mirror of
https://github.com/tencentmusic/cube-studio.git
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66 lines
5.4 KiB
Markdown
66 lines
5.4 KiB
Markdown
# Cube Studio
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English | [简体中文](README.md)
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### Infra
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<img width="1442" alt="image" src="https://user-images.githubusercontent.com/20157705/182568155-f0d06046-8bfc-49dd-b283-720db0e556bc.png">
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cube-studio is a one-stop cloud-native machine learning platform open sourced by Tencent Music, Currently mainly includes the following functions
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- 1、data management: feature store, online and offline features; dataset management, structure data and media data, data label platform
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- 2、develop: notebook(vscode/jupyter); docker image management; image build online
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- 3、train: pipeline drag and drop online; open template market; distributed computing/training tasks, example tf/pytorch/mxnet/spark/ray/horovod/kaldi/volcano; batch priority scheduling; resource monitoring/alarm/balancing; cron scheduling
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- 4、automl: nni, ray
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- 5、inference: model manager; serverless traffic control; tf/pytorch/onnx/tensorrt model deploy, tfserving/torchserver/onnxruntime/triton inference; VGPU; load balancing、high availability、elastic scaling
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- 6、infra: multi-user; multi-project; multi-cluster; edge cluster mode; blockchain sharing;
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# Doc
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https://github.com/tencentmusic/cube-studio/wiki
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# Job Template
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tips:
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- 1、You can develop your own template, Easy to develop and more suitable for your own scenarios
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| template | type | describe |
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|:----------------------| :---- |:---------------------------------------------------------------------------------------------|
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| linux | base | Custom stand-alone operating environment, free to implement all custom stand-alone functions |
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| datax | import export | Import and export of heterogeneous data sources |
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| hadoop | data processing | hdfs,hbase,sqoop,spark client |
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| sparkjob | data processing | spark serverless |
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| volcanojob | data processing | volcano multi-machine distributed framework |
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| ray | data processing | python ray multi-machine distributed framework |
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| ray-sklearn | machine learning | sklearn based on ray framework supports multi-machine distributed parallel computing |
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| xgb | machine learning | xgb model training and inference |
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| tfjob | deep learning | Multi-machine distributed training of tensorflow |
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| pytorchjob | deep learning | Multi-machine distributed training of pytorch |
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| horovod | deep learning | Multi-machine distributed training of horovod |
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| paddle | deep learning | Multi-machine distributed training of paddle |
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| mxnet | deep learning | Multi-machine distributed training of mxnet |
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| kaldi | deep learning | Multi-machine distributed training of kaldi |
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| tfjob-train | model train | distributed training of tensorflow: plain and runner |
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| tfjob-runner | model train | distributed training of tensorflow: runner method |
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| tfjob-plain | model train | distributed training of tensorflow: plain method |
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| tf-model-evaluation | model evaluate | distributed model evaluation of tensorflow2.3 |
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| tf-offline-predict | model inference | distributed offline model inference of tensorflow2.3 |
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| model-register | model service | register model to platform |
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| model-offline-predict | model service | distributed offline model inference of framework |
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| deploy-service | model service | deploy inference service |
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| media-download | multimedia data processing | Distributed download of media files |
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| video-audio | multimedia data processing | Distributed extraction of audio from video |
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| video-img | multimedia data processing | Distributed extraction of pictures from video |
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| yolov7 | machine vision | object-detection with yolov7 |
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# Deploy
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[wiki](https://github.com/tencentmusic/cube-studio/wiki/%E5%B9%B3%E5%8F%B0%E5%8D%95%E6%9C%BA%E9%83%A8%E7%BD%B2)
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# Company
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