An easy-to-use framework for Recommendation (Sekai Edition)
Project description
TorchEasyRec Introduction
What is TorchEasyRec?
TorchEasyRec is an easy-to-use framework for Recommendation
TorchEasyRec implements state of the art deep learning models used in common recommendation tasks: candidate generation(matching), scoring(ranking), multi-task learning and generative recommendation. It improves the efficiency of generating high performance models by simple configuration and easy customization.
Get Started
Why TorchEasyRec?
Run everywhere
- Local / PAI-DLC / PAI-DSW / EMR-DataScience
Diversified input data
- MaxCompute Table
- OSS files
- CSV files
- Parquet files
Easy-to-use
- Flexible feature config and model config
- Easy to implement customized models
- Easy deployment to EAS: automatic scaling, easy monitoring
Fast and robust
- Efficient and robust feature generation
- Large scale embedding with different sharding strategies
- Hybrid data-parallelism/model-parallelism
- Optimized kernels for RecSys powered by TorchRec
- Mixed precision
- Consistency guarantee: train and serving
A variety of features & models
- IdFeature / RawFeature / ComboFeature / LookupFeature / MatchFeature / ExprFeature / KvDotProduct / BoolMaskFeature / OverlapFeature / TokenizeFeature / SequenceIdFeature / SequenceRawFeature / SequenceFeature
- Match: DSSM / TDM / DAT / MIND
- Rank: WideAndDeep / DeepFM / MultiTower / DIN / RocketLaunching / DLRM / MaskNet / DCN / DCNv2 / xDeepFM
- Multi-Task: MMoE / DBMTL / PLE
- Generative-Rec: DlrmHSTU
- More models in development
Contribute
Any contributions you make are greatly appreciated!
- Please report bugs by submitting a issue.
- Please submit contributions using pull requests.
- Please refer to the Development document for more details.
Contact
Join Us
-
DingDing Group: 32260796, click this url or scan QrCode to join!
-
DingDing Group2: 37930014162, click this url or scan QrCode to join!
-
Email Group: easy_rec@service.aliyun.com.
Enterprise Service
- If you have any questions about how to use TorchEasyRec, please join the DingTalk group and contact us.
- If you have enterprise service needs or need to purchase Alibaba Cloud services to build a recommendation system, please join the DingTalk group to contact us.
License
TorchEasyRec is released under Apache License 2.0. Please note that third-party libraries may not have the same license as TorchEasyRec.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file tzrec_sekai-0.9.6.tar.gz.
File metadata
- Download URL: tzrec_sekai-0.9.6.tar.gz
- Upload date:
- Size: 10.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0f2037eab8412a130346e5f118a2df9d2e618288b2df864912201d66ebf8a9fd
|
|
| MD5 |
9d59d211c5e31ba4d220e008befe3d2e
|
|
| BLAKE2b-256 |
beed50a21cedf1e28352d4a623426c9bede4f1a4fe7a869600e78774b774390e
|
File details
Details for the file tzrec_sekai-0.9.6-py2.py3-none-any.whl.
File metadata
- Download URL: tzrec_sekai-0.9.6-py2.py3-none-any.whl
- Upload date:
- Size: 10.7 MB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
76a8a69d50b287763020f2586e92c818c765f17f15cdcd73b0f7d7640f8a3491
|
|
| MD5 |
f021bab2052b0a2e26412527cec041b3
|
|
| BLAKE2b-256 |
a8c3b6c53fea57a5cba34c81298da580052342f97919eefcb127deee9f788e7a
|