mindspore-ai / mindspore-ai/hyper-parallel
[Bug]: 数据不够时训练静默退出
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- Dominant language
- Python
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- Forks
- 63
- Avg merge
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Description
Checklist
- 1. I have searched the existing issues (https://gitcode.com/mindspore/hyper-parallel/issues)
- 2. I have read the relevant documentation.
- 3. I have created a minimal reproduction case that clearly demonstrates the issue, including a complete code example and the error message with full traceback and error logs.
🐛 Describe the bug
使用小数据集进行训练，发现在某个step后静默退出。
Expected behavior
退出前有提示数据不足
Additional context
Environment info
Python 3.11.10
torch 2.6.0
transformers 5.13.0
Thanks for contributing 🎉!
schema_version: 1
source: gitcode
gitcode_repo: mindspore/hyper-parallel
gitcode_issue: 366
source_url: https://gitcode.com/mindspore/hyper-parallel/issues/366
Contributor guide
No contributing guide indexed for this repository
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
The issue names no source files, entry points, or tests. First reproduce the silent exit with the small dataset described, then trace the training loop and data-loading path to identify where insufficient data ends execution. Done means the run reports that the data is insufficient before exiting, with regression coverage for the reproduced case.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100