Package com.google.cloud.aiplatform.v1

Interface CustomJobSpecOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
CustomJobSpec, CustomJobSpec.Builder
@Generated public interface CustomJobSpecOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • getPersistentResourceId

      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:
      The persistentResourceId.

    • getPersistentResourceIdBytes

      com.google.protobuf.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:
      The bytes for persistentResourceId.

    • getWorkerPoolSpecsList

      List<WorkerPoolSpec> getWorkerPoolSpecsList()
       Required. The spec of the worker pools including machine type and Docker
 image. All worker pools except the first one are optional and can be
 skipped by providing an empty value.
      repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

    • getWorkerPoolSpecs

      WorkerPoolSpec getWorkerPoolSpecs(int index)
       Required. The spec of the worker pools including machine type and Docker
 image. All worker pools except the first one are optional and can be
 skipped by providing an empty value.
      repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

    • getWorkerPoolSpecsCount

      int getWorkerPoolSpecsCount()
       Required. The spec of the worker pools including machine type and Docker
 image. All worker pools except the first one are optional and can be
 skipped by providing an empty value.
      repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

    • getWorkerPoolSpecsOrBuilderList

      List<? extends WorkerPoolSpecOrBuilder> getWorkerPoolSpecsOrBuilderList()
       Required. The spec of the worker pools including machine type and Docker
 image. All worker pools except the first one are optional and can be
 skipped by providing an empty value.
      repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

    • getWorkerPoolSpecsOrBuilder

      WorkerPoolSpecOrBuilder getWorkerPoolSpecsOrBuilder(int index)
       Required. The spec of the worker pools including machine type and Docker
 image. All worker pools except the first one are optional and can be
 skipped by providing an empty value.
      repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];

    • hasScheduling

      boolean hasScheduling()
       Scheduling options for a CustomJob.
      .google.cloud.aiplatform.v1.Scheduling scheduling = 3;
      Returns:
      Whether the scheduling field is set.

    • getScheduling

      Scheduling getScheduling()
       Scheduling options for a CustomJob.
      .google.cloud.aiplatform.v1.Scheduling scheduling = 3;
      Returns:
      The scheduling.

    • getSchedulingOrBuilder

      SchedulingOrBuilder getSchedulingOrBuilder()
       Scheduling options for a CustomJob.
      .google.cloud.aiplatform.v1.Scheduling scheduling = 3;

    • getServiceAccount

      String getServiceAccount()
       Specifies the service account for workload run-as account.
 Users submitting jobs must have act-as permission on this run-as account.
 If unspecified, the [Vertex AI Custom Code Service
 Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)
 for the CustomJob's project is used.
      string service_account = 4;
      Returns:
      The serviceAccount.

    • getServiceAccountBytes

      com.google.protobuf.ByteString getServiceAccountBytes()
       Specifies the service account for workload run-as account.
 Users submitting jobs must have act-as permission on this run-as account.
 If unspecified, the [Vertex AI Custom Code Service
 Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)
 for the CustomJob's project is used.
      string service_account = 4;
      Returns:
      The bytes for serviceAccount.

    • getNetwork

      String getNetwork()
       Optional. The full name of the Compute Engine
 [network](/compute/docs/networks-and-firewalls#networks) to which the Job
 should be peered. For example, `projects/12345/global/networks/myVPC`.
 [Format](/compute/docs/reference/rest/v1/networks/insert)
 is of the form `projects/{project}/global/networks/{network}`.
 Where {project} is a project number, as in `12345`, and {network} is a
 network name.

 To specify this field, you must have already [configured VPC Network
 Peering for Vertex
 AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering).

 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:
      The network.

    • getNetworkBytes

      com.google.protobuf.ByteString getNetworkBytes()
       Optional. The full name of the Compute Engine
 [network](/compute/docs/networks-and-firewalls#networks) to which the Job
 should be peered. For example, `projects/12345/global/networks/myVPC`.
 [Format](/compute/docs/reference/rest/v1/networks/insert)
 is of the form `projects/{project}/global/networks/{network}`.
 Where {project} is a project number, as in `12345`, and {network} is a
 network name.

 To specify this field, you must have already [configured VPC Network
 Peering for Vertex
 AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering).

 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:
      The bytes for network.

    • getReservedIpRangesList

      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];
      Returns:
      A list containing the reservedIpRanges.

    • getReservedIpRangesCount

      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:
      The count of reservedIpRanges.

    • getReservedIpRanges

      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];
      Parameters:
      index - The index of the element to return.
      Returns:
      The reservedIpRanges at the given index.

    • getReservedIpRangesBytes

      com.google.protobuf.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];
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the reservedIpRanges at the given index.

