Class CustomJobSpec.Builder (3.23.0)

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

Represents the spec of a CustomJob.

Protobuf type google.cloud.aiplatform.v1beta1.CustomJobSpec

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
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
NameDescription
valuesIterable<String>

The reservedIpRanges to add.

Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
valuesIterable<? extends com.google.cloud.aiplatform.v1beta1.WorkerPoolSpec>
Returns
TypeDescription
CustomJobSpec.Builder

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public CustomJobSpec.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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
NameDescription
valueString

The reservedIpRanges to add.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes of the reservedIpRanges to add.

Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
valueWorkerPoolSpec
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
builderForValueWorkerPoolSpec.Builder
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
NameDescription
indexint
valueWorkerPoolSpec
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
NameDescription
indexint
builderForValueWorkerPoolSpec.Builder
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
indexint
Returns
TypeDescription
WorkerPoolSpec.Builder

build()

public CustomJobSpec build()
Returns
TypeDescription
CustomJobSpec

buildPartial()

public CustomJobSpec buildPartial()
Returns
TypeDescription
CustomJobSpec

clear()

public CustomJobSpec.Builder clear()
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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.v1beta1.GcsDestination base_output_directory = 6;

Returns
TypeDescription
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
TypeDescription
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
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

clearExperiment()

public CustomJobSpec.Builder clearExperiment()

Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

string experiment = 17 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

clearExperimentRun()

public CustomJobSpec.Builder clearExperimentRun()

Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

string experiment_run = 18 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public CustomJobSpec.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public CustomJobSpec.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

clearPersistentResourceId()

public CustomJobSpec.Builder clearPersistentResourceId()

Optional. The ID of the PersistentResource in the same Project and Location which to run

If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.

string persistent_resource_id = 14 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

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
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

clearScheduling()

public CustomJobSpec.Builder clearScheduling()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Returns
TypeDescription
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
TypeDescription
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
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
CustomJobSpec.Builder

clone()

public CustomJobSpec.Builder clone()
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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.v1beta1.GcsDestination base_output_directory = 6;

Returns
TypeDescription
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.v1beta1.GcsDestination base_output_directory = 6;

Returns
TypeDescription
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.v1beta1.GcsDestination base_output_directory = 6;

Returns
TypeDescription
GcsDestinationOrBuilder

getDefaultInstanceForType()

public CustomJobSpec getDefaultInstanceForType()
Returns
TypeDescription
CustomJobSpec

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

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
TypeDescription
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
TypeDescription
boolean

The enableWebAccess.

getExperiment()

public String getExperiment()

Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

string experiment = 17 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
String

The experiment.

getExperimentBytes()

public ByteString getExperimentBytes()

Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

string experiment = 17 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
ByteString

The bytes for experiment.

getExperimentRun()

public String getExperimentRun()

Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

string experiment_run = 18 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
String

The experimentRun.

getExperimentRunBytes()

public ByteString getExperimentRunBytes()

Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

string experiment_run = 18 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
ByteString

The bytes for experimentRun.

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
TypeDescription
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
TypeDescription
ByteString

The bytes for network.

getPersistentResourceId()

public String getPersistentResourceId()

Optional. The ID of the PersistentResource in the same Project and Location which to run

If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.

string persistent_resource_id = 14 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
String

The persistentResourceId.

getPersistentResourceIdBytes()

public ByteString getPersistentResourceIdBytes()

Optional. The ID of the PersistentResource in the same Project and Location which to run

If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.

string persistent_resource_id = 14 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Returns
TypeDescription
ByteString

The bytes for persistentResourceId.

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
NameDescription
indexint

The index of the element to return.

Returns
TypeDescription
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
NameDescription
indexint

The index of the value to return.

Returns
TypeDescription
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
TypeDescription
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
TypeDescription
ProtocolStringList

A list containing the reservedIpRanges.

getScheduling()

public Scheduling getScheduling()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Returns
TypeDescription
Scheduling

The scheduling.

getSchedulingBuilder()

public Scheduling.Builder getSchedulingBuilder()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Returns
TypeDescription
Scheduling.Builder

getSchedulingOrBuilder()

public SchedulingOrBuilder getSchedulingOrBuilder()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Returns
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
indexint
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
indexint
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
indexint
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
List<? extends com.google.cloud.aiplatform.v1beta1.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.v1beta1.GcsDestination base_output_directory = 6;

Returns
TypeDescription
boolean

Whether the baseOutputDirectory field is set.

hasScheduling()

public boolean hasScheduling()

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Returns
TypeDescription
boolean

Whether the scheduling field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

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.v1beta1.GcsDestination base_output_directory = 6;

Parameter
NameDescription
valueGcsDestination
Returns
TypeDescription
CustomJobSpec.Builder

mergeFrom(CustomJobSpec other)

public CustomJobSpec.Builder mergeFrom(CustomJobSpec other)
Parameter
NameDescription
otherCustomJobSpec
Returns
TypeDescription
CustomJobSpec.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public CustomJobSpec.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
CustomJobSpec.Builder
Overrides
Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public CustomJobSpec.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

mergeScheduling(Scheduling value)

public CustomJobSpec.Builder mergeScheduling(Scheduling value)

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Parameter
NameDescription
valueScheduling
Returns
TypeDescription
CustomJobSpec.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final CustomJobSpec.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
indexint
Returns
TypeDescription
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.v1beta1.GcsDestination base_output_directory = 6;

Parameter
NameDescription
valueGcsDestination
Returns
TypeDescription
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.v1beta1.GcsDestination base_output_directory = 6;

Parameter
NameDescription
builderForValueGcsDestination.Builder
Returns
TypeDescription
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
NameDescription
valueboolean

The enableDashboardAccess to set.

Returns
TypeDescription
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
NameDescription
valueboolean

The enableWebAccess to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setExperiment(String value)

public CustomJobSpec.Builder setExperiment(String value)

Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

string experiment = 17 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
NameDescription
valueString

The experiment to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setExperimentBytes(ByteString value)

public CustomJobSpec.Builder setExperimentBytes(ByteString value)

Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

string experiment = 17 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
NameDescription
valueByteString

The bytes for experiment to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setExperimentRun(String value)

public CustomJobSpec.Builder setExperimentRun(String value)

Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

string experiment_run = 18 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
NameDescription
valueString

The experimentRun to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setExperimentRunBytes(ByteString value)

public CustomJobSpec.Builder setExperimentRunBytes(ByteString value)

Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

string experiment_run = 18 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
NameDescription
valueByteString

The bytes for experimentRun to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public CustomJobSpec.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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
NameDescription
valueString

The network to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for network to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setPersistentResourceId(String value)

public CustomJobSpec.Builder setPersistentResourceId(String value)

Optional. The ID of the PersistentResource in the same Project and Location which to run

If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.

string persistent_resource_id = 14 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
NameDescription
valueString

The persistentResourceId to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setPersistentResourceIdBytes(ByteString value)

public CustomJobSpec.Builder setPersistentResourceIdBytes(ByteString value)

Optional. The ID of the PersistentResource in the same Project and Location which to run

If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.

string persistent_resource_id = 14 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }

Parameter
NameDescription
valueByteString

The bytes for persistentResourceId to set.

Returns
TypeDescription
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
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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
NameDescription
indexint

The index to set the value at.

valueString

The reservedIpRanges to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setScheduling(Scheduling value)

public CustomJobSpec.Builder setScheduling(Scheduling value)

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Parameter
NameDescription
valueScheduling
Returns
TypeDescription
CustomJobSpec.Builder

setScheduling(Scheduling.Builder builderForValue)

public CustomJobSpec.Builder setScheduling(Scheduling.Builder builderForValue)

Scheduling options for a CustomJob.

.google.cloud.aiplatform.v1beta1.Scheduling scheduling = 3;

Parameter
NameDescription
builderForValueScheduling.Builder
Returns
TypeDescription
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
NameDescription
valueString

The serviceAccount to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for serviceAccount to set.

Returns
TypeDescription
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
NameDescription
valueString

The tensorboard to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for tensorboard to set.

Returns
TypeDescription
CustomJobSpec.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final CustomJobSpec.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
CustomJobSpec.Builder
Overrides

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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
NameDescription
indexint
valueWorkerPoolSpec
Returns
TypeDescription
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.v1beta1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
NameDescription
indexint
builderForValueWorkerPoolSpec.Builder
Returns
TypeDescription
CustomJobSpec.Builder