github.com/kubeflow/pytorch-operator/pkg/client/clientset/versioned/typed/kubeflow/v1beta1/fake

PyTorch on Kubernetes


License
Apache-2.0
Install
go get github.com/kubeflow/pytorch-operator/pkg/client/clientset/versioned/typed/kubeflow/v1beta1/fake

Documentation

Kubernetes Custom Resource and Operator for PyTorch jobs

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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

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 the manifests for the distributed MNIST example. You may change the config file based on your requirements.

cat examples/mnist/v1/pytorch_job_mnist_gloo.yaml

Deploy the PyTorchJob resource to start training:

kubectl create -f examples/mnist/v1/pytorch_job_mnist_gloo.yaml

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

kubectl get pods -l pytorch-job-name=pytorch-dist-mnist-gloo

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=pytorch-dist-mnist-gloo,pytorch-replica-type=master -o name)
kubectl logs -f ${PODNAME}

Monitoring a PyTorch Job

kubectl get -o yaml pytorchjobs pytorch-dist-mnist-gloo

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/v1
  kind: PyTorchJob
  metadata:
    creationTimestamp: 2019-01-11T00:51:48Z
    generation: 1
    name: pytorch-dist-mnist-gloo
    namespace: default
    resourceVersion: "2146573"
    selfLink: /apis/kubeflow.org/v1/namespaces/kubeflow/pytorchjobs/pytorch-dist-mnist-gloo
    uid: 13ad0e7f-153b-11e9-b5c1-42010a80001e
  spec:
    pytorchReplicaSpecs:
      Master:
        replicas: 1
        restartPolicy: OnFailure
        template:
          spec:
            containers:
            - args:
              - --backend
              - gloo
              image: gcr.io/kubeflow-ci/pytorch-dist-mnist-test:v1.0
              name: pytorch
              resources:
                limits:
                  nvidia.com/gpu: "1"
      Worker:
        replicas: 1
        restartPolicy: OnFailure
        template:
          spec:
            containers:
            - args:
              - --backend
              - gloo
              image: gcr.io/kubeflow-ci/pytorch-dist-mnist-test:v1.0
              name: pytorch
              resources:
                limits:
                  nvidia.com/gpu: "1"
  status:
    completionTime: 2019-01-11T01:03:15Z
    conditions:
    - lastTransitionTime: 2019-01-11T00:51:48Z
      lastUpdateTime: 2019-01-11T00:51:48Z
      message: PyTorchJob pytorch-dist-mnist-gloo is created.
      reason: PyTorchJobCreated
      status: "True"
      type: Created
    - lastTransitionTime: 2019-01-11T00:57:22Z
      lastUpdateTime: 2019-01-11T00:57:22Z
      message: PyTorchJob pytorch-dist-mnist-gloo is running.
      reason: PyTorchJobRunning
      status: "False"
      type: Running
    - lastTransitionTime: 2019-01-11T01:03:15Z
      lastUpdateTime: 2019-01-11T01:03:15Z
      message: PyTorchJob pytorch-dist-mnist-gloo is successfully completed.
      reason: PyTorchJobSucceeded
      status: "True"
      type: Succeeded
    replicaStatuses:
      Master:
        succeeded: 1
      Worker:
        succeeded: 1
    startTime: 2019-01-11T00:57:22Z

Contributing

Please refer to the developer_guide.