deepspeedai / deepspeedai/DeepSpeed
[BUG] RuntimeError: 'weight' must be 2-D when two models are used
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- Dominant language
- Python
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Description
Describe the bug
My training involves two models, in which model A will update parameters, and model B is only used to generate results. Due to resource problems, I have to enable the zero3 strategy, and the sharding of both models at the same time will cause some errors, so how can I make model B not participate in the sharding? I use the deepspeed launcher.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the DeepSpeed launcher and reproduce the reported setup using two models with the zero3 strategy, recording where the 'weight' 2-D error occurs. Done means identifying a supported way for model B to avoid sharding while model A remains sharded, or documenting the missing configuration or limitation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- 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