Curriculum training a Differentiable Neural Computer using Population Based Training

Welcome to this installment of DeepMind mashup.

For background, read up on Differentiable Neural Computers and Population Based Training.

Prerequisites

• You need to have an AMQP queue server (the default is localhost)

Run local:

To run the system locally as single process:

pipenv install
pipenv shell

python -m experiment.k8 --master-works

To test:

pipenv shell
./script/test.sh

Deploying to Kubernetes (A cheatsheet of K8 runes)

Install RabitMQ

• Install Helm
• Initialise Helm on your cluster as per their docs

Give helm permissions on GKE:

kubectl create clusterrolebinding --user system:serviceaccount:kube-system:default kube-system-cluster-admin --clusterrole cluster-admin

Install a queue:

helm install --name one --set rabbitmq.username=admin,rabbitmq.password=secretpassword,rabbitmq.erlangCookie=secretcookie     stable/rabbitmq

Check the console output to get the AMPQ url and password for your new queue

Install our PBT application

Update secret.yaml to have the url to your AMQP queue.

Deploy the config:

kubectl create -f kubernetes/secret.yaml
kubectl create -f kubernetes/deployment.yaml

Set up permissions:

kubectl create serviceaccount default --namespace default
kubectl create clusterrolebinding default-cluster-rule --clusterrole=cluster-admin --serviceaccount=default:default

To see dashboard:

gcloud config config-helper --format=json | jq --raw-output '.credential.access_token'
kubectl proxy