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public static final class CustomJobSpec.Builder extends GeneratedMessageV3.Builder<CustomJobSpec.Builder> implements CustomJobSpecOrBuilderRepresents the spec of a CustomJob.
Protobuf type google.cloud.aiplatform.v1.CustomJobSpec
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > CustomJobSpec.BuilderImplements
CustomJobSpecOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| 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];
| Name | Description |
| values | Iterable<String>The reservedIpRanges to add. |
| 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];
| Name | Description |
| values | Iterable<? extends com.google.cloud.aiplatform.v1.WorkerPoolSpec> |
| Type | Description |
| CustomJobSpec.Builder |
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public CustomJobSpec.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Name | Description |
| field | FieldDescriptor |
| value | Object |
| Type | Description |
| CustomJobSpec.Builder |
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];
| Name | Description |
| value | StringThe reservedIpRanges to add. |
| 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];
| Name | Description |
| value | ByteStringThe bytes of the reservedIpRanges to add. |
| 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];
| Name | Description |
| value | WorkerPoolSpec |
| 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];
| Name | Description |
| builderForValue | WorkerPoolSpec.Builder |
| 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];
| Name | Description |
| index | int |
| value | WorkerPoolSpec |
| 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];
| Name | Description |
| index | int |
| builderForValue | WorkerPoolSpec.Builder |
| 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];
| 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];
| Name | Description |
| index | int |
| Type | Description |
| WorkerPoolSpec.Builder |
build()
public CustomJobSpec build()| Type | Description |
| CustomJobSpec |
buildPartial()
public CustomJobSpec buildPartial()| Type | Description |
| CustomJobSpec |
clear()
public CustomJobSpec.Builder clear()| Type | Description |
| CustomJobSpec.Builder |
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;
| Type | Description |
| CustomJobSpec.Builder |
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];
| Type | Description |
| CustomJobSpec.Builder | This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public CustomJobSpec.Builder clearField(Descriptors.FieldDescriptor field)| Name | Description |
| field | FieldDescriptor |
| Type | Description |
| CustomJobSpec.Builder |
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) = { ... }
| Type | Description |
| CustomJobSpec.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public CustomJobSpec.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Name | Description |
| oneof | OneofDescriptor |
| Type | Description |
| CustomJobSpec.Builder |
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];
| 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;
| 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;
| 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) = { ... }
| 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];
| Type | Description |
| CustomJobSpec.Builder |
clone()
public CustomJobSpec.Builder clone()| Type | Description |
| CustomJobSpec.Builder |
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;
| 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;
| 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;
| Type | Description |
| GcsDestinationOrBuilder |
getDefaultInstanceForType()
public CustomJobSpec getDefaultInstanceForType()| Type | Description |
| CustomJobSpec |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Type | Description |
| Descriptor |
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];
| 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) = { ... }
| 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) = { ... }
| 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];
| Name | Description |
| index | intThe index of the element to return. |
| 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];
| Name | Description |
| index | intThe index of the value to return. |
| 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];
| 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];
| Type | Description |
| ProtocolStringList | A list containing the reservedIpRanges. |
getScheduling()
public Scheduling getScheduling()Scheduling options for a CustomJob.
.google.cloud.aiplatform.v1.Scheduling scheduling = 3;
| Type | Description |
| Scheduling | The scheduling. |
getSchedulingBuilder()
public Scheduling.Builder getSchedulingBuilder()Scheduling options for a CustomJob.
.google.cloud.aiplatform.v1.Scheduling scheduling = 3;
| Type | Description |
| Scheduling.Builder |
getSchedulingOrBuilder()
public SchedulingOrBuilder getSchedulingOrBuilder()Scheduling options for a CustomJob.
.google.cloud.aiplatform.v1.Scheduling scheduling = 3;
| 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;
| 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;
| 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) = { ... }
| 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) = { ... }
| 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];
| Name | Description |
| index | int |
| 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];
| Name | Description |
| index | int |
| 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];
| 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];
| 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];
| 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];
| Name | Description |
| index | int |
| 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];
| 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;
| 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;
| Type | Description |
| boolean | Whether the scheduling field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Type | Description |
| FieldAccessorTable |
isInitialized()
public final boolean isInitialized()| Type | Description |
| boolean |
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;
| Name | Description |
| value | GcsDestination |
| Type | Description |
| CustomJobSpec.Builder |
mergeFrom(CustomJobSpec other)
public CustomJobSpec.Builder mergeFrom(CustomJobSpec other)| Name | Description |
| other | CustomJobSpec |
| Type | Description |
| CustomJobSpec.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public CustomJobSpec.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Name | Description |
| input | CodedInputStream |
| extensionRegistry | ExtensionRegistryLite |
| Type | Description |
| CustomJobSpec.Builder |
| Type | Description |
| IOException |
mergeFrom(Message other)
public CustomJobSpec.Builder mergeFrom(Message other)| Name | Description |
| other | Message |
| Type | Description |
| CustomJobSpec.Builder |
mergeScheduling(Scheduling value)
public CustomJobSpec.Builder mergeScheduling(Scheduling value)Scheduling options for a CustomJob.
.google.cloud.aiplatform.v1.Scheduling scheduling = 3;
| Name | Description |
| value | Scheduling |
| Type | Description |
| CustomJobSpec.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final CustomJobSpec.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Name | Description |
| unknownFields | UnknownFieldSet |
| Type | Description |
| CustomJobSpec.Builder |
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];
| Name | Description |
| index | int |
| 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;
| Name | Description |
| value | GcsDestination |
| 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;
| Name | Description |
| builderForValue | GcsDestination.Builder |
| Type | Description |
| CustomJobSpec.Builder |
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];
| Name | Description |
| value | booleanThe enableWebAccess to set. |
| Type | Description |
| CustomJobSpec.Builder | This builder for chaining. |
setField(Descriptors.FieldDescriptor field, Object value)
public CustomJobSpec.Builder setField(Descriptors.FieldDescriptor field, Object value)| Name | Description |
| field | FieldDescriptor |
| value | Object |
| Type | Description |
| CustomJobSpec.Builder |
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) = { ... }
| Name | Description |
| value | StringThe network to set. |
| 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) = { ... }
| Name | Description |
| value | ByteStringThe bytes for network to set. |
| 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)| Name | Description |
| field | FieldDescriptor |
| index | int |
| value | Object |
| Type | Description |
| CustomJobSpec.Builder |
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];
| Name | Description |
| index | intThe index to set the value at. |
| value | StringThe reservedIpRanges to set. |
| 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;
| Name | Description |
| value | Scheduling |
| 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;
| Name | Description |
| builderForValue | Scheduling.Builder |
| 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;
| Name | Description |
| value | StringThe serviceAccount to set. |
| 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;
| Name | Description |
| value | ByteStringThe bytes for serviceAccount to set. |
| 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) = { ... }
| Name | Description |
| value | StringThe tensorboard to set. |
| 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) = { ... }
| Name | Description |
| value | ByteStringThe bytes for tensorboard to set. |
| Type | Description |
| CustomJobSpec.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final CustomJobSpec.Builder setUnknownFields(UnknownFieldSet unknownFields)| Name | Description |
| unknownFields | UnknownFieldSet |
| Type | Description |
| CustomJobSpec.Builder |
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];
| Name | Description |
| index | int |
| value | WorkerPoolSpec |
| 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];
| Name | Description |
| index | int |
| builderForValue | WorkerPoolSpec.Builder |
| Type | Description |
| CustomJobSpec.Builder |