⚠️ Repo Archive Notice

As of Nov 13, 2020, charts in this repo will no longer be updated. For more information, see the Helm Charts Deprecation and Archive Notice, and Update.

Distributed TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs, and it supports distributed computing, allowing 'data parallel' or 'model parallel' on different servers. This means data scientists can now scale out distributed training to 100s of GPUs using TensorFlow.

DEPRECATION NOTICE

This chart is deprecated and no longer supported.

Prerequisites

Kubernetes cluster v1.12+

Chart Details

This chart will create a TensorFlow cluster, and distribute a computation graph across that cluster.

Installing the Chart

To install the chart with the release name mnist:
bash
```
$ helm install mnist incubator/distributed-tensorflow
```

To install with custom values via file:

$ helm install --values values.yaml mnist incubator/distributed-tensorflow

Below is an example of the custom value file values.yaml with GPU support.

worker:
  number: 2
  podManagementPolicy: Parallel
  image:
    repository: dysproz/distributed-tf
    tag: 1.6.0-gpu
  port: 9090
  gpuCount: 1

ps:
  number: 2
  podManagementPolicy: Parallel
  image:
    repository: dysproz/distributed-tf
    tag: 1.6.0
    pullPolicy: IfNotPresent
  port: 8080

# optimize for training
hyperparams:
  batchsize: 20
  learningrate: 0.001
  trainsteps: 10000

Notice: you can check the details of docker image from Docker hub

Uninstalling the Chart

To uninstall/delete the mnist deployment:
bash
```
$ helm delete mnist
```

The command removes all the Kubernetes components associated with the chart and deletes the release.

Configuration

The following table lists the configurable parameters of the Service Distributed Tensorflow chart and their default values.

Parameter	Description	Default
`worker.image.repository`	TensorFlow Worker Server's image repository	`dysproz/distributed-tf`
`worker.image.tag`	TensorFlow Worker Server's image tag	`gpu`
`worker.image.pullPolicy`	image pullPolicy for the worker	`IfNotPresent`
`worker.gpuCount`	Set the gpu to be allocated and allowed for the Pods	`0`
`worker.env`	key-value environment variables	None
`ps.image.repository`	TensorFlow Parameter Server's image repository	`dysproz/distributed-tf`
`ps.image.tag`	TensorFlow Parameter Server's image tag	`1.7.0-gpu`
`ps.image.pullPolicy`	image pullPolicy for the ps	`IfNotPresent`
`ps.env`	key-value environment variables	None
`volumes`	List of volumes defined in cluster (in standard k8s format)	host path to /tmp/mnist
`volumeMounts`	Volumes mounted into Pods (in standard k8s format)	host path volume mounted into /tmp/mnist-log
`hyperparams.batchsize`	batch size	`20`
`hyperparams.learningrate`	learning rate	`0.001`
`hyperparams.trainsteps`	train steps	`0` (continuous run)
`hyperparams.datadir`	data directory	None
`hyperparams.logdir`	logging directory	None
`hyperparams.hiddenunits`	Hidden units in neural network	None