charts/bitnami/mxnet

Apache MXNet (Incubating)

Apache MXNet (Incubating) is a deep learning platform that accelerates the transition from research prototyping to production deployment. It is built for full integration into Python that enables you to use it with its libraries and main packages.

TL;DR

$ helm repo add bitnami https://charts.bitnami.com/bitnami
$ helm install my-release bitnami/mxnet

Introduction

This chart bootstraps an Apache MXNet (Incubating) deployment on a Kubernetes cluster using the Helm package manager.

Bitnami charts can be used with Kubeapps for deployment and management of Helm Charts in clusters. This Helm chart has been tested on top of Bitnami Kubernetes Production Runtime (BKPR). Deploy BKPR to get automated TLS certificates, logging and monitoring for your applications.

Prerequisites

• Kubernetes 1.12+
• Helm 3.1.0
• PV provisioner support in the underlying infrastructure
• ReadWriteMany volumes for deployment scaling

Installing the Chart

To install the chart with the release name my-release:

$ helm repo add bitnami https://charts.bitnami.com/bitnami
$ helm install my-release bitnami/mxnet

These commands deploy Apache MXNet (Incubating) on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured.

Tip

: List all releases using helm list

Uninstalling the Chart

To uninstall/delete the my-release deployment:

$ helm delete my-release

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

Parameters

The following table lists the configurable parameters of the Mxnet chart and their default values.

Global Parameters

Parameter	Description	Default
global.imageRegistry	Global Docker image registry	nil
global.imagePullSecrets	Global Docker registry secret names as an array	[] (does not add image pull secrets to deployed pods)
global.storageClass	Global storage class for dynamic provisioning	nil

Common parameters

Parameter	Description	Default
nameOverride	String to partially override common.names.fullname	nil
fullnameOverride	String to fully override common.names.fullname	nil

