How to run DeepRacer locally on Mac

rundeepraceronmac.md

I took all my instructions from this page.  https://github.com/crr0004/deepracer

Here are the revised instructions for OSX (bold is console command)

1. Change to a folder in terminal that is not case-sensitive. ~/ should be fine
2. git clone --recurse-submodules https://github.com/crr0004/deepracer.git
3. brew install minio/stable/minio -- you may need to install brew first -- /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
4. install vncviewer from here https://www.realvnc.com/download/file/viewer.files/VNC-Viewer-6.19.325-MacOSX-x86_64.dmg
5. cd rl_coach
6. vim env.sh
7. Replace

export S3_ENDPOINT_URL=http://$(hostname -i):9000

with

IPADDR=$(ifconfig|grep -e 'inet [197][970]' | awk '{print $2}')
export S3_ENDPOINT_URL=http://$IPADDR:9000

8. add a "g" before readlink, so that it reads greadlink
9. save and exit
10. brew install coreutils
11. the "source" command in linux means run a shell script. in Mac you can use "." instead of "source"
12. . ./env.sh
13. minio server data
14. Browse to http://127.0.0.1:9000 and use the credentials the minio command gave you to login
15. Create a bucket called bucket. Create a folder custom_files in the bucket. Upload the two local files from deepracer/custom_files into bucket\custom_files.
16. Now edit the env.sh file again, this time replacing "minio" with the minio access key and "miniokey" with the access secret.
17. Now you're all done setting up your fake s3 bucket/server
18. Let's start Sagemaker setup, do Command T to open new terminal
19. Go back to the "deepracer" or repo root folder cd ..
20. python3 -m venv sagemaker_venv
21. This assumes you already have python3 installed. You probably need both pythons installed, 2 and 3.
22. . sagemaker_venv/bin/activate
23. pip install PyYAML==3.11
24. pip install urllib3==1.21.1
25. pip install -U sagemaker-python-sdk/ awscli ipython pandas
26. docker pull crr0004/sagemaker-rl-tensorflow:console
27. docker tag crr0004/sagemaker-rl-tensorflow:console 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-cpu-py3
28. I'm also assuming you already have docker installed and logged in with a docker account
29. mkdir -p ~/.sagemaker && cp config.yaml ~/.sagemaker
30. cd rl_coach
31. export LOCAL_ENV_VAR_JSON_PATH=$(greadlink -f ./env_vars.json)
32. cd ../.. to return to your folder holding the deepracer folder Git repo
33. mkdir -p robo/container
34. cd deepracer/rl_coach/
35. ipython rl_deepracer_coach_robomaker.py
36. Now SAGEMAKER LOCAL should be working. Now lets get Robomaker ready...
37. Command T to open new terminal window
38. cd ..
39. . sagemaker_venv/bin/activate
40. cd rl_coach
41. . ./env.sh
42. docker pull crr0004/deepracer_robomaker:console
43. cd ..
44. edit the robomaker.env file to also reference your local ip address and your aws key and secret
45. docker run --rm --name dr --env-file ./robomaker.env --network sagemaker-local -p 8080:5900 -it crr0004/deepracer_robomaker:console
46. Command Space, open vnc viewer, connect to 127.0.0.1:8080 to view Gazebo

Thank you! It seems to be working.

upd: ...except map loading, I haven't figured out how to fix it. Docker tag step seems to be obsolete.

I havent been able to upload the custom files from my local to minIO console. Any ideas?