tensorflow

package
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Published: Jun 3, 2019 License: Apache-2.0 Imports: 39 Imported by: 0

Documentation

Overview

Package controller provides a Kubernetes controller for a TFJob resource.

Package controller provides a Kubernetes controller for a TFJob resource.

Package controller provides a Kubernetes controller for a TFJob resource.

Package controller provides a Kubernetes controller for a TFJob resource.

Package controller provides a Kubernetes controller for a TFJob resource.

Index

Constants

View Source
const (
	// EnvCustomClusterDomain is the custom defined cluster domain, such as "svc.cluster.local".
	// Ref: https://kubernetes.io/docs/concepts/services-networking/dns-pod-service/#a-records
	EnvCustomClusterDomain = "CUSTOM_CLUSTER_DOMAIN"
)

Variables

View Source
var (
	// KeyFunc is the short name to DeletionHandlingMetaNamespaceKeyFunc.
	// IndexerInformer uses a delta queue, therefore for deletes we have to use this
	// key function but it should be just fine for non delete events.
	KeyFunc = cache.DeletionHandlingMetaNamespaceKeyFunc

	// DefaultTFControllerConfiguration is the suggested tf-operator configuration for production.
	DefaultTFControllerConfiguration = jobcontroller.JobControllerConfiguration{
		ReconcilerSyncLoopPeriod: metav1.Duration{Duration: 15 * time.Second},
		EnableGangScheduling:     false,
	}
)

Functions

func ContainChieforMasterSpec

func ContainChieforMasterSpec(tfJob *tfv1.TFJob) bool

ContainChieforMasterSpec returns true if the tfjob contains chief or master spec.

func GetPortFromTFJob

func GetPortFromTFJob(tfJob *tfv1.TFJob, rtype tfv1.TFReplicaType) (int32, error)

GetPortFromTFJob gets the port of tensorflow container.

func NewUnstructuredTFJobInformer

func NewUnstructuredTFJobInformer(restConfig *restclientset.Config, namespace string) tfjobinformersv1.TFJobInformer

Types

type ClusterSpec

type ClusterSpec map[string][]string

ClusterSpec represents a cluster TensorFlow specification. https://www.tensorflow.org/deploy/distributed#create_a_tftrainclusterspec_to_describe_the_cluster It is a map from job names to network addresses.

type TFConfig

type TFConfig struct {
	// Cluster represents a TensorFlow ClusterSpec.
	// See: https://www.tensorflow.org/api_docs/python/tf/train/ClusterSpec
	Cluster ClusterSpec `json:"cluster"`
	Task    TaskSpec    `json:"task"`
	// Environment is used by tensorflow.contrib.learn.python.learn in versions <= 1.3
	// TODO(jlewi): I don't think it is used in versions TF >- 1.4. So we can eventually get rid of it.
	Environment string `json:"environment"`
}

TFConfig is a struct representing the distributed TensorFlow config. This struct is turned into an environment variable TF_CONFIG which is used by TensorFlow processes to configure themselves. https://www.tensorflow.org/api_docs/python/tf/estimator/RunConfig#methods https://cloud.google.com/ml-engine/docs/tensorflow/distributed-training-details

type TFController

type TFController struct {
	jobcontroller.JobController
	// contains filtered or unexported fields
}

TFController is the type for TFJob Controller, which manages the lifecycle of TFJobs.

func NewTFController

func NewTFController(

	tfJobInformer tfjobinformersv1.TFJobInformer,
	kubeClientSet kubeclientset.Interface,
	kubeBatchClientSet kubebatchclient.Interface,
	tfJobClientSet tfjobclientset.Interface,
	kubeInformerFactory kubeinformers.SharedInformerFactory,

	tfJobInformerFactory tfjobinformers.SharedInformerFactory,
	option options.ServerOption) *TFController

NewTFController returns a new TFJob controller.

func (*TFController) ControllerName

func (tc *TFController) ControllerName() string

func (*TFController) GetAPIGroupVersion

func (tc *TFController) GetAPIGroupVersion() schema.GroupVersion

func (*TFController) GetAPIGroupVersionKind

func (tc *TFController) GetAPIGroupVersionKind() schema.GroupVersionKind

func (*TFController) GetGroupNameLabelKey

func (tc *TFController) GetGroupNameLabelKey() string

func (*TFController) GetGroupNameLabelValue

func (tc *TFController) GetGroupNameLabelValue() string

func (*TFController) GetJobFromAPIClient

func (tc *TFController) GetJobFromAPIClient(namespace, name string) (metav1.Object, error)

func (*TFController) GetJobFromInformerCache

func (tc *TFController) GetJobFromInformerCache(namespace, name string) (metav1.Object, error)

func (*TFController) GetJobNameLabelKey

func (tc *TFController) GetJobNameLabelKey() string

func (*TFController) GetJobRoleKey

func (tc *TFController) GetJobRoleKey() string

func (*TFController) GetReplicaIndexLabelKey

func (tc *TFController) GetReplicaIndexLabelKey() string

func (*TFController) GetReplicaTypeLabelKey

func (tc *TFController) GetReplicaTypeLabelKey() string

func (*TFController) NewTFJobInformer

func (tc *TFController) NewTFJobInformer(tfJobInformerFactory tfjobinformers.SharedInformerFactory) tfjobinformersv1.TFJobInformer

NewTFJobInformer returns TFJobInformer from the given factory.

func (*TFController) Run

func (tc *TFController) Run(threadiness int, stopCh <-chan struct{}) error

Run will set up the event handlers for types we are interested in, as well as syncing informer caches and starting workers. It will block until stopCh is closed, at which point it will shutdown the workqueue and wait for workers to finish processing their current work items.

type TaskSpec

type TaskSpec struct {
	Type  string `json:"type"`
	Index int    `json:"index"`
}

TaskSpec is the specification for a task (PS or worker) of the TFJob.

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