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public interface CustomJobSpecOrBuilder extends MessageOrBuilder
Implements
MessageOrBuilderMethods
getBaseOutputDirectory()
public abstract GcsDestination getBaseOutputDirectory()
The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob:
- AIP_MODEL_DIR =
<base_output_directory>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/logs/
For CustomJob backing a Trial of HyperparameterTuningJob: - AIP_MODEL_DIR =
<base_output_directory>/<trial_id>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/<trial_id>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/<trial_id>/logs/
.google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;
Type | Description |
GcsDestination | The baseOutputDirectory. |
getBaseOutputDirectoryOrBuilder()
public abstract GcsDestinationOrBuilder getBaseOutputDirectoryOrBuilder()
The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob:
- AIP_MODEL_DIR =
<base_output_directory>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/logs/
For CustomJob backing a Trial of HyperparameterTuningJob: - AIP_MODEL_DIR =
<base_output_directory>/<trial_id>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/<trial_id>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/<trial_id>/logs/
.google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;
Type | Description |
GcsDestinationOrBuilder |
getEnableWebAccess()
public abstract boolean getEnableWebAccess()
Optional. Whether you want Vertex AI to enable interactive shell
access
to training containers.
If set to true
, you can access interactive shells at the URIs given
by CustomJob.web_access_uris or Trial.web_access_uris (within
HyperparameterTuningJob.trials).
bool enable_web_access = 10 [(.google.api.field_behavior) = OPTIONAL];
Type | Description |
boolean | The enableWebAccess. |
getNetwork()
public abstract 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 abstract 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 abstract 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 | int The index of the element to return. |
Type | Description |
String | The reservedIpRanges at the given index. |
getReservedIpRangesBytes(int index)
public abstract 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 | int The index of the value to return. |
Type | Description |
ByteString | The bytes of the reservedIpRanges at the given index. |
getReservedIpRangesCount()
public abstract 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 abstract List<String> 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 |
List<String> | A list containing the reservedIpRanges. |
getScheduling()
public abstract Scheduling getScheduling()
Scheduling options for a CustomJob.
.google.cloud.aiplatform.v1.Scheduling scheduling = 3;
Type | Description |
Scheduling | The scheduling. |
getSchedulingOrBuilder()
public abstract SchedulingOrBuilder getSchedulingOrBuilder()
Scheduling options for a CustomJob.
.google.cloud.aiplatform.v1.Scheduling scheduling = 3;
Type | Description |
SchedulingOrBuilder |
getServiceAccount()
public abstract String getServiceAccount()
Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
string service_account = 4;
Type | Description |
String | The serviceAccount. |
getServiceAccountBytes()
public abstract ByteString getServiceAccountBytes()
Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
string service_account = 4;
Type | Description |
ByteString | The bytes for serviceAccount. |
getTensorboard()
public abstract String getTensorboard()
Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob
will upload Tensorboard logs.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}
string tensorboard = 7 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
Type | Description |
String | The tensorboard. |
getTensorboardBytes()
public abstract ByteString getTensorboardBytes()
Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob
will upload Tensorboard logs.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}
string tensorboard = 7 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
Type | Description |
ByteString | The bytes for tensorboard. |
getWorkerPoolSpecs(int index)
public abstract WorkerPoolSpec getWorkerPoolSpecs(int index)
Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];
Name | Description |
index | int |
Type | Description |
WorkerPoolSpec |
getWorkerPoolSpecsCount()
public abstract int getWorkerPoolSpecsCount()
Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];
Type | Description |
int |
getWorkerPoolSpecsList()
public abstract List<WorkerPoolSpec> getWorkerPoolSpecsList()
Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];
Type | Description |
List<WorkerPoolSpec> |
getWorkerPoolSpecsOrBuilder(int index)
public abstract WorkerPoolSpecOrBuilder getWorkerPoolSpecsOrBuilder(int index)
Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];
Name | Description |
index | int |
Type | Description |
WorkerPoolSpecOrBuilder |
getWorkerPoolSpecsOrBuilderList()
public abstract List<? extends WorkerPoolSpecOrBuilder> getWorkerPoolSpecsOrBuilderList()
Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];
Type | Description |
List<? extends com.google.cloud.aiplatform.v1.WorkerPoolSpecOrBuilder> |
hasBaseOutputDirectory()
public abstract boolean hasBaseOutputDirectory()
The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob:
- AIP_MODEL_DIR =
<base_output_directory>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/logs/
For CustomJob backing a Trial of HyperparameterTuningJob: - AIP_MODEL_DIR =
<base_output_directory>/<trial_id>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/<trial_id>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/<trial_id>/logs/
.google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;
Type | Description |
boolean | Whether the baseOutputDirectory field is set. |
hasScheduling()
public abstract boolean hasScheduling()
Scheduling options for a CustomJob.
.google.cloud.aiplatform.v1.Scheduling scheduling = 3;
Type | Description |
boolean | Whether the scheduling field is set. |