Common Mxnet parameters

Parameter	Description	Default
image.registry	Apache MXNet (Incubating) image registry	docker.io
image.repository	Apache MXNet (Incubating) image name	bitnami/mxnet
image.tag	Apache MXNet (Incubating) image tag	{TAG_NAME}
image.pullPolicy	Image pull policy	IfNotPresent
image.pullSecrets	Specify docker-registry secret names as an array	[] (does not add image pull secrets to deployed pods)
image.debug	Specify if debug logs should be enabled	false
git.registry	Git image registry	docker.io
git.repository	Git image name	bitnami/git
git.tag	Git image tag	{TAG_NAME}
git.pullPolicy	Git image pull policy	IfNotPresent
git.pullSecrets	Specify docker-registry secret names as an array	[] (does not add image pull secrets to deployed pods)
volumePermissions.enabled	Enable init container that changes volume permissions in the data directory	false
volumePermissions.image.registry	Init container volume-permissions image registry	docker.io
volumePermissions.image.repository	Init container volume-permissions image name	bitnami/bitnami-shell
volumePermissions.image.tag	Init container volume-permissions image tag	"10"
volumePermissions.image.pullPolicy	Init container volume-permissions image pull policy	Always
volumePermissions.resources	Init container resource requests/limit	nil
entrypoint.file	Main entrypoint to your application. If not specified, it will be a sleep infinity command	''
entrypoint.args	Args required by your entrypoint	nil
entrypoint.workDir	Working directory for launching the entrypoint	'/app'
podManagementPolicy	StatefulSet (worker and server nodes) pod management policy	Parallel
mode	Run Apache MXNet (Incubating) in standalone or distributed mode (possible values: standalone, distributed)	standalone
hostAliases	Add deployment host aliases	[]
commonExtraEnvVars	Extra environment variables to add to server, scheduler and worker nodes	nil
configMap	Config map that contains the files you want to load in Apache MXNet (Incubating)	nil
cloneFilesFromGit.enabled	Enable in order to download files from git repository	false
cloneFilesFromGit.repository	Repository that holds the files	nil
cloneFilesFromGit.revision	Revision from the repository to checkout	master
cloneFilesFromGit.extraVolumeMounts	Add extra volume mounts for the GIT container	[]
existingSecret	Name of a secret with sensitive data to mount in the pods	nil
service.type	Kubernetes service type	ClusterIP
resources.limits	The resources limits for the Mxnet container	{}
resources.requests	The requested resources for the Mxnet container	{}
podAffinityPreset	Pod affinity preset. Ignored if affinity is set. Allowed values: soft or hard	""
podAntiAffinityPreset	Pod anti-affinity preset. Ignored if affinity is set. Allowed values: soft or hard	soft
nodeAffinityPreset.type	Node affinity preset type. Ignored if affinity is set. Allowed values: soft or hard	""
nodeAffinityPreset.key	Node label key to match Ignored if affinity is set.	""
nodeAffinityPreset.values	Node label values to match. Ignored if affinity is set.	[]
affinity	Affinity for pod assignment	{} (evaluated as a template)
nodeSelector	Node labels for pod assignment	{} (evaluated as a template)
tolerations	Tolerations for pod assignment	[] (evaluated as a template)
securityContext.enabled	Enable security context	true
securityContext.fsGroup	Group ID for the container	1001
securityContext.runAsUser	User ID for the container	1001
livenessProbe.enabled	Enable/disable the Liveness probe	true
livenessProbe.initialDelaySeconds	Delay before liveness probe is initiated	5
livenessProbe.periodSeconds	How often to perform the probe	5
livenessProbe.timeoutSeconds	When the probe times out	5
livenessProbe.successThreshold	Minimum consecutive successes for the probe to be considered successful after having failed.	1
livenessProbe.failureThreshold	Minimum consecutive failures for the probe to be considered failed after having succeeded.	5
readinessProbe.enabled	Enable/disable the Readiness probe	true
readinessProbe.initialDelaySeconds	Delay before readiness probe is initiated	5
readinessProbe.periodSeconds	How often to perform the probe	5
readinessProbe.timeoutSeconds	When the probe times out	1
readinessProbe.successThreshold	Minimum consecutive successes for the probe to be considered successful after having failed.	1
readinessProbe.failureThreshold	Minimum consecutive failures for the probe to be considered failed after having succeeded.	5
persistence.enabled	Use a PVC to persist data	false
persistence.mountPath	Path to mount the volume at	/bitnami/mxnet
persistence.storageClass	Storage class of backing PVC	nil (uses alpha storage class annotation)
persistence.accessMode	Use volume as ReadOnly or ReadWrite	ReadWriteOnce
persistence.size	Size of data volume	8Gi
persistence.annotations	Persistent Volume annotations	{}
sidecars	Attach additional containers to the pods (scheduler, worker and server nodes)	[]
initContainers	Attach additional init containers to the pods (scheduler, worker and server nodes)	[]
extraVolumes	Array to add extra volumes	[] (evaluated as a template)
extraVolumeMounts	Array to add extra mount	[] (evaluated as a template)

Mxnet Server parameters (only for distributed mode)

Parameter	Description	Default
server.replicaCount	Number of Server nodes that will execute your code	1
server.extraEnvVars	Extra environment variables to add to the Server nodes	[]
server.hostAliases	Add deployment host aliases	[]
server.podAffinityPreset	Mxnet Server pod affinity preset. Ignored if affinity is set. Allowed values: soft or hard	""
server.podAntiAffinityPreset	Mxnet Server pod anti-affinity preset. Ignored if affinity is set. Allowed values: soft or hard	soft
server.nodeAffinityPreset.type	Mxnet Server node affinity preset type. Ignored if affinity is set. Allowed values: soft or hard	""
server.nodeAffinityPreset.key	Mxnet Server node label key to match Ignored if affinity is set.	""
server.nodeAffinityPreset.values	Mxnet Server node label values to match. Ignored if affinity is set.	[]
server.affinity	Mxnet Server affinity for pod assignment	{} (evaluated as a template)
server.nodeSelector	Mxnet Server node labels for pod assignment	{} (evaluated as a template)
server.tolerations	Mxnet Server tolerations for pod assignment	[] (evaluated as a template)
server.resources.limits	The resources limits for the Mxnet Server container	{}
server.resources.requests	The requested resources for the Mxnet Server container	{}