    • hasPscInterfaceConfig

      boolean hasPscInterfaceConfig()
       Optional. Configuration for PSC-I for CustomJob.
      .google.cloud.aiplatform.v1.PscInterfaceConfig psc_interface_config = 21 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      Whether the pscInterfaceConfig field is set.

    • getPscInterfaceConfig

      PscInterfaceConfig getPscInterfaceConfig()
       Optional. Configuration for PSC-I for CustomJob.
      .google.cloud.aiplatform.v1.PscInterfaceConfig psc_interface_config = 21 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The pscInterfaceConfig.

    • getPscInterfaceConfigOrBuilder

      PscInterfaceConfigOrBuilder getPscInterfaceConfigOrBuilder()
       Optional. Configuration for PSC-I for CustomJob.
      .google.cloud.aiplatform.v1.PscInterfaceConfig psc_interface_config = 21 [(.google.api.field_behavior) = OPTIONAL];

    • hasBaseOutputDirectory

      boolean hasBaseOutputDirectory()
       The Cloud Storage location to store the output of this CustomJob or
 HyperparameterTuningJob. For HyperparameterTuningJob,
 the baseOutputDirectory of
 each child CustomJob backing a Trial is set to a subdirectory of name
 [id][google.cloud.aiplatform.v1.Trial.id] under its parent
 HyperparameterTuningJob's baseOutputDirectory.

 The following Vertex AI environment variables will be passed to
 containers or python modules when this field is set:

 For CustomJob:

 * AIP_MODEL_DIR = `<base_output_directory>/model/`
 * AIP_CHECKPOINT_DIR = `<base_output_directory>/checkpoints/`
 * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/logs/`

 For CustomJob backing a Trial of HyperparameterTuningJob:

 * AIP_MODEL_DIR = `<base_output_directory>/<trial_id>/model/`
 * AIP_CHECKPOINT_DIR = `<base_output_directory>/<trial_id>/checkpoints/`
 * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/<trial_id>/logs/`
      .google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;
      Returns:
      Whether the baseOutputDirectory field is set.

    • getBaseOutputDirectory

      GcsDestination getBaseOutputDirectory()
       The Cloud Storage location to store the output of this CustomJob or
 HyperparameterTuningJob. For HyperparameterTuningJob,
 the baseOutputDirectory of
 each child CustomJob backing a Trial is set to a subdirectory of name
 [id][google.cloud.aiplatform.v1.Trial.id] under its parent
 HyperparameterTuningJob's baseOutputDirectory.

 The following Vertex AI environment variables will be passed to
 containers or python modules when this field is set:

 For CustomJob:

 * AIP_MODEL_DIR = `<base_output_directory>/model/`
 * AIP_CHECKPOINT_DIR = `<base_output_directory>/checkpoints/`
 * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/logs/`

 For CustomJob backing a Trial of HyperparameterTuningJob:

 * AIP_MODEL_DIR = `<base_output_directory>/<trial_id>/model/`
 * AIP_CHECKPOINT_DIR = `<base_output_directory>/<trial_id>/checkpoints/`
 * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/<trial_id>/logs/`
      .google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;
      Returns:
      The baseOutputDirectory.

    • getBaseOutputDirectoryOrBuilder

      GcsDestinationOrBuilder getBaseOutputDirectoryOrBuilder()
       The Cloud Storage location to store the output of this CustomJob or
 HyperparameterTuningJob. For HyperparameterTuningJob,
 the baseOutputDirectory of
 each child CustomJob backing a Trial is set to a subdirectory of name
 [id][google.cloud.aiplatform.v1.Trial.id] under its parent
 HyperparameterTuningJob's baseOutputDirectory.

 The following Vertex AI environment variables will be passed to
 containers or python modules when this field is set:

 For CustomJob:

 * AIP_MODEL_DIR = `<base_output_directory>/model/`
 * AIP_CHECKPOINT_DIR = `<base_output_directory>/checkpoints/`
 * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/logs/`

 For CustomJob backing a Trial of HyperparameterTuningJob:

 * AIP_MODEL_DIR = `<base_output_directory>/<trial_id>/model/`
 * AIP_CHECKPOINT_DIR = `<base_output_directory>/<trial_id>/checkpoints/`
 * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/<trial_id>/logs/`
      .google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;

    • getProtectedArtifactLocationId

      String getProtectedArtifactLocationId()
       The ID of the location to store protected artifacts. e.g. us-central1.
 Populate only when the location is different than CustomJob location.
 List of supported locations:
 https://cloud.google.com/vertex-ai/docs/general/locations
      string protected_artifact_location_id = 19;
      Returns:
      The protectedArtifactLocationId.

    • getProtectedArtifactLocationIdBytes

      com.google.protobuf.ByteString getProtectedArtifactLocationIdBytes()
       The ID of the location to store protected artifacts. e.g. us-central1.
 Populate only when the location is different than CustomJob location.
 List of supported locations:
 https://cloud.google.com/vertex-ai/docs/general/locations
      string protected_artifact_location_id = 19;
      Returns:
      The bytes for protectedArtifactLocationId.

