mindspore-ai / mindspore-ai/hyper-parallel
[Trainer] 代码串讲与关键流程说明
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- Dominant language
- Python
- Stars
- 53
- Forks
- 63
- Avg merge
- 23h 45m
- Merged PRs (30d)
- 63
Description
背景
为帮助开发者理解HyperParallel Trainer的整体设计、使用方式和扩展方法，在本Issue中集中进行代码串讲。
串讲内容
一、上层：用户接口与训练全流程
- Config：面向用户暴露的配置项和扩展方式
- 从配置解析、模型导入与并行化、训练组件导入到Training Loop的完整流程
二、并行层：新Trainer中的实现与扩展
- TP与CP
- EP
- FSDP
三、训练功能：新Trainer中的功能实现
- 高性能Module与Function
- 低精度适配及其与高性能Module的兼容
- Activation重计算与Swap
记录方式
Committer按模块在本Issue评论区补充代码截图和说明。每条评论建议标明代码路径、模块职责及关键调用关系，便于后续开发和问题定位。
schema_version: 1
source: gitcode
gitcode_repo: mindspore/hyper-parallel
gitcode_issue: 394
source_url: https://gitcode.com/mindspore/hyper-parallel/issues/394
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
No file paths or tests are named. Start by locating the Trainer Config, configuration parsing, model parallelization, training-loop entry points, and implementations for TP/CP, EP, FSDP, high-performance modules, low-precision support, activation recomputation, and swap. Done means the issue comments document each path, module responsibility, and key call relationship.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100