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@ -1,46 +1,45 @@
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import contextlib
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import functools
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from typing import Optional
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from contextlib import AbstractContextManager
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from dataclasses import dataclass
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from typing import Optional
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import torch
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import torch.nn as nn
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import torch.distributed as dist
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import torch.nn as nn
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from colossalai.context.parallel_mode import ParallelMode
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from colossalai.core import global_context as gpc
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from colossalai.context.singleton_meta import SingletonMeta
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from colossalai.core import global_context as gpc
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from colossalai.logging import get_dist_logger
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from colossalai.utils.model.utils import InsertPostInitMethodToModuleSubClasses
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from colossalai.zero.shard_utils import BaseShardStrategy
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from colossalai.zero.sharded_model._utils import cast_tensor_to_fp16
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from colossalai.zero.sharded_model.sharded_model_v2 import ShardedModelV2
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from colossalai.zero.sharded_param import ShardedParamV2
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from colossalai.utils.model.utils import InsertPostInitMethodToModuleSubClasses
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class ZeroContextConfig(object):
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@dataclass
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class ZeroContextConfig:
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"""The configuration used to control zero context initialization.
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Args:
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target_device (torch.device): The device where param data are after exiting the context.
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replicated (bool, optional): Whether the param is replicated across data parallel group.
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is_replicated (bool, optional): Whether the param is replicated across data parallel group.
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Some parameters are not replicated, e.g. parameters in MOE experts.
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shard_param (bool, optional): Is param sharded after exiting the context. Defaults to False.
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"""
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def __init__(self, target_device: torch.device, replicated: bool = True, shard_param: bool = False):
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super().__init__()
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target_device: torch.device
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is_replicated: bool = True
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shard_param: bool = False
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if shard_param:
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assert replicated, "Non-replicated parameters can't be sharded."
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# replicated no-shard parameters should locate in cuda, since we will broadcast them soon
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if replicated and not shard_param:
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assert target_device.type == 'cuda', "Replicated no-shard paramters should locate in cuda."
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def __post_init__(self):
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if self.shard_param:
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assert self.is_replicated, "Non-replicated parameters can't be sharded."
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self.target_device = target_device
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self.is_replicated: bool = replicated
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self.shard_param: bool = shard_param
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if self.is_replicated and not self.shard_param:
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assert self.target_device.type == 'cuda', "Replicated no-shard parameters should be located in cuda."
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class ZeroInitContext(InsertPostInitMethodToModuleSubClasses):
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@ -74,7 +73,7 @@ class ZeroInitContext(InsertPostInitMethodToModuleSubClasses):
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self.seed = seed
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self.dp_process_group = gpc.get_group(ParallelMode.DATA)
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self.config = ZeroContextConfig(target_device=target_device, replicated=True, shard_param=shard_param)
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self.config = ZeroContextConfig(target_device=target_device, is_replicated=True, shard_param=shard_param)
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ZeroContextMgr().current_context = self
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@ -248,7 +247,7 @@ class ZeroContextMgr(metaclass=SingletonMeta):
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def no_shard_zero_context(is_replicated: bool = True) -> AbstractContextManager:
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return ZeroContextMgr().hijack_context_config(target_device=torch.device('cuda', torch.cuda.current_device()),
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replicated=is_replicated,
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is_replicated=is_replicated,
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shard_param=False)
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