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Developer Guide

Kubeflow Training Operator is currently at v1.

Requirements

  • Go (1.22 or later)

Building the operator

Create a symbolic link inside your GOPATH to the location you checked out the code

mkdir -p $(go env GOPATH)/src/github.com/kubeflow
ln -sf ${GIT_TRAINING} $(go env GOPATH)/src/github.com/kubeflow/training-operator

Install dependencies

go mod tidy

Build it

go install github.com/kubeflow/training-operator/cmd/training-operator.v1

Running the Operator Locally

Running the operator locally (as opposed to deploying it on a K8s cluster) is convenient for debugging/development.

Run a Kubernetes cluster

First, you need to run a Kubernetes cluster locally. There are lots of choices:

Configure KUBECONFIG and KUBEFLOW_NAMESPACE

We can configure the operator to run locally using the configuration available in your kubeconfig to communicate with a K8s cluster. Set your environment:

export KUBECONFIG=$(echo ~/.kube/config)
export KUBEFLOW_NAMESPACE=$(your_namespace)
  • KUBEFLOW_NAMESPACE is used when deployed on Kubernetes, we use this variable to create other resources (e.g. the resource lock) internal in the same namespace. It is optional, use default namespace if not set.

Create the TFJob CRD

After the cluster is up, the TFJob CRD should be created on the cluster.

make install

Run Operator

Now we are ready to run operator locally:

make run

To verify local operator is working, create an example job and you should see jobs created by it.

cd ./examples/tensorflow/dist-mnist
docker build -f Dockerfile -t kubeflow/tf-dist-mnist-test:1.0 .
kubectl create -f ./tf_job_mnist.yaml

Go version

On ubuntu the default go package appears to be gccgo-go which has problems see issue golang-go package is also really old so install from golang tarballs instead.

Generate Python SDK

To generate Python SDK for the operator, run:

./hack/python-sdk/gen-sdk.sh

This command will re-generate the api and model files together with the documentation and model tests. The following files/folders in sdk/python are auto-generated and should not be modified directly:

sdk/python/docs
sdk/python/kubeflow/training/models
sdk/python/kubeflow/training/*.py
sdk/python/test/*.py

The Training Operator client and public APIs are located here:

sdk/python/kubeflow/training/api

Code Style

Python

  • Use black to format Python code

  • Run the following to install black:

    pip install black==23.9.1

  • To check your code:

    black --check --exclude '/*kubeflow_org_v1*|__init__.py|api_client.py|configuration.py|exceptions.py|rest.py' sdk/