com.google.cloud.aiplatform.v1

Interface CustomJobSpecOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

CustomJobSpec, CustomJobSpec.Builder

public interface CustomJobSpecOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
GcsDestination	getBaseOutputDirectory() The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob.
GcsDestinationOrBuilder	getBaseOutputDirectoryOrBuilder() The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob.
boolean	getEnableWebAccess() Optional.
String	getNetwork() The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered.
com.google.protobuf.ByteString	getNetworkBytes() The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered.
Scheduling	getScheduling() Scheduling options for a CustomJob.
SchedulingOrBuilder	getSchedulingOrBuilder() Scheduling options for a CustomJob.
String	getServiceAccount() Specifies the service account for workload run-as account.
com.google.protobuf.ByteString	getServiceAccountBytes() Specifies the service account for workload run-as account.
WorkerPoolSpec	getWorkerPoolSpecs(int index) Required.
int	getWorkerPoolSpecsCount() Required.
List<WorkerPoolSpec>	getWorkerPoolSpecsList() Required.
WorkerPoolSpecOrBuilder	getWorkerPoolSpecsOrBuilder(int index) Required.
List<? extends WorkerPoolSpecOrBuilder>	getWorkerPoolSpecsOrBuilderList() Required.
boolean	hasBaseOutputDirectory() The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob.
boolean	hasScheduling() Scheduling options for a CustomJob.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getWorkerPoolSpecsList

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];

getWorkerPoolSpecs

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];

getWorkerPoolSpecsCount

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];

getWorkerPoolSpecsOrBuilderList

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];

getWorkerPoolSpecsOrBuilder

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];

hasScheduling

boolean hasScheduling()

 Scheduling options for a CustomJob.
 

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

Returns:

Whether the scheduling field is set.

getScheduling

Scheduling getScheduling()

 Scheduling options for a CustomJob.
 

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

Returns:

The scheduling.

getSchedulingOrBuilder

SchedulingOrBuilder getSchedulingOrBuilder()

 Scheduling options for a CustomJob.
 

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

getServiceAccount

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](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)
 for the CustomJob's project is used.
 

string service_account = 4;

Returns:

The serviceAccount.

getServiceAccountBytes

com.google.protobuf.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](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)
 for the CustomJob's project is used.
 

string service_account = 4;

Returns:

The bytes for serviceAccount.

getNetwork

String getNetwork()

 The full name of the Compute Engine
 [network](/compute/docs/networks-and-firewalls#networks) to which the Job
 should be peered. For example, `projects/12345/global/networks/myVPC`.
 [Format](/compute/docs/reference/rest/v1/networks/insert)
 is of the form `projects/{project}/global/networks/{network}`.
 Where {project} is a project number, as in `12345`, and {network} is a
 network name.
 Private services access must already be configured for the network. If left
 unspecified, the job is not peered with any network.
 

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

Returns:

The network.

getNetworkBytes

com.google.protobuf.ByteString getNetworkBytes()

 The full name of the Compute Engine
 [network](/compute/docs/networks-and-firewalls#networks) to which the Job
 should be peered. For example, `projects/12345/global/networks/myVPC`.
 [Format](/compute/docs/reference/rest/v1/networks/insert)
 is of the form `projects/{project}/global/networks/{network}`.
 Where {project} is a project number, as in `12345`, and {network} is a
 network name.
 Private services access must already be configured for the network. If left
 unspecified, the job is not peered with any network.
 

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

Returns:

The bytes for network.

hasBaseOutputDirectory

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][google.cloud.aiplatform.v1.Trial.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:

Whether the baseOutputDirectory field is set.

getBaseOutputDirectory

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][google.cloud.aiplatform.v1.Trial.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:

The baseOutputDirectory.

getBaseOutputDirectoryOrBuilder

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][google.cloud.aiplatform.v1.Trial.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;

getEnableWebAccess

boolean getEnableWebAccess()

 Optional. Whether you want Vertex AI to enable [interactive shell
 access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell)
 to training containers.
 If set to `true`, you can access interactive shells at the URIs given
 by [CustomJob.web_access_uris][google.cloud.aiplatform.v1.CustomJob.web_access_uris] or [Trial.web_access_uris][google.cloud.aiplatform.v1.Trial.web_access_uris] (within
 [HyperparameterTuningJob.trials][google.cloud.aiplatform.v1.HyperparameterTuningJob.trials]).
 

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

Returns:

The enableWebAccess.