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ColossalAI/colossalai/utils/checkpoint_io/meta.py

82 lines
2.0 KiB

from dataclasses import dataclass
from typing import List, Optional, Set, Dict
@dataclass
class ParamDistMeta:
# parallel info
dp_rank: int
dp_world_size: int
tp_rank: int
tp_world_size: int
# tp info
tp_shard_dims: Optional[List[int]] = None
tp_num_parts: Optional[List[int]] = None
# zero info
zero_numel: Optional[int] = None
zero_orig_shape: Optional[List[int]] = None
@property
def used_tp(self) -> bool:
return self.tp_shard_dims is not None and self.tp_num_parts is not None
@property
def used_zero(self) -> bool:
return self.zero_numel is not None and self.zero_orig_shape is not None
@property
def parallel_meta(self) -> tuple:
return self.dp_rank, self.dp_world_size, self.tp_rank, self.tp_world_size
@property
def tp_meta(self) -> tuple:
return self.tp_shard_dims, self.tp_num_parts
@property
def zero_meta(self) -> tuple:
return self.zero_numel, self.zero_orig_shape
@staticmethod
def from_dict(d: dict) -> 'ParamDistMeta':
return ParamDistMeta(**d)
@dataclass
class ParamRedistMeta:
# parallel info
dp_world_size: int
tp_world_size: int
# tp info
tp_shard_dims: Optional[List[int]] = None
tp_num_parts: Optional[List[int]] = None
# zero info
zero_start_dp_rank: Optional[int] = None
zero_offsets: Optional[List[int]] = None
@property
def used_tp(self) -> bool:
return self.tp_shard_dims is not None and self.tp_num_parts is not None
@property
def used_zero(self) -> bool:
return self.zero_start_dp_rank is not None and self.zero_offsets is not None
@dataclass
class RankRedistMeta:
dp_rank: int
tp_rank: int
pp_rank: int
@dataclass
class PipelineRedistMeta:
params: Set[str]
@dataclass
class RedistMeta:
rank_meta: Dict[str, Dict[int, RankRedistMeta]]
pipeline_meta: List[PipelineRedistMeta]
param_meta: Dict[str, ParamRedistMeta]