AI platform surveyossforum.jp/jossfiles/NEAOSS-WG1-20190423_AcumosAI_r1.pdf · 4/23/2019 · • After restarting docker, we couldn’t connect Acumos AI portal To connect, we had

© Hitachi, Ltd. 2019. All rights reserved.

Hitachi, Ltd. OSS Solution Center

Yusuke Furuyama

4/23/2019 NEAOSS WG1

AI platform surveyFeatures of Acumos AI

© Hitachi, Ltd. 2019. All rights reserved. 1

Contents

1. Why we evaluated Acumos AI?

2. What is Acumos AI?

3. Checking the Features of Acumos AI

4. Summary



2

• AI Innovation➢ Various algorithms have been developed (ex. Deep Learning)

➢ Lots of benefits from AI.

➢ In Hitachi, the number of AI project is increasing

• Enterprise Customer’s needs and challenges for AI application development➢ Needs for on-premise deployment

• Some cloud services for AI application development / deployment

➢ Leveraging AI models developed by different libraries(ex. TensorFlow, scikit-learn)

• API is different among libraries

➢ Getting AI models trained by someone

• Not so many places / tools for sharing the models (especially for private sharing)

According to official docs, Acumos AI seems to be useful to meet these needs


Contents




4. Summary


2-1. Overview of Acumos AI

4

・OSS AI platform under Linux Foundation・Makes it easy to build, share, deploy AI apps

- Package tool kits (TensorFlow, scikit-learn) and models with a common API - Provide marketplace for sharing AI models privately (among Acumos AI systems)

and publicly - Container based easy deployment to both public cloud and private environment

https://www.acumos.org/wp-content/uploads/sites/61/2018/03/acumos_open_source_ai_platform_032518.pdf


2-2. Development on Acumos AI

5

①Create the model with common API from the model trained by various ML/DL libraries②Dockerize the model and register to Acumos AI ③Combine multiple models on Design Studio (GUI dev tool) to build AI app④Deploy AI app to production environment

Common API

Pre-trainedModel

Model

Model

ML/DL libraries

Wrapped model

Portal

Creating docker image

docker imagedocker image

docker image

ML/DL libraries

Publish / Share

Developing AI application Azure / Private Kubernetes

GUI dev tool

docker container(Model)

docker container(Controller)


Onboard model

Creators of AI models

Application developers

Deployment

Infrastructure Engineers ProductionEnvironment

Additional External Dataset

AdditionalTraining

Transfer learning(Currently not implemented)

AI application


2-3. Features of Acumos AI

6

1. Difference among ML/DL libraries is wrapped by common API2. Dockerized model/apps for easy app development and easy deployment 3. GUI dev tool (Design Studio) for visual programming4. Sharing models/apps privately/publicly on the Market place

Common API

Pre-trainedModel

Model

Model

ML/DL libraries

Wrapped model

Portal

Creating docker image

docker imagedocker image

docker image

ML/DL libraries

Publish / Share

Developing AI application Azure / Private Kubernetes

GUI dev tool


docker container(Controller)


Onboard model

Creators of AI models

Application developers

Deployment

Infrastructure Engineers ProductionEnvironment

1. Common APIfor models

2. Docker container

3. GUI development tool

4. Market place

Additional External Dataset

AdditionalTraining

Currently not implemented

AI application


Contents




4. Summary


3-1. Features we checked

8

• Creating models with common API

➢ Used the models for face-privacy-filter tool

• Creating docker images of models

• Development AI application with Design Studio

➢ Combined 2 models on Design Studio as a development

• Deployment of developed AI application

➢ To private Kubernetes environment

• Using the functions of developed AI application from the photo

editing application

Tried following features along the development steps on previous chapter


3-2. About photo editing application

9

Developed AI applicationFrontend web application (Web server: Python SimpleHTTPServer)

Input(Photo)

Output(Pixelatedphoto)

