PaddlePaddle Cloud is a Distributed Deep-Learning Cloud Platform for both cloud providers and enterprises.

PaddlePaddle Cloud use Kubernetes as it's backend job dispatching and cluster resource management center. And use PaddlePaddle as the deep-learning frame work. Users can use web pages or command-line tools to submit their deep-learning training jobs remotely to make use of power of large scale GPU clusters.

中文手册

English tutorials(comming soon...)

• PaddlePaddle Cloud use kubernetes as it's backend core, deploy kubernetes cluster using Sextant or any tool you like.

• Build Paddle Cloud Docker Image

  # build docker image git clone https://github.com/PaddlePaddle/cloud.git cd cloud/paddlecloud docker build -t [your_docker_registry]/pcloud . # push to registry so that we can submit paddlecloud to kubernetes docker push [your_docker_registry]/pcloud

• We use volume to mount MySQL data, cert files and settings, in k8s/ folder we have some samples for how to mount stand-alone files and settings using hostpath. Here's a good tutorial of creating kubernetes certs: https://coreos.com/kubernetes/docs/latest/getting-started.html

  • create data folder on a Kubernetes node, such as:

  mkdir -p /home/pcloud/data/mysql mkdir -p /home/pcloud/data/certs

  • Copy Kubernetes CA files (ca.pem, ca-key.pem) to /home/pcloud/data/certs folder
  • Copy Kubernetes admin user key (admin.pem, admin-key.pem) to /home/pcloud/data/certs folder (if you don't have it on Kubernetes worker node, you'll find it on Kubernetes master node)
  • Optianal: copy CephFS Key file(admin.secret) to /home/pcloud/data/certs folder
  • Copy paddlecloud/settings.py file to /home/pcloud/data folder

• Configure cloud_deployment.yaml

  • spec.template.spec.containers[0].volumes change the hostPath which match your data folder.
  • spec.template.spec.nodeSelector., edit the value kubernetes.io/hostname to host which data folder on.You can use kubectl get nodes to list all the Kubernetes nodes.

• Configure settings.py

  • Add your domain name (or the paddle cloud server's hostname or ip address) to ALLOWED_HOSTS.

  • Configure DATACENTERS to your backend storage, supports CephFS and HostPath currently. You can use HostPath mode to make use of shared file-systems like "NFS". If you use something like hostPath, you need to modify the DATACENTERS field in settings.py as follows:

    DATACENTERS = { "<MY_DATA_CENTER_NAME_HERE>":{ "fstype": "hostpath", "host_path": "/home/pcloud/data/public/", "mount_path": "/pfs/%s/home/%s/" # mount_path % ( dc, username ) } } 

• Configure cloud_ingress.yaml is your kubernetes cluster is using ingress (if you need to use Jupyter notebook, you have to configure the ingress controller) to proxy HTTP traffics, or you can configure cloud_service.yaml to use NodePort

  • if using ingress, configure spec.rules[0].host to your domain name

• Deploy mysql on Kubernetes first if you don't have it on your cluster, and modify the mysql endpoint in settings.py

  • kubectl create -f ./mysql_deployment.yaml (you need to fill in the nodeselector field with your node's hostname or ip in yaml first)
  • kubectl create -f ./mysql_service.yaml

• Deploy cloud on Kubernetes

  • kubectl create -f k8s/cloud_deployment.yaml(you need to fill in the nodeselector field with your node's hostname or ip in yaml first)
  • kubectl create -f k8s/cloud_service.yaml
  • kubectl create -f k8s/cloud_ingress.yaml(optianal if you don't need Jupyter notebook)

To test or visit the website, find out the kubernetes ingress IP addresses, or the NodePort.

Then open your browser and visit http://<ingress-ip-address>, or http://<any-node-ip-address>:<NodePort>

• Prepare public dataset

  You can create a Kubernetes Job for preparing the public cloud dataset with RecordIO files. You should modify the YAML file as your environment:

  • <DATACENTER>, Your cluster datacenter
  • <MONITOR_ADDR>, Ceph monitor address

  kubectl create -f k8s/prepare_dataset.yaml

• You still need a kubernetes cluster when try running locally.
• Make sure you have Python > 2.7.10 installed.
• Python needs to support OPENSSL 1.2. To check it out, simply run:

   >>> import ssl >>> ssl.OPENSSL_VERSION 'OpenSSL 1.0.2k 26 Jan 2017'

• Make sure you are using a virtual environment of some sort (e.g. virtualenv or pyenv).

virtualenv paddlecloudenv # enable the virtualenv source paddlecloudenv/bin/activate 

To run for the first time, you need to:

cd paddlecloud npm install pip install -r requirements.txt ./manage.py migrate ./manage.py loaddata sites npm run dev 

Browse to http://localhost:8000/

If you are starting the server for the second time, just run:

./manage.py runserver 

If you want to use mail command to send confirmation emails, change the below settings:

EMAIL_BACKEND = 'django_sendmail_backend.backends.EmailBackend' 

You may need to use hostNetwork for your pod when using mail command.

Or you can use django smtp bindings just refer to https://docs.djangoproject.com/en/1.11/topics/email/