TLaunch_dev
Introduction
安装
virtualenv tmarl_env -p python3
# under tmarl_env, go into this repo and execute:
pip install -r requirements_dev.txt
pip install .
Quick Start
1.使用SSH登录TPod
TPod是一款面向分布式场景，为TLaunch准备的用户及资源管理工具。当管理员使用TPod创建用户后，可以自定义的为其指定分配的系统资源（包括CPU、GPU、Memory、Storage），并为该用户创建一个已经预装好TLaunch框架的TPod开发机，用户可以直接通过SSH登录该机器访问集群，以快速进入开发流程。
TPod的存储结构
在TPod中，我们会在/TData目录下创建你的个人文件夹，该文件夹会通过挂载的文件系统与远端同步。/TData内会预先创建以下内容：
code:用于存放训练代码setup.sh:用于指定训练环境及代码的安装方法
data:用于存放训练所需的数据cache:用于存放分布式计算过程中产生的缓存文件models:用于存放模型数据
2.存放算法代码并指定安装方法
在多数分布式场景中，少量的代码往往会经常改动。若每次改动代码都重新构建镜像，会浪费大量的时间。因此，我们可以将这部分代码存放在/TData/code文件夹中。在训练中，每当一个pods被创建时，都将先按照code文件夹中的setup.sh脚本更新环境
3.调用TLaunch创建任务
refs:https://github.com/TARTRL/TMARL/blob/master/docs/tlaunch/README.md
4.管理任务
当任务创建完成后，我们可以调用kubectl来查看任务状态及日志，其中常用的几条指令包括：
- 查看正在运行中的任务：
kubectl get lpjobs - 查看正在运行中的pods:
kubectl get pods - 查看pod节点日志:
kubectl logs ${pod name} - 查看pod节点详细信息:
kubectl describe pods ${pod name} - 删除任务:
kubectl delete lpjobs ${lpjob name}
1 maintainer
Metadata
1 maintainer
Release files for tlaunch 0.0.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| tlaunch-0.0.2.tar.gz | 46.0 kB | Without provenance | Details for tlaunch-0.0.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| tlaunch-0.0.2-py3-none-any.whl | Python 3 | none | any | Details for tlaunch-0.0.2-py3-none-any.whl |
Total release size: 118.8 kB
Release files / tlaunch-0.0.2.tar.gz
| Download URL | tlaunch-0.0.2.tar.gz |
|---|---|
| Size | 46.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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twine/4.0.1 CPython/3.9.15
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Release files / tlaunch-0.0.2-py3-none-any.whl
| Download URL | tlaunch-0.0.2-py3-none-any.whl |
|---|---|
| Size | 72.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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No |
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twine/4.0.1 CPython/3.9.15
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