Interface CustomJobSpecOrBuilder (2.7.4)

Version 2.7.4

• 3.55.0 (latest)
• 3.54.0
• 3.53.0
• 3.52.0
• 3.50.0
• 3.49.0
• 3.48.0
• 3.47.0
• 3.46.0
• 3.45.0
• 3.44.0
• 3.43.0
• 3.42.0
• 3.41.0
• 3.40.0
• 3.38.0
• 3.37.0
• 3.36.0
• 3.35.0
• 3.34.0
• 3.33.0
• 3.32.0
• 3.31.0
• 3.30.0
• 3.29.0
• 3.28.0
• 3.25.0
• 3.24.0
• 3.23.0
• 3.22.0
• 3.21.0
• 3.20.0
• 3.19.0
• 3.18.0
• 3.17.0
• 3.16.0
• 3.15.0
• 3.14.0
• 3.13.0
• 3.12.0
• 3.11.0
• 3.10.0
• 3.9.0
• 3.8.0
• 3.7.0
• 3.6.0
• 3.5.0
• 3.4.2
• 3.3.0
• 3.2.0
• 3.0.0
• 2.9.8
• 2.8.9
• 2.7.4
• 2.5.3
• 2.4.0

public interface CustomJobSpecOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getBaseOutputDirectory()

public abstract GcsDestination getBaseOutputDirectory()

The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob:

• AIP_MODEL_DIR = <base_output_directory>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/logs/ For CustomJob backing a Trial of HyperparameterTuningJob:
• AIP_MODEL_DIR = <base_output_directory>/<trial_id>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/<trial_id>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/<trial_id>/logs/

.google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;

Returns

Type	Description
GcsDestination	The baseOutputDirectory.

getBaseOutputDirectoryOrBuilder()

public abstract GcsDestinationOrBuilder getBaseOutputDirectoryOrBuilder()

The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob:

• AIP_MODEL_DIR = <base_output_directory>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/logs/ For CustomJob backing a Trial of HyperparameterTuningJob:
• AIP_MODEL_DIR = <base_output_directory>/<trial_id>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/<trial_id>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/<trial_id>/logs/

.google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;

Returns

Type	Description
GcsDestinationOrBuilder

getEnableWebAccess()

public abstract boolean getEnableWebAccess()

Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

bool enable_web_access = 10 [(.google.api.field_behavior) = OPTIONAL];

Returns

Type	Description
boolean	The enableWebAccess.

getNetwork()

public abstract String getNetwork()

The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.

string network = 5 [(.google.api.resource_reference) = { ... }

Returns

Type	Description
String	The network.

getNetworkBytes()

public abstract ByteString getNetworkBytes()

The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.

string network = 5 [(.google.api.resource_reference) = { ... }

Returns

Type	Description
ByteString	The bytes for network.

getScheduling()

public abstract Scheduling getScheduling()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1.Scheduling scheduling = 3;

Returns

Type	Description
Scheduling	The scheduling.

getSchedulingOrBuilder()

public abstract SchedulingOrBuilder getSchedulingOrBuilder()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1.Scheduling scheduling = 3;

Returns

Type	Description
SchedulingOrBuilder

getServiceAccount()

public abstract String getServiceAccount()

Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.

string service_account = 4;

Returns

Type	Description
String	The serviceAccount.

getServiceAccountBytes()

public abstract ByteString getServiceAccountBytes()

Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.

string service_account = 4;

Returns

Type	Description
ByteString	The bytes for serviceAccount.

getTensorboard()

public abstract String getTensorboard()

Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}

string tensorboard = 7 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns

Type	Description
String	The tensorboard.

getTensorboardBytes()

public abstract ByteString getTensorboardBytes()

Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}

string tensorboard = 7 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns

Type	Description
ByteString	The bytes for tensorboard.

getWorkerPoolSpecs(int index)

public abstract WorkerPoolSpec getWorkerPoolSpecs(int index)

Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter

Name	Description
index	int

Returns

Type	Description
WorkerPoolSpec

getWorkerPoolSpecsCount()

public abstract int getWorkerPoolSpecsCount()

Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns

Type	Description
int

getWorkerPoolSpecsList()

public abstract List<WorkerPoolSpec> getWorkerPoolSpecsList()

Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns

Type	Description
List<WorkerPoolSpec>

getWorkerPoolSpecsOrBuilder(int index)

public abstract WorkerPoolSpecOrBuilder getWorkerPoolSpecsOrBuilder(int index)

Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter

Name	Description
index	int

Returns

Type	Description
WorkerPoolSpecOrBuilder

getWorkerPoolSpecsOrBuilderList()

public abstract List<? extends WorkerPoolSpecOrBuilder> getWorkerPoolSpecsOrBuilderList()

Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns

Type	Description
List<? extends com.google.cloud.aiplatform.v1.WorkerPoolSpecOrBuilder>

hasBaseOutputDirectory()

public abstract boolean hasBaseOutputDirectory()

The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob:

• AIP_MODEL_DIR = <base_output_directory>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/logs/ For CustomJob backing a Trial of HyperparameterTuningJob:
• AIP_MODEL_DIR = <base_output_directory>/<trial_id>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/<trial_id>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/<trial_id>/logs/

.google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;

Returns

Type	Description
boolean	Whether the baseOutputDirectory field is set.

hasScheduling()

public abstract boolean hasScheduling()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1.Scheduling scheduling = 3;

Returns

Type	Description
boolean	Whether the scheduling field is set.