stable/tensorflow-notebook

Chart version: 0.1.3
Api version: v1
App version: 1.6.0
A Helm chart for tensorflow notebook and tensorboard
application
Chart Type
Active
Status
Unknown
License
119
Downloads
https://kubernetes-charts.storage.googleapis.com
Set me up:
helm repo add center https://repo.chartcenter.io
Install Chart:
helm install tensorflow-notebook center/stable/tensorflow-notebook
Versions (0)

TensorFlow Notebook Helm Chart

TensorFlow is an open source software library for numerical computation using data flow graphs, and tensorboard is the tool visualizing TensorFlow programs. Using Jupyter notebook to get into TensorFlow and develop models is the great way for data scientist. With these three tools you are able to start your machine learning work in two minutes.

Prerequisites

  • Kubernetes cluster v1.8+

Chart Details

This chart will deploy the followings:

  • Jupyter Notebook with TensorFlow
  • Tensorboard

Installing the Chart

  • To install the chart with the release name notebook:
  $ helm install --name notebook stable/tensorflow-notebook
  • To install with custom values via file : $ helm install --values values.yaml --name notebook stable/tensorflow-notebook

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

  jupyter:
    image:
      repository: tensorflow/tensorflow
      tag: 1.6.0-devel-gpu
      pullPolicy: IfNotPresent
    password: tensorflow
    resources:
      limits:
        nvidia.com/gpu: 1
    requests:
        nvidia.com/gpu: 1
  tensorboard: 
    image:   
      repository: tensorflow/tensorflow
      tag: 1.6.0-devel
      pullPolicy: IfNotPresent
  service:
    type: LoadBalancer

Run TensorFlow Example tensorboard_basic.ipynb

Notice: you should set the log_path /output/training_logs

Check the TensorBoard

Uninstalling the Chart

  • To uninstall/delete the notebook deployment:

    $ helm delete notebook
    

    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 Tensorflow Development chart and their default values. | Parameter | Description | Default | |———–|————-|———| | jupyter.image.repository | TensorFlow Development image repository | tensorflow/tensorflow | | jupyter.image.tag | TensorFlow Development image tag | 1.5.0-devel-gpu | | jupyter.password | The password to access jupyter | mytest | | jupyter.image.pullPolicy | image pullPolicy for the jupyter | IfNotPresent | | tensorboard.image.repository | TensorFlow Development image repository | tensorflow/tensorflow | | tensorboard.image.tag | TensorFlow Development image tag | 1.5.0-devel-gpu | | tensorboard.image.pullPolicy | image pullPolicy for the tensorboard | IfNotPresent | | resources | Set the resource to be allocated and allowed for the Pods | {} | | service.type | service type | LoadBalancer |