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Follow instructions from https://course.fast.ai/start_gcp.html
but when you get to step 3 use these instructions:
#Use this instead of the fast AI image -
export IMAGE_FAMILY="tf-latest-gpu"
export ZONE="us-west1-b"
export INSTANCE_NAME="my-deepracer-instance-test"
export INSTANCE_TYPE="n1-highmem-8" # budget: "n1-highmem-4"
gcloud compute instances create $INSTANCE_NAME \
--zone=$ZONE \
--image-family=$IMAGE_FAMILY \
--image-project=deeplearning-platform-release \
--maintenance-policy=TERMINATE \
--accelerator="type=nvidia-tesla-k80,count=1" \
--machine-type=$INSTANCE_TYPE \
--boot-disk-size=200GB \
--metadata="install-nvidia-driver=True" \
--preemptible
#Nip into VPC Network - Firewall Rules and open ports 9000, 8080, 6379, 8081, 5800, 5901
#connect via ssh (after about 5 mins to let it build) then run:
wget https://raw.githubusercontent.com/fmacrae/AI-Learning/master/GCPDeepracerSetup.sh
bash GCPDeepracerSetup.sh
It should install everything then give you the three sets of commands you need to run it
For the first time minio is already running so you can skip that line.
Second set of commands run sagemaker
Open another terminal /ssh connection to run the third set of commands
You can then monitor the gazeebo on port 8081 via VNC
Feed back if you have any issues. I've tested it a few times and seems to work OK.
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