nn.Module):
if self.use_distributed:
dist.barrier()
state_dict = self._gather_state_dict(model)
yield state_dict
if self.use_distributed:
dist.barrier()
def _gather_state_dict(self, model: nn.Module):
state_dict = self.unwrap_model(model)
if self.use_distributed and get_rank() != 0:
return None
return state_dict
@property
def use_distributed(self) -> bool:
return get_world_size() > 1
@@ -208,6 +224,13 @@ class DDPExecutor(BaseExecutor):
return model.module.state_dict()
return model.state_dict()
def _gather_state_dict(self, model: nn.Module):
if not self.use_distributed:
return self.unwrap_model(model)
if get_rank() != 0:
return None
return self.unwrap_model(model)
@ExecutorFactory.register("fsdp")
class FSDPExecutor(BaseExecutor):
@@ -279,7 +302,7 @@ class FSDPExecutor(BaseExecutor):
with FSDP.state_dict_type(
model,
StateDictType.FULL_STATE_DICT,
FullStateDictConfig(offload_to_cpu=True, rank0_only=False),
FullStateDictConfig(offload_to_cpu=True, rank0_only=True),
):
return model.state_dict()