ByteDance-Seed / ByteDance-Seed/Bagel
EMA Model Save Fails Due to CPU Memory Exhaustion
- Dominant language
- Python
- Stars
- 6.2k
- Forks
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Description
I can save the model ckpt after fine-tuning it on 2 A100 GPUs with --cpu_offload True and --sharding_strategy FULL_SHARD.
But the EMA model can't be saved correctly (due to CPU memory exhaustion, ~433 GB) even I consider:
with FSDP.state_dict_type(
ema_model,
StateDictType.SHARDED_STATE_DICT,
ShardedStateDictConfig(offload_to_cpu=True),
):
...
Have anyone encounter this?
I'd appreciate your help!
Contributor guide
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Research direction
Reproduce EMA checkpoint saving with 2 A100 GPUs, --cpu_offload True, --sharding_strategy FULL_SHARD, and SHARDED_STATE_DICT with offload_to_cpu enabled. Trace the EMA model's FSDP state-dict path and compare it with the working model checkpoint; done means the EMA checkpoint saves without exhausting roughly 433 GB of CPU memory.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- distributed-systems, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100