Face Detect Model

Face Pixelation Model

REST API


3-3. Creation the model with common API / Dockerize

10

Demo


3-4. Development AI application with Design Studio

11

Demo


3-5. Deployment of developed AI application

12

Demo


3-6. Pixelate faces on Photo

13

Demo


3-7. Difficulties in using Acumos AI

• Couldn’t make docker images of AI models behind proxy

environment

➢ Failed to download some files from Internet because of proxy

➢ Acumos AI (Athena release) doesn’t have any settings for proxy

• After restarting docker, we couldn’t connect Acumos AI portal

➢ To connect, we had to uninstall Acumos AI and re-install

Acumos AI project announces that features for

・ Using Acumos AI behind the proxy・ Training models

will be implemented in next release(*)

This behavior seems to be a bug, so we’re going to escalate this issue to Acumos AI project

• Training hasn’t implemented yet

(*) https://wiki.acumos.org/display/REL/Project+Status+in+Boreas+Releasehttps://jira.acumos.org/browse/ACUMOS-940


Contents




4. Summary


4. Summary

16

• Confirmed following features are implemented

➢ Creation the model with common API

➢ Creation the docker image of the model

➢ GUI development tool for AI application

➢ Deployment of AI application to Azure / on-premise k8s environment

➢ Market place for sharing models and apps privately / publicly

Acumos AI is useful to meet the following needs

・ Deployment of AI apps to on-premise environment

・ Leveraging AI models developed by different DL/ML libraries

・ Getting AI models trained by someone in a organization

Training on Acumos AI and Using Acumos AI behind

proxy environment will be implemented next release

・ Confirm if these features are implemented in next release

・ If these features will be implemented, we can say Acumos AI is

suitable for AI app development of enterprise customers


END


Trademarks

18

• The Linux Foundation® is registered trademark of The Linux Foundation

• Other brand names and product names used in this material are trademarks,

registered trademarks, or trade names of their respective holders.


Appendix. Creation the model with common API / Dockerize

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① Select [ON-BOARDING MODEL] from the menu of Acumos AI portal and click ”ON-BOARDING BY WEB”

② Dockerize the model by Click “Browse” and select the model → Click ”Upload”→ Click ”On-Board Model”


Appendix. Creation the model with common API/ Dockerize

③ If creating docker image finishes successfully, rightmost icon will be changed like below

④ Select “MY MODELS”, then we can see the docker image created from the model


Appendix. Development AI application w/ Design Studio

22

① Select the model for development from “MY MODELS” then click “Manage My Models”

② Select the “Publish to Public Marketplace” and fill out the required information then click “Submit To Publication”



23

③ After registering the model to the marketplace, the rightmost icon will be changed like below

④ Select “MARCKETPLACE”, then we can see the model on the marketplace



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⑤ Select “DESIGN STUDIO”, then open “Models” tab

⑥ Develop AI app by connecting AI models on “DESIGN STUDIO”, then save the application



25

⑦ Select saved AI app from “My Solutions”, then click “Validate” tab

⑧ After validation, you can see developed AI app from “MY MODELS” → “MY UNPUBLISHED MODELS”


Appendix. Deployment of developed AI application

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② Select “Publish to Public Marketplace”, then set required fields. After setting, click “Submit to Publication”

① Select application for publish from “MY MODELS”, then click “Manage My Model”



27

③ After registering the app to Marketplace, you can see the rightmost icon is changed like below

④ Select “MARKETPLACE”, then you can see registered app



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⑤ Select application for deployment from “MY MODELS”, then click “Manage My Model”

⑥ Select “Export/Deploy to Cloud”, then click “Export To Cloud”→”Deploy to local” and download zip file of AI application from “Download Solution Package”



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# unzip solutin.zip -d /tmp/solution

# cd /tmp/solution

# docker login nexus3.acumos.org:10001 -u docker -p docker# ./deploy.sh . <username of docker-proxy> <password of docker-proxy>

⑦ Send downloaded zip file to the demo environment⑧ Extract the zip file on the demo environment

⑨ Deploy AI application by the following commands

Documents

AI platform surveyossforum.jp/jossfiles/NEAOSS-WG1-20190423_AcumosAI_r1.pdf · 4/23/2019 · • After restarting docker, we couldn’t connect Acumos AI portal To connect, we had