Mxnet Worker parameters (only for distributed mode)

Parameter	Description	Default
worker.replicaCount	Number of Worker nodes that will execute your code	1
worker.extraEnvVars	Extra environment variables to add to the Server nodes	[]
worker.hostAliases	Add deployment host aliases	[]
worker.podAffinityPreset	Mxnet Worker pod affinity preset. Ignored if affinity is set. Allowed values: soft or hard	""
worker.podAntiAffinityPreset	Mxnet Worker pod anti-affinity preset. Ignored if affinity is set. Allowed values: soft or hard	soft
worker.nodeAffinityPreset.type	Mxnet Worker node affinity preset type. Ignored if affinity is set. Allowed values: soft or hard	""
worker.nodeAffinityPreset.key	Mxnet Worker node label key to match Ignored if affinity is set.	""
worker.nodeAffinityPreset.values	Mxnet Worker node label values to match. Ignored if affinity is set.	[]
worker.affinity	Mxnet Worker affinity for pod assignment	{} (evaluated as a template)
worker.nodeSelector	Mxnet Worker node labels for pod assignment	{} (evaluated as a template)
worker.tolerations	Mxnet Worker tolerations for pod assignment	[] (evaluated as a template)
worker.resources.limits	The resources limits for the Mxnet Worker container	{}
worker.resources.requests	The requested resources for the Mxnet Worker container	{}

Mxnet Scheduler parameters (only for distributed mode)

Parameter	Description	Default
scheduler.replicaCount	Number of Scheduler nodes that will execute your code	1
scheduler.extraEnvVars	Extra environment variables to add to the Server nodes	[]
scheduler.hostAliases	Add deployment host aliases	[]
scheduler.podAffinityPreset	Mxnet Scheduler pod affinity preset. Ignored if affinity is set. Allowed values: soft or hard	""
scheduler.podAntiAffinityPreset	Mxnet Scheduler pod anti-affinity preset. Ignored if affinity is set. Allowed values: soft or hard	soft
scheduler.nodeAffinityPreset.type	Mxnet Scheduler node affinity preset type. Ignored if affinity is set. Allowed values: soft or hard	""
scheduler.nodeAffinityPreset.key	Mxnet Scheduler node label key to match Ignored if affinity is set.	""
scheduler.nodeAffinityPreset.values	Mxnet Scheduler node label values to match. Ignored if affinity is set.	[]
scheduler.affinity	Mxnet Scheduler affinity for pod assignment	{} (evaluated as a template)
scheduler.nodeSelector	Mxnet Scheduler node labels for pod assignment	{} (evaluated as a template)
scheduler.tolerations	Mxnet Scheduler tolerations for pod assignment	[] (evaluated as a template)
scheduler.resources.limits	The resources limits for the Mxnet Scheduler container	{}
scheduler.resources.requests	The requested resources for the Mxnet Scheduler container	{}

Specify each parameter using the --set key=value[,key=value] argument to helm install. For example,

$ helm install my-release \
  --set mode=distributed \
  --set server.replicaCount=2 \
  --set worker.replicaCount=3 \
    bitnami/mxnet

The above command creates 6 pods for Apache MXNet (Incubating): one scheduler, two servers, and three workers.

Alternatively, a YAML file that specifies the values for the parameters can be provided while installing the chart. For example,

$ helm install my-release -f values.yaml bitnami/mxnet

Tip

: You can use the default values.yaml

Configuration and installation details

Rolling VS Immutable tags

It is strongly recommended to use immutable tags in a production environment. This ensures your deployment does not change automatically if the same tag is updated with a different image.

Bitnami will release a new chart updating its containers if a new version of the main container, significant changes, or critical vulnerabilities exist.

