Kubernetes Custom Resource and Operator for PyTorch jobs

Overview

This repository contains the specification and implementation of PyTorchJob custom resource definition. Using this custom resource, users can create and manage PyTorch jobs like other built-in resources in Kubernetes. See CRD definition

Prerequisites

• Kubernetes >= 1.8
• kubectl

Installing PyTorch Operator

Please refer to the installation instructions in the Kubeflow user guide. This installs pytorchjob CRD and pytorch-operator controller to manage the lifecycle of PyTorch jobs.

Creating a PyTorch Job

You can create PyTorch Job by defining a PyTorchJob config file. See distributed MNIST example config file. You may change the config file based on your requirements.

cat examples/dist-mnist/pytorch_job_mnist.yaml

Deploy the PyTorchJob resource to start training:

kubectl create -f examples/dist-mnist/pytorch_job_mnist.yaml

You should now be able to see the created pods matching the specified number of replicas.

kubectl get pods -l pytorch_job_name=dist-mnist-for-e2e-test

Training should run for about 10 epochs and takes 5-10 minutes on a cpu cluster. Logs can be inspected to see its training progress.

PODNAME=$(kubectl get pods -l pytorch_job_name=dist-mnist-for-e2e-test,task_index=0 -o name)
kubectl logs -f ${PODNAME}

Monitoring a PyTorch Job

kubectl get -o yaml pytorchjobs dist-mnist-for-e2e-test

See the status section to monitor the job status. Here is sample output when the job is successfully completed.

apiVersion: v1
items:
- apiVersion: kubeflow.org/v1alpha1
  kind: PyTorchJob
  metadata:
    clusterName: ""
    creationTimestamp: 2018-06-22T08:16:14Z
    generation: 1
    name: dist-mnist-for-e2e-test
    namespace: default
    resourceVersion: "3276193"
    selfLink: /apis/kubeflow.org/v1alpha1/namespaces/default/pytorchjobs/dist-mnist-for-e2e-test
    uid: 87772d3b-75f4-11e8-bdd9-42010aa00072
  spec:
    RuntimeId: kmma
    pytorchImage: pytorch/pytorch:v0.2
    replicaSpecs:
    - masterPort: 23456
      replicaType: MASTER
      replicas: 1
      template:
        metadata:
          creationTimestamp: null
        spec:
          containers:
          - image: gcr.io/kubeflow-ci/pytorch-dist-mnist_test:1.0
            imagePullPolicy: IfNotPresent
            name: pytorch
            resources: {}
          restartPolicy: OnFailure
    - masterPort: 23456
      replicaType: WORKER
      replicas: 3
      template:
        metadata:
          creationTimestamp: null
        spec:
          containers:
          - image: gcr.io/kubeflow-ci/pytorch-dist-mnist_test:1.0
            imagePullPolicy: IfNotPresent
            name: pytorch
            resources: {}
          restartPolicy: OnFailure
    terminationPolicy:
      master:
        replicaName: MASTER
        replicaRank: 0
  status:
    phase: Done
    reason: ""
    replicaStatuses:
    - ReplicasStates:
        Succeeded: 1
      replica_type: MASTER
      state: Succeeded
    - ReplicasStates:
        Running: 1
        Succeeded: 2
      replica_type: WORKER
      state: Running
    state: Succeeded
kind: List
metadata:
  resourceVersion: ""
  selfLink: ""