Files
AstrAI/astrai/parallel/__init__.py
T
ViperEkura 0b6a17330f feat: add FSDP2Executor using torch.distributed.fsdp.fully_shard API
- New FSDP2Executor registers as 'fsdp2' in ExecutorFactory, using per-module fully_shard() instead of FSDP1 FlatParameter wrapper
- FSDP2 preserves original Parameter objects as DTensors, eliminating use_orig_params=True hack
- FSDP2Executor implements _no_sync via set_requires_gradient_sync, clip_grad_norm via unshard, unwrap_model via DTensor.full_tensor
- Drop **_extra/**_ddp_only_kwargs fallbacks in BaseExecutor/FSDPExecutor/FSDP2Executor, replaced by parallel_mode-aware executor_kwargs dispatch in train.py (ddp-only kwargs only passed when parallel_mode=ddp)
- Export FSDP2Executor in astrai.parallel.__init__
2026-07-20 01:46:25 +08:00

41 lines
830 B
Python

from astrai.parallel.executor import (
AccumOptimizer,
AccumScheduler,
BaseExecutor,
DDPExecutor,
ExecutorFactory,
FSDP2Executor,
FSDPExecutor,
GradientState,
NoneExecutor,
)
from astrai.parallel.module import ColumnParallelLinear, RowParallelLinear
from astrai.parallel.setup import (
get_current_device,
get_rank,
get_world_size,
only_on_rank,
setup_parallel,
spawn_parallel_fn,
)
__all__ = [
"get_world_size",
"get_rank",
"get_current_device",
"only_on_rank",
"setup_parallel",
"spawn_parallel_fn",
"RowParallelLinear",
"ColumnParallelLinear",
"ExecutorFactory",
"BaseExecutor",
"GradientState",
"AccumOptimizer",
"AccumScheduler",
"NoneExecutor",
"DDPExecutor",
"FSDPExecutor",
"FSDP2Executor",
]