Loading your files

The Apache MXNet (Incubating) chart supports three different ways to load your files. In order of priority, they are:

1. Existing config map
2. Files under the files directory
3. Cloning a git repository

This means that if you specify a config map with your files, it won't look for the files/ directory nor the git repository.

In order to use use an existing config map you can set the configMap=my-config-map parameter.

To load your files from the files/ directory you don't have to set any option. Just copy your files inside and don't specify a ConfigMap.

Finally, if you want to clone a git repository you can use the following parameters:

cloneFilesFromGit.enabled=true
cloneFilesFromGit.repository=https://github.com/my-user/my-repo
cloneFilesFromGit.revision=master

In case you want to add a file that includes sensitive information, pass a secret object using the existingSecret parameter. All the files in the secret will be mounted in the /secrets folder.

Distributed training example

We will use the gluon example from the Apache MXNet (Incubating) official repository. Launch it with the following values:

mode=distributed
cloneFilesFromGit.enabled=true
cloneFilesFromGit.repository=https://github.com/apache/incubator-mxnet.git
cloneFilesFromGit.revision=master
entrypoint.file=image_classification.py
entrypoint.args="--dataset cifar10 --model vgg11 --epochs 1 --kvstore dist_sync"
entrypoint.workDir=/app/example/gluon/

Check the logs of the worker node:

INFO:root:Starting new image-classification task:, Namespace(batch_norm=False, batch_size=32, builtin_profiler=0, data_dir='', dataset='cifar10', dtype='float32', epochs=1, gpus='', kvstore='dist_sync', log_interval=50, lr=0.1, lr_factor=0.1, lr_steps='30,60,90', mode=None, model='vgg11', momentum=0.9, num_workers=4, prefix='', profile=False, resume='', save_frequency=10, seed=123, start_epoch=0, use_pretrained=False, use_thumbnail=False, wd=0.0001)
INFO:root:downloaded http://data.mxnet.io/mxnet/data/cifar10.zip into data/cifar10.zip successfully
[10:05:40] src/io/iter_image_recordio_2.cc:172: ImageRecordIOParser2: data/cifar/train.rec, use 1 threads for decoding..
[10:05:45] src/io/iter_image_recordio_2.cc:172: ImageRecordIOParser2: data/cifar/test.rec, use 1 threads for decoding..

If you want to increase the verbosity, set the environment variable PS_VERBOSE=1 or PS_VERBOSE=2 using the commonEnvVars value.

mode=distributed
cloneFilesFromGit.enabled=true
cloneFilesFromGit.repository=https://github.com/apache/incubator-mxnet.git
cloneFilesFromGit.revision=master
entrypoint.file=image_classification.py
entrypoint.args="--dataset cifar10 --model vgg11 --epochs 1 --kvstore dist_sync"
entrypoint.workDir=/app/example/gluon/
commonExtraEnvVars[0].name=PS_VERBOSE
commonExtraEnvVars[0].value=1

You will now see log entries in the scheduler and server nodes.

[14:22:44] src/van.cc:290: Bind to role=scheduler, id=1, ip=10.32.0.11, port=9092, is_recovery=0
[14:22:53] src/van.cc:56: assign rank=9 to node role=worker, ip=10.32.0.17, port=55423, is_recovery=0
[14:22:53] src/van.cc:56: assign rank=11 to node role=worker, ip=10.32.0.16, port=60779, is_recovery=0
[14:22:53] src/van.cc:56: assign rank=13 to node role=worker, ip=10.32.0.15, port=39817, is_recovery=0
[14:22:53] src/van.cc:56: assign rank=15 to node role=worker, ip=10.32.0.14, port=48119, is_recovery=0
[14:22:53] src/van.cc:56: assign rank=8 to node role=server, ip=10.32.0.13, port=56713, is_recovery=0
[14:22:53] src/van.cc:56: assign rank=10 to node role=server, ip=10.32.0.12, port=57099, is_recovery=0
[14:22:53] src/van.cc:83: the scheduler is connected to 4 workers and 2 servers
[14:22:53] src/van.cc:183: Barrier count for 7 : 1
[14:22:53] src/van.cc:183: Barrier count for 7 : 2
[14:22:53] src/van.cc:183: Barrier count for 7 : 3
[14:22:53] src/van.cc:183: Barrier count for 7 : 4
...

