BatchAIJob (Microsoft Azure Management Libraries for Java 1.36.0)

All Superinterfaces:

com.microsoft.azure.management.resources.fluentcore.arm.models.HasId, com.microsoft.azure.management.resources.fluentcore.model.HasInner<com.microsoft.azure.management.batchai.implementation.JobInner>, com.microsoft.azure.management.resources.fluentcore.arm.models.HasName, com.microsoft.azure.management.resources.fluentcore.model.Indexable, com.microsoft.azure.management.resources.fluentcore.model.Refreshable<BatchAIJob>
```
@Beta(value=V1_6_0)
public interface BatchAIJob
extends com.microsoft.azure.management.resources.fluentcore.model.HasInner<com.microsoft.azure.management.batchai.implementation.JobInner>, com.microsoft.azure.management.resources.fluentcore.model.Indexable, com.microsoft.azure.management.resources.fluentcore.arm.models.HasId, com.microsoft.azure.management.resources.fluentcore.arm.models.HasName, com.microsoft.azure.management.resources.fluentcore.model.Refreshable<BatchAIJob>
```
Client-side representation of Batch AI Job object, associated with Batch AI Cluster.

Nested Class Summary

Nested Classes
Modifier and Type	Interface and Description
`static interface`	`BatchAIJob.Definition` The entirety of the Batch AI job definition.
`static interface`	`BatchAIJob.DefinitionStages` Grouping of Batch AI job definition stages.

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method and Description
`CaffeSettings`	`caffeSettings()`
`ChainerSettings`	`chainerSettings()`
`ResourceId`	`cluster()`
`CNTKsettings`	`cntkSettings()`
`JobPropertiesConstraints`	`constraints()`
`ContainerSettings`	`containerSettings()`
`org.joda.time.DateTime`	`creationTime()`
`CustomToolkitSettings`	`customToolkitSettings()`
`List<EnvironmentVariable>`	`environmentVariables()`
`JobPropertiesExecutionInfo`	`executionInfo()`
`ExecutionState`	`executionState()` Gets the current state of the job.
`org.joda.time.DateTime`	`executionStateTransitionTime()`
`BatchAIExperiment`	`experiment()`
`List<InputDirectory>`	`inputDirectories()`
`String`	`jobOutputDirectoryPathSegment()`
`JobPreparation`	`jobPreparation()`
`com.microsoft.azure.PagedList<OutputFile>`	`listFiles(String outputDirectoryId)` List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
`com.microsoft.azure.PagedList<OutputFile>`	`listFiles(String outputDirectoryId, String directory, Integer linkExpiryMinutes, Integer maxResults)` List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
`rx.Observable<OutputFile>`	`listFilesAsync(String outputDirectoryId)` List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
`rx.Observable<OutputFile>`	`listFilesAsync(String outputDirectoryId, String directory, Integer linkExpiryMinutes, Integer maxResults)` List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
`com.microsoft.azure.PagedList<RemoteLoginInformation>`	`listRemoteLoginInformation()` Gets a list of currently existing nodes which were used for the Job execution.
`rx.Observable<RemoteLoginInformation>`	`listRemoteLoginInformationAsync()` Gets a list of currently existing nodes which were used for the Job execution.
`MountVolumes`	`mountVolumes()`
`int`	`nodeCount()`
`List<OutputDirectory>`	`outputDirectories()`
`ProvisioningState`	`provisioningState()`
`org.joda.time.DateTime`	`provisioningStateTransitionTime()` The time at which the job entered its current provisioning state.
`PyTorchSettings`	`pyTorchSettings()`
`JobPriority`	`schedulingPriority()`
`List<EnvironmentVariableWithSecretValue>`	`secrets()`
`String`	`stdOutErrPathPrefix()`
`TensorFlowSettings`	`tensorFlowSettings()`
`void`	`terminate()` Terminates a job.
`rx.Completable`	`terminateAsync()` Terminates a job.
`ToolType`	`toolType()`

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.model.HasInner
inner

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.model.Indexable
key

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.arm.models.HasId
id

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.arm.models.HasName
name

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.model.Refreshable
refresh, refreshAsync

- Method Detail
  - terminate
```
void terminate()
```
    Terminates a job.
  - terminateAsync
```
rx.Completable terminateAsync()
```
    Terminates a job.
    
