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2020.04.22 aws deepracer log analysis
- 1. AWS DeepRacer Log Analysis New release and collateral learning in action AWS Machine Learning Community NYC, New York City, 22.04.2020
- 2. Who am I? ● Lead Developer, Java ● Working for OpenMarket ● AWS Hero ● AWS DeepRacer Community Leader ● AWS DeepRacer League 2019 finalist ● Hobbyist baker ● Blogger: https://blog.deepracing.io https://breadcentric.com https://codelikeamother.uk https://kurykodowe.pl
- 3. How it all began AWS Summit London, DeepRacer Workshops
- 4. Log analysis
- 5. Tools in use Jupyter Notebook AWS Boto3 Numpy Pandas Matplotlib
- 6. Community Log Analysis Challenge ● Prepare an improvement to log analysis ● 10 entries, really good ● 0 merged
- 7. Community Log Analysis Challenge ● Merging generated JSON documents is difficult ● Changes overlap ● A bag of supporting code ● Other issues
- 8. We have to do better What if ● we had an easily resolvable project? ● we versioned notebooks as python scripts? ● we took supporting code from pypi?
- 9. deepracer-analysis https://github.com/aws-deepracer-community/deepracer-analysis Community notebooks Docker image Same as presented at the AWS DeepRacer Experts Boot Camp in 2019
- 10. Jupytext
- 11. Look Mom! I’m on PyPi! https://github.com/aws-deepracer-community/deepracer-utils/ I had to learn to use: ● setuptools ● versioneer ● tox
- 12. Running Docker: bin/build-docker-image.sh bin/start.sh lab bin/open-notebook.sh # mac: bin/url-to-notebook.sh Venv: python3 -m venv venv source venv/bin/activate pip install --upgrade -r requirements.txt jupyter lab
- 13. Editing Editing the notebook py file stays in synch After merging: jupytext --to notebook --execute notebook.py
- 14. Vision ● Bridge between training in the console and using SageMaker ● Learning resource: notebooks, data analysis, AWS APIs usage
- 15. TODOs ● Port the merge requests ● Tutorial notebooks - learning journey from first analysis to creating your own ○ Easy notebooks to start with ○ Specialised notebooks with advanced analysis ● Logs/training management ● Analyse object avoidance and head to head training (data missing from logs) ● Analyse evaluations during the training
- 16. Get support through the community http://join.deepracing.io #dr-training-log-analysis AWS DeepRacer Beginners Challenge: WIN $1000 AWS credits! Visit https://blog.deepracing.io for details
- 17. Questions? Let’s stay in touch https://www.linkedin.com/in/tomasz-ptak/ https://codelikeamother.uk https://breadcentric.com
Editor's Notes
- providing messaging solutions to companies who want to communicate with their customers at a scale
- re:Invent - I got a DeepRacer and decided to race at the summit so that it’s not waisted In the end of April 2019 - AWS DeepRacer Console became available I went to a workshop because credits - you know, I didn’t want - minutes ago I have learned that you can execute code cells in Jupyter Notebook
- While it’s fun to stare at the car going around the track, it won’t give you enough information to see how you’re doing. The simulation however does some logging and that includes data for each step that let you get some more information about the progress. You can visualise progress, certain behaviours, how your reward is doing and so on. When I struggled, I started using AWS’ log analysis, then added some functions, moved code out of the notebook
- We’ve had 10 nice entries, some rather basic level, others really in-depth Many were first pull requests in people’s lives
- Remember FrontPage? A bag - there were three files of code in python without a reliable change tracking process Community project was on a fork of the AWS workshops repo, changes on a branch. Most new starter issues were solvable by asking about the repo used, then branch, then notebook, and usually this didn’t work first time
- We cannot deter people as early when they want to run the project for the first time. We cannot make our lives difficult because the tool we choose is visually pleasing We need a utils project
- The fragment I’m showing has no output. Remember that Jupyter Notebook holds the image outputs in JSON as well. Good luck diffing that.
- I wanted to have a properly versioned code bundle. First log analysis, then other applications: local models upload, console models backup and restoration, eventually API integration
- First experience: I started a notebook and left it running for a month 6 months later I trained cars using SageMaker Notebooks
- Personal experience