Sidecars and Init Containers

If you have a need for additional containers to run within the same pod as Apache MXNet (Incubating) (e.g. an additional metrics or logging exporter), you can do so via the sidecars config parameter. Simply define your container according to the Kubernetes container spec.

sidecars:
- name: your-image-name
  image: your-image
  imagePullPolicy: Always
  ports:
  - name: portname
   containerPort: 1234

Similarly, you can add extra init containers using the initContainers parameter.

initContainers:
- name: your-image-name
  image: your-image
  imagePullPolicy: Always
  ports:
  - name: portname
   containerPort: 1234

Persistence

The Bitnami Apache MXNet (Incubating) image can persist data. If enabled, the persisted path is /bitnami/mxnet by default.

The chart mounts a Persistent Volume at this location. The volume is created using dynamic volume provisioning.

Adjust permissions of persistent volume mountpoint

As the image run as non-root by default, it is necessary to adjust the ownership of the persistent volume so that the container can write data into it.

By default, the chart is configured to use Kubernetes Security Context to automatically change the ownership of the volume. However, this feature does not work in all Kubernetes distributions. As an alternative, this chart supports using an initContainer to change the ownership of the volume before mounting it in the final destination.

You can enable this initContainer by setting volumePermissions.enabled to true.

Setting Pod's affinity

This chart allows you to set your custom affinity using the XXX.affinity parameter(s). Find more information about Pod's affinity in the kubernetes documentation.

As an alternative, you can use of the preset configurations for pod affinity, pod anti-affinity, and node affinity available at the bitnami/common chart. To do so, set the XXX.podAffinityPreset, XXX.podAntiAffinityPreset, or XXX.nodeAffinityPreset parameters.

Troubleshooting

Find more information about how to deal with common errors related to Bitnami’s Helm charts in this troubleshooting guide.

Upgrading

To 2.1.0

Some parameters disappeared in favor of new ones:

• schedulerExtraEnvVars and schedulerPort -> deprecated in favor of scheduler.extraEnvVars and scheduler.port, respectively.
• serverExtraEnvVars and serverCount -> deprecated in favor of server.extraEnvVars and server.replicaCount, respectively.
• workerExtraEnvVars and workerCount -> deprecated in favor of worker.extraEnvVars and worker.replicaCount, respectively.

This version also introduces bitnami/common, a library chart as a dependency. More documentation about this new utility could be found here. Please, make sure that you have updated the chart dependencies before executing any upgrade.

To 2.0.0

On November 13, 2020, Helm v2 support was formally finished, this major version is the result of the required changes applied to the Helm Chart to be able to incorporate the different features added in Helm v3 and to be consistent with the Helm project itself regarding the Helm v2 EOL.

What changes were introduced in this major version?

• Previous versions of this Helm Chart use apiVersion: v1 (installable by both Helm 2 and 3), this Helm Chart was updated to apiVersion: v2 (installable by Helm 3 only). Here you can find more information about the apiVersion field.
• The different fields present in the Chart.yaml file has been ordered alphabetically in a homogeneous way for all the Bitnami Helm Charts

Considerations when upgrading to this version

• If you want to upgrade to this version from a previous one installed with Helm v3, you shouldn't face any issues
• If you want to upgrade to this version using Helm v2, this scenario is not supported as this version doesn't support Helm v2 anymore
• If you installed the previous version with Helm v2 and wants to upgrade to this version with Helm v3, please refer to the official Helm documentation about migrating from Helm v2 to v3

Useful links

• https://docs.bitnami.com/tutorials/resolve-helm2-helm3-post-migration-issues/
• https://helm.sh/docs/topics/v2_v3_migration/
• https://helm.sh/blog/migrate-from-helm-v2-to-helm-v3/