search

microsoft / nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
https://nni.readthedocs.io
MIT License
14k stars 1.81k forks source link

Chinese doc discussion #4298

Closed liuzhe-lz closed 2 years ago

liuzhe-lz commented 2 years ago

The table below shows monthly viewed times for top 30 doc pages, ordered by readthedocs catalogue.

These pages should be translated in this release: (15 in total)

liuzhe-lz commented 2 years ago
English Chinese Vote
Readme (index) 1904 766 6/6 ✓
Overview 783 571 5/6 ✓
Installation 661 460 5/6 ✓
　　Linux & Mac 436 307 4/6 ✓
　　Windows 297 4/6 ✓
　　Use Docker
QuickStart 965 862 6/6 ✓
Auto (Hyper-parameter) Tuning 800 772 6/6 ✓
　　Write Trial 403 473 6/6 ✓
　　Tuners 266 4/6 *
　　　　Overview 538 383 3/6 *
　　　　...
　　Assessors
　　　　Overview 1/6
　　　　...
　　Training Platform... 3/6
　　Examples...
　　WebUI 403 4/6 ✓
　　How to Debug 1/6
　　Advanced...
　　HPO Benchmarks...
Neural Architecture Search 763 509 5/5 ✓
　　Overview 578 249 4/5
　　Quick Start 432 276 5/5 ✓
　　Construct Model Space...
　　Multi-trial NAS... 1/5
　　One-shot NAS 1/5
　　　　DARTS 326
　　　　...
　　NAS Benchmarks...
　　NAS API References
Model Compression 631 382 5/5 ✓
　　Overview 395 283 4/5 ✓
　　Quick Start 239 5/5 ✓
　　Pruning 435 267 1/5
　　　　Pruners 704 430 1/5
　　　　Dependency Aware Mode
　　　　Model Speedup
　　Pruning V2 1/5
　　　　...
　　Quantization 2/5
　　　　Quantizers 351 2/5
　　　　Quantization Speedup 1/5
　　Utilities
　　Advanced Usage
　　API Reference
Feauture Engineering 230
　　...
References 304 3/6
　　nnictl Commands 540 302 3/6
　　Experiment Configuration 427 356 3/6
　　Experiment Configuration (legacy) 202 1/6
　　Search Space 301 207 3/6
　　NNI Annotation
　　SDK API References
　　　　Auto Tune
　　　　NAS
　　　　Compression
　　　　Python API 351 2/6
　　Supported Framework Library
　　Launch from Python
　　　　...
　　Shared Storage
　　Tensorboard
Use Cases and Solutions 293 260 3/6
　　...
Research and Publications 1/6
FAQ 1/6
How to Contribute... 1/6
Change Log
liuzhe-lz commented 2 years ago

I vote for:

(index) Overview Installation 　　Linux & Mac 　　Windows QuickStart　　(suggest rename to "Quick Start") Auto (Hyper-parameter) Tuning　　(suggest rename to "Auto Hyper-parameter Tuning") 　　Write Trial 　　Tuners 　　　　Overview 　　Web UI Neural Architecture Search 　　Overview 　　Quick Start Model Compression 　　Overview 　　Quick Start 　　Pruning V2 　　　　Pruning Speedup?　　(not exist yet) 　　Quantization 　　　　Quantizers 　　　　Quantization Speedup References 　　nnictl Commands 　　Experiment Configuration 　　Search Space 　　SDK API References - Python API　　(this is "launch experiment from python", I think it should not be here) Use Cases and Solutions Research and Publications

ultmaster commented 2 years ago

I vote for:

Readme Installation Quickstart HPO (should merge them into quickstart?) 　　Write Trial 　　Tuner Overview 　　WebUI NAS 　　Quickstart Compression 　　Quickstart

QuanluZhang commented 2 years ago

vote for:

(index) Overview QuickStart Auto (Hyper-parameter) Tuning 　　Write Trial 　　Tuners 　　Training Platform Neural Architecture Search 　　Overview 　　Quick Start 　　Multi-trial NAS 　　One-shot NAS Model Compression 　　Overview 　　Quick Start 　　Pruning 　　　　Pruners 　　Quantization 　　　　Quantizers Use Cases and Solutions (two or three)

SparkSnail commented 2 years ago

I vote for:

(index) Overview Installation 　　Linux & Mac 　　Windows QuickStart Auto (Hyper-parameter) Tuning 　　Write Trial 　　Tuners 　　Training Platform Neural Architecture Search 　　Overview 　　Quick Start Model Compression 　　Overview 　　Quick Start References 　　nnictl Commands
　　Experiment Configuration
Search Space
Python API
Use Cases and Solutions

Lijiaoa commented 2 years ago

index Overview Installation

QuickStart Auto(Hyper-parameter) Tuning

Neural Architecture Search (不做参考) Model Compression（不做参考）

References

Use Cases and Solutions FAQ How to Contribute

J-shang commented 2 years ago

Readme (index) Overview Installation

QuickStart Auto (Hyper-parameter) Tuning

Neural Architecture Search

Model Compression