    Returns:
    
    a representation of the deferred computation of this call
  - listFiles
```
com.microsoft.azure.PagedList<OutputFile> listFiles(String outputDirectoryId)
```
    List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
    
    Parameters:
    
    outputDirectoryId - Id of the job output directory. This is the OutputDirectory-->id parameter that is given by the user during Create Job.
    
    Returns:
    
    list of files inside the given output directory
  - listFilesAsync
```
rx.Observable<OutputFile> listFilesAsync(String outputDirectoryId)
```
    List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
    
    Parameters:
    
    outputDirectoryId - Id of the job output directory. This is the OutputDirectory-->id parameter that is given by the user during Create Job.
    
    Returns:
    
    an observable that emits output file information
  - listFiles
```
com.microsoft.azure.PagedList<OutputFile> listFiles(String outputDirectoryId,
                                                    String directory,
                                                    Integer linkExpiryMinutes,
                                                    Integer maxResults)
```
    List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
    
    Parameters:
    
    outputDirectoryId - Id of the job output directory. This is the OutputDirectory-->id parameter that is given by the user during Create Job.
    
    directory - the path to the directory
    
    linkExpiryMinutes - the number of minutes after which the download link will expire
    
    maxResults - the maximum number of items to return in the response. A maximum of 1000 files can be returned
    
    Returns:
    
    list of files inside the given output directory
  - listFilesAsync
```
rx.Observable<OutputFile> listFilesAsync(String outputDirectoryId,
                                         String directory,
                                         Integer linkExpiryMinutes,
                                         Integer maxResults)
```
    List all files inside the given output directory (Only if the output directory is on Azure File Share or Azure Storage container).
    
    Parameters:
    
    outputDirectoryId - Id of the job output directory. This is the OutputDirectory-->id parameter that is given by the user during Create Job.
    
    directory - the path to the directory
    
    linkExpiryMinutes - the number of minutes after which the download link will expire
    
    maxResults - the maximum number of items to return in the response. A maximum of 1000 files can be returned
    
    Returns:
    
    an observable that emits output file information
  - listRemoteLoginInformation
```
com.microsoft.azure.PagedList<RemoteLoginInformation> listRemoteLoginInformation()
```
    Gets a list of currently existing nodes which were used for the Job execution. The returned information contains the node ID, its public IP and SSH port.
    
    Returns:
    
    list of remote login details
  - listRemoteLoginInformationAsync
```
rx.Observable<RemoteLoginInformation> listRemoteLoginInformationAsync()
```
    Gets a list of currently existing nodes which were used for the Job execution. The returned information contains the node ID, its public IP and SSH port.
    
    Returns:
    
    an observable that emits remote login information
  - schedulingPriority
```
JobPriority schedulingPriority()
```
    Returns:
    
    priority associated with the job. Priority values can range from -1000 to 1000, with -1000 being the lowest priority and 1000 being the highest priority. The default value is 0.
  - cluster
```
ResourceId cluster()
```
    Returns:
    
    the Id of the cluster on which this job will run.
  - mountVolumes
```
MountVolumes mountVolumes()
```
    Returns:
    
    information on mount volumes to be used by the job. These volumes will be mounted before the job execution and will be unmouted after the job completion. The volumes will be mounted at location specified by $AZ_BATCHAI_JOB_MOUNT_ROOT environment variable.
  - jobOutputDirectoryPathSegment
```
String jobOutputDirectoryPathSegment()
```
    Returns:
    
    a segment of job's output directories path created by BatchAI. Batch AI creates job's output directories under an unique path to avoid conflicts between jobs. This value contains a path segment generated by Batch AI to make the path unique and can be used to find the output directory on the node or mounted filesystem.
  - nodeCount
```
int nodeCount()
```
    Returns:
    
    number of compute nodes to run the job on. The job will be gang scheduled on that many compute nodes.
  - containerSettings
```
ContainerSettings containerSettings()
```
    Returns:
    
    the settings for the container to run the job. If not provided, the job will run on the VM.
  - toolType
```
ToolType toolType()
```
    Returns:
    
    The toolkit type of this job
  - cntkSettings
```
CNTKsettings cntkSettings()
```
    Returns:
    
    the settings for CNTK (aka Microsoft Cognitive Toolkit) job
  - pyTorchSettings
```
PyTorchSettings pyTorchSettings()
```
    Returns:
    
    the settings for pyTorch job
  - tensorFlowSettings
```
TensorFlowSettings tensorFlowSettings()
```
    Returns:
    
    the settings for Tensor Flow job
  - caffeSettings
```
CaffeSettings caffeSettings()
```
    Returns:
    
    the settings for Caffe job.
  - chainerSettings
```
ChainerSettings chainerSettings()
```
    Returns:
    
    the settings for Chainer job.
  - customToolkitSettings
```
CustomToolkitSettings customToolkitSettings()
```
    Returns:
    
    the settings for custom tool kit job
  - jobPreparation
```
JobPreparation jobPreparation()
```
    Returns:
    
    the actions to be performed before tool kit is launched. The specified actions will run on all the nodes that are part of the job.
  - stdOutErrPathPrefix
```
String stdOutErrPathPrefix()
```
    Returns:
    
    the path where the Batch AI service will upload stdout and stderror of the job.
  - inputDirectories
```
List<InputDirectory> inputDirectories()
```
    Returns:
    
    the list of input directories for the Job
  - outputDirectories
```
List<OutputDirectory> outputDirectories()
```
    Returns:
    
    the list of output directories where the models will be created
  - environmentVariables
```
List<EnvironmentVariable> environmentVariables()
```
    Returns:
    
    Additional environment variables to be passed to the job. Batch AI services sets the following environment variables for all jobs: AZ_BATCHAI_INPUT_id, AZ_BATCHAI_OUTPUT_id, AZ_BATCHAI_NUM_GPUS_PER_NODE, For distributed TensorFlow jobs, following additional environment variables are set by the Batch AI Service: AZ_BATCHAI_PS_HOSTS, AZ_BATCHAI_WORKER_HOSTS.
  - secrets
```
List<EnvironmentVariableWithSecretValue> secrets()
```
    Returns:
    
    environment variables with secret values to set on the job. Only names are reported, server will never report values of these variables back.
  - constraints
```
JobPropertiesConstraints constraints()
```
    Returns:
    
    constraints associated with the Job.
  - creationTime
```
org.joda.time.DateTime creationTime()
```
    Returns:
    
    the creation time of the job
  - provisioningState
```
ProvisioningState provisioningState()
```
    Returns:
    
    the provisioned state of the Batch AI job
  - provisioningStateTransitionTime
```
org.joda.time.DateTime provisioningStateTransitionTime()
```
    The time at which the job entered its current provisioning state.
    
    Returns:
    
    the time at which the job entered its current provisioning state
  - executionState
```
ExecutionState executionState()
```
    Gets the current state of the job. Possible values are: queued - The job is queued and able to run. A job enters this state when it is created, or when it is awaiting a retry after a failed run. running - The job is running on a compute cluster. This includes job-level preparation such as downloading resource files or set up container specified on the job - it does not necessarily mean that the job command line has started executing. terminating - The job is terminated by the user, the terminate operation is in progress. succeeded - The job has completed running succesfully and exited with exit code 0. failed - The job has finished unsuccessfully (failed with a non-zero exit code) and has exhausted its retry limit. A job is also marked as failed if an error occurred launching the job.
    
    Returns:
    
    the current state of the job
  - executionStateTransitionTime
```
org.joda.time.DateTime executionStateTransitionTime()
```
    Returns:
    
    the time at which the job entered its current execution state
  - executionInfo
```
JobPropertiesExecutionInfo executionInfo()
```
    Returns:
    
    information about the execution of a job in the Azure Batch service.
  - experiment
```
BatchAIExperiment experiment()
```
    Returns:
    
    the experiment information of the job.

                             /**                             
* Copyright (c) Microsoft Corporation. All rights reserved.                             
* Licensed under the MIT License. See License.txt in the project root for                             
* license information.                             
*/

Interface BatchAIJob

Nested Class Summary

Method Summary

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.model.HasInner

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.model.Indexable

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.arm.models.HasId

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.arm.models.HasName

Methods inherited from interface com.microsoft.azure.management.resources.fluentcore.model.Refreshable

Method Detail

terminate

terminateAsync

listFiles

listFilesAsync

listFiles

listFilesAsync

listRemoteLoginInformation

listRemoteLoginInformationAsync

schedulingPriority

cluster

mountVolumes

jobOutputDirectoryPathSegment

nodeCount

containerSettings

toolType

cntkSettings

pyTorchSettings

tensorFlowSettings

caffeSettings

chainerSettings

customToolkitSettings

jobPreparation

stdOutErrPathPrefix

inputDirectories

outputDirectories

environmentVariables

secrets

constraints

creationTime

provisioningState

provisioningStateTransitionTime

executionState

executionStateTransitionTime

executionInfo

experiment