Google Cloud Ai Platform V1 Client - Class CustomJobSpec (0.17.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class CustomJobSpec.

Represents the spec of a CustomJob.

Generated from protobuf message google.cloud.aiplatform.v1.CustomJobSpec

Methods

__construct

Constructor.

Parameters
NameDescription
data array

Optional. Data for populating the Message object.

↳ worker_pool_specs array<Google\Cloud\AIPlatform\V1\WorkerPoolSpec>

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.

↳ scheduling Google\Cloud\AIPlatform\V1\Scheduling

Scheduling options for a CustomJob.

↳ service_account string

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.

↳ network string

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.

↳ reserved_ip_ranges array

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'].

↳ base_output_directory Google\Cloud\AIPlatform\V1\GcsDestination

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/

↳ tensorboard string

Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}

↳ enable_web_access bool

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).

↳ enable_dashboard_access bool

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).

↳ experiment string

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

↳ experiment_run string

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

getWorkerPoolSpecs

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.

Returns
TypeDescription
Google\Protobuf\Internal\RepeatedField

setWorkerPoolSpecs

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.

Parameter
NameDescription
var array<Google\Cloud\AIPlatform\V1\WorkerPoolSpec>
Returns
TypeDescription
$this

getScheduling

Scheduling options for a CustomJob.