Class CustomJobSpec.Builder (3.14.0)

Version 3.14.0

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public static final class CustomJobSpec.Builder extends GeneratedMessageV3.Builder<CustomJobSpec.Builder> implements CustomJobSpecOrBuilder

Represents the spec of a CustomJob.

Protobuf type google.cloud.aiplatform.v1.CustomJobSpec

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > CustomJobSpec.Builder

Implements

CustomJobSpecOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

Methods

addAllReservedIpRanges(Iterable<String> values)

public CustomJobSpec.Builder addAllReservedIpRanges(Iterable<String> values)

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
values	Iterable<String> The reservedIpRanges to add.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

addAllWorkerPoolSpecs(Iterable<? extends WorkerPoolSpec> values)

public CustomJobSpec.Builder addAllWorkerPoolSpecs(Iterable<? extends WorkerPoolSpec> values)

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
values	Iterable<? extends com.google.cloud.aiplatform.v1.WorkerPoolSpec>

Returns
Type	Description
CustomJobSpec.Builder

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public CustomJobSpec.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

addReservedIpRanges(String value)

public CustomJobSpec.Builder addReservedIpRanges(String value)

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	String The reservedIpRanges to add.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

addReservedIpRangesBytes(ByteString value)

public CustomJobSpec.Builder addReservedIpRangesBytes(ByteString value)

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	ByteString The bytes of the reservedIpRanges to add.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

addWorkerPoolSpecs(WorkerPoolSpec value)

public CustomJobSpec.Builder addWorkerPoolSpecs(WorkerPoolSpec value)

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
value	WorkerPoolSpec

Returns
Type	Description
CustomJobSpec.Builder

addWorkerPoolSpecs(WorkerPoolSpec.Builder builderForValue)

public CustomJobSpec.Builder addWorkerPoolSpecs(WorkerPoolSpec.Builder builderForValue)

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
builderForValue	WorkerPoolSpec.Builder

Returns
Type	Description
CustomJobSpec.Builder

addWorkerPoolSpecs(int index, WorkerPoolSpec value)

public CustomJobSpec.Builder addWorkerPoolSpecs(int index, WorkerPoolSpec value)

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];

Parameters
Name	Description
index	int
value	WorkerPoolSpec

Returns
Type	Description
CustomJobSpec.Builder

addWorkerPoolSpecs(int index, WorkerPoolSpec.Builder builderForValue)

public CustomJobSpec.Builder addWorkerPoolSpecs(int index, WorkerPoolSpec.Builder builderForValue)

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];

Parameters
Name	Description
index	int
builderForValue	WorkerPoolSpec.Builder

Returns
Type	Description
CustomJobSpec.Builder

addWorkerPoolSpecsBuilder()

public WorkerPoolSpec.Builder addWorkerPoolSpecsBuilder()

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
WorkerPoolSpec.Builder

addWorkerPoolSpecsBuilder(int index)

public WorkerPoolSpec.Builder addWorkerPoolSpecsBuilder(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.Builder

build()

public CustomJobSpec build()

Returns
Type	Description
CustomJobSpec

buildPartial()

public CustomJobSpec buildPartial()

Returns
Type	Description
CustomJobSpec

clear()

public CustomJobSpec.Builder clear()

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearBaseOutputDirectory()

public CustomJobSpec.Builder clearBaseOutputDirectory()

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
CustomJobSpec.Builder

clearEnableDashboardAccess()

public CustomJobSpec.Builder clearEnableDashboardAccess()

Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

bool enable_dashboard_access = 16 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

clearEnableWebAccess()

public CustomJobSpec.Builder clearEnableWebAccess()

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
CustomJobSpec.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public CustomJobSpec.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
field	FieldDescriptor

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearNetwork()

public CustomJobSpec.Builder clearNetwork()

Optional. 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.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public CustomJobSpec.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
oneof	OneofDescriptor

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearReservedIpRanges()

public CustomJobSpec.Builder clearReservedIpRanges()

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

clearScheduling()

public CustomJobSpec.Builder clearScheduling()

Scheduling options for a CustomJob.

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

Returns
Type	Description
CustomJobSpec.Builder

clearServiceAccount()

public CustomJobSpec.Builder clearServiceAccount()

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
CustomJobSpec.Builder	This builder for chaining.

clearTensorboard()

public CustomJobSpec.Builder clearTensorboard()

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
CustomJobSpec.Builder	This builder for chaining.

clearWorkerPoolSpecs()

public CustomJobSpec.Builder clearWorkerPoolSpecs()

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
CustomJobSpec.Builder

clone()

public CustomJobSpec.Builder clone()

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getBaseOutputDirectory()

public 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.

getBaseOutputDirectoryBuilder()

public GcsDestination.Builder getBaseOutputDirectoryBuilder()

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.Builder

getBaseOutputDirectoryOrBuilder()

public 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

getDefaultInstanceForType()

public CustomJobSpec getDefaultInstanceForType()

Returns
Type	Description
CustomJobSpec

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getEnableDashboardAccess()

public boolean getEnableDashboardAccess()

Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

bool enable_dashboard_access = 16 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
boolean	The enableDashboardAccess.

getEnableWebAccess()

public 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 String getNetwork()

Optional. 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.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
Type	Description
String	The network.

getNetworkBytes()

public ByteString getNetworkBytes()

Optional. 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.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
Type	Description
ByteString	The bytes for network.

getReservedIpRanges(int index)

public String getReservedIpRanges(int index)

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int The index of the element to return.

Returns
Type	Description
String	The reservedIpRanges at the given index.

getReservedIpRangesBytes(int index)

public ByteString getReservedIpRangesBytes(int index)

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
index	int The index of the value to return.

Returns
Type	Description
ByteString	The bytes of the reservedIpRanges at the given index.

getReservedIpRangesCount()

public int getReservedIpRangesCount()

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
int	The count of reservedIpRanges.

getReservedIpRangesList()

public ProtocolStringList getReservedIpRangesList()

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type	Description
ProtocolStringList	A list containing the reservedIpRanges.

getScheduling()

public Scheduling getScheduling()

Scheduling options for a CustomJob.

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

Returns
Type	Description
Scheduling	The scheduling.

getSchedulingBuilder()

public Scheduling.Builder getSchedulingBuilder()

Scheduling options for a CustomJob.

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

Returns
Type	Description
Scheduling.Builder

getSchedulingOrBuilder()

public SchedulingOrBuilder getSchedulingOrBuilder()

Scheduling options for a CustomJob.

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

Returns
Type	Description
SchedulingOrBuilder

getServiceAccount()

public 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 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 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 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 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

getWorkerPoolSpecsBuilder(int index)

public WorkerPoolSpec.Builder getWorkerPoolSpecsBuilder(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.Builder

getWorkerPoolSpecsBuilderList()

public List<WorkerPoolSpec.Builder> getWorkerPoolSpecsBuilderList()

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<Builder>

getWorkerPoolSpecsCount()

public 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 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 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 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 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 boolean hasScheduling()

Scheduling options for a CustomJob.

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

Returns
Type	Description
boolean	Whether the scheduling field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeBaseOutputDirectory(GcsDestination value)

public CustomJobSpec.Builder mergeBaseOutputDirectory(GcsDestination value)

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;

Parameter
Name	Description
value	GcsDestination

Returns
Type	Description
CustomJobSpec.Builder

mergeFrom(CustomJobSpec other)

public CustomJobSpec.Builder mergeFrom(CustomJobSpec other)

Parameter
Name	Description
other	CustomJobSpec

Returns
Type	Description
CustomJobSpec.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public CustomJobSpec.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
CustomJobSpec.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public CustomJobSpec.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
CustomJobSpec.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeScheduling(Scheduling value)

public CustomJobSpec.Builder mergeScheduling(Scheduling value)

Scheduling options for a CustomJob.

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

Parameter
Name	Description
value	Scheduling

Returns
Type	Description
CustomJobSpec.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final CustomJobSpec.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

removeWorkerPoolSpecs(int index)

public CustomJobSpec.Builder removeWorkerPoolSpecs(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
CustomJobSpec.Builder

setBaseOutputDirectory(GcsDestination value)

public CustomJobSpec.Builder setBaseOutputDirectory(GcsDestination value)

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;

Parameter
Name	Description
value	GcsDestination

Returns
Type	Description
CustomJobSpec.Builder

setBaseOutputDirectory(GcsDestination.Builder builderForValue)

public CustomJobSpec.Builder setBaseOutputDirectory(GcsDestination.Builder builderForValue)

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;

Parameter
Name	Description
builderForValue	GcsDestination.Builder

Returns
Type	Description
CustomJobSpec.Builder

setEnableDashboardAccess(boolean value)

public CustomJobSpec.Builder setEnableDashboardAccess(boolean value)

Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

bool enable_dashboard_access = 16 [(.google.api.field_behavior) = OPTIONAL];

Parameter
Name	Description
value	boolean The enableDashboardAccess to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setEnableWebAccess(boolean value)

public CustomJobSpec.Builder setEnableWebAccess(boolean value)

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];

Parameter
Name	Description
value	boolean The enableWebAccess to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public CustomJobSpec.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setNetwork(String value)

public CustomJobSpec.Builder setNetwork(String value)

Optional. 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.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
Name	Description
value	String The network to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setNetworkBytes(ByteString value)

public CustomJobSpec.Builder setNetworkBytes(ByteString value)

Optional. 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.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
Name	Description
value	ByteString The bytes for network to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public CustomJobSpec.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters
Name	Description
field	FieldDescriptor
index	int
value	Object

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setReservedIpRanges(int index, String value)

public CustomJobSpec.Builder setReservedIpRanges(int index, String value)

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];

Parameters
Name	Description
index	int The index to set the value at.
value	String The reservedIpRanges to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setScheduling(Scheduling value)

public CustomJobSpec.Builder setScheduling(Scheduling value)

Scheduling options for a CustomJob.

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

Parameter
Name	Description
value	Scheduling

Returns
Type	Description
CustomJobSpec.Builder

setScheduling(Scheduling.Builder builderForValue)

public CustomJobSpec.Builder setScheduling(Scheduling.Builder builderForValue)

Scheduling options for a CustomJob.

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

Parameter
Name	Description
builderForValue	Scheduling.Builder

Returns
Type	Description
CustomJobSpec.Builder

setServiceAccount(String value)

public CustomJobSpec.Builder setServiceAccount(String value)

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;

Parameter
Name	Description
value	String The serviceAccount to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setServiceAccountBytes(ByteString value)

public CustomJobSpec.Builder setServiceAccountBytes(ByteString value)

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;

Parameter
Name	Description
value	ByteString The bytes for serviceAccount to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setTensorboard(String value)

public CustomJobSpec.Builder setTensorboard(String value)

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) = { ... }

Parameter
Name	Description
value	String The tensorboard to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setTensorboardBytes(ByteString value)

public CustomJobSpec.Builder setTensorboardBytes(ByteString value)

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) = { ... }

Parameter
Name	Description
value	ByteString The bytes for tensorboard to set.

Returns
Type	Description
CustomJobSpec.Builder	This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final CustomJobSpec.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
CustomJobSpec.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)

setWorkerPoolSpecs(int index, WorkerPoolSpec value)

public CustomJobSpec.Builder setWorkerPoolSpecs(int index, WorkerPoolSpec value)

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];

Parameters
Name	Description
index	int
value	WorkerPoolSpec

Returns
Type	Description
CustomJobSpec.Builder

setWorkerPoolSpecs(int index, WorkerPoolSpec.Builder builderForValue)

public CustomJobSpec.Builder setWorkerPoolSpecs(int index, WorkerPoolSpec.Builder builderForValue)

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];

Parameters
Name	Description
index	int
builderForValue	WorkerPoolSpec.Builder

Returns
Type	Description
CustomJobSpec.Builder