    • getTensorboard

      String getTensorboard()
       Optional. The name of a Vertex AI
 [Tensorboard][google.cloud.aiplatform.v1.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:
      The tensorboard.

    • getTensorboardBytes

      com.google.protobuf.ByteString getTensorboardBytes()
       Optional. The name of a Vertex AI
 [Tensorboard][google.cloud.aiplatform.v1.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:
      The bytes for tensorboard.

    • getEnableWebAccess

      boolean getEnableWebAccess()
       Optional. Whether you want Vertex AI to enable [interactive shell
 access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell)
 to training containers.

 If set to `true`, you can access interactive shells at the URIs given
 by
 [CustomJob.web_access_uris][google.cloud.aiplatform.v1.CustomJob.web_access_uris]
 or
 [Trial.web_access_uris][google.cloud.aiplatform.v1.Trial.web_access_uris]
 (within
 [HyperparameterTuningJob.trials][google.cloud.aiplatform.v1.HyperparameterTuningJob.trials]).
      bool enable_web_access = 10 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The enableWebAccess.

    • getEnableDashboardAccess

      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][google.cloud.aiplatform.v1.CustomJob.web_access_uris]
 or
 [Trial.web_access_uris][google.cloud.aiplatform.v1.Trial.web_access_uris]
 (within
 [HyperparameterTuningJob.trials][google.cloud.aiplatform.v1.HyperparameterTuningJob.trials]).
      bool enable_dashboard_access = 16 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The enableDashboardAccess.

    • getExperiment

      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:
      The experiment.

    • getExperimentBytes

      com.google.protobuf.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:
      The bytes for experiment.

    • getExperimentRun

      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:
      The experimentRun.

    • getExperimentRunBytes

      com.google.protobuf.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:
      The bytes for experimentRun.

    • getModelsList

      List<String> getModelsList()
       Optional. The name of the Model resources for which to generate a mapping
 to artifact URIs. Applicable only to some of the Google-provided custom
 jobs. Format: `projects/{project}/locations/{location}/models/{model}`

 In order to retrieve a specific version of the model, also provide
 the version ID or version alias.
 Example: `projects/{project}/locations/{location}/models/{model}@2`
 or
 `projects/{project}/locations/{location}/models/{model}@golden`
 If no version ID or alias is specified, the "default" version will be
 returned. The "default" version alias is created for the first version of
 the model, and can be moved to other versions later on. There will be
 exactly one default version.
      repeated string models = 20 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
      Returns:
      A list containing the models.

    • getModelsCount

      int getModelsCount()
       Optional. The name of the Model resources for which to generate a mapping
 to artifact URIs. Applicable only to some of the Google-provided custom
 jobs. Format: `projects/{project}/locations/{location}/models/{model}`

 In order to retrieve a specific version of the model, also provide
 the version ID or version alias.
 Example: `projects/{project}/locations/{location}/models/{model}@2`
 or
 `projects/{project}/locations/{location}/models/{model}@golden`
 If no version ID or alias is specified, the "default" version will be
 returned. The "default" version alias is created for the first version of
 the model, and can be moved to other versions later on. There will be
 exactly one default version.
      repeated string models = 20 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
      Returns:
      The count of models.

    • getModels

      String getModels(int index)
       Optional. The name of the Model resources for which to generate a mapping
 to artifact URIs. Applicable only to some of the Google-provided custom
 jobs. Format: `projects/{project}/locations/{location}/models/{model}`

 In order to retrieve a specific version of the model, also provide
 the version ID or version alias.
 Example: `projects/{project}/locations/{location}/models/{model}@2`
 or
 `projects/{project}/locations/{location}/models/{model}@golden`
 If no version ID or alias is specified, the "default" version will be
 returned. The "default" version alias is created for the first version of
 the model, and can be moved to other versions later on. There will be
 exactly one default version.
      repeated string models = 20 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
      Parameters:
      index - The index of the element to return.
      Returns:
      The models at the given index.

    • getModelsBytes

      com.google.protobuf.ByteString getModelsBytes(int index)
       Optional. The name of the Model resources for which to generate a mapping
 to artifact URIs. Applicable only to some of the Google-provided custom
 jobs. Format: `projects/{project}/locations/{location}/models/{model}`

 In order to retrieve a specific version of the model, also provide
 the version ID or version alias.
 Example: `projects/{project}/locations/{location}/models/{model}@2`
 or
 `projects/{project}/locations/{location}/models/{model}@golden`
 If no version ID or alias is specified, the "default" version will be
 returned. The "default" version alias is created for the first version of
 the model, and can be moved to other versions later on. There will be
 exactly one default version.
      repeated string models = 20 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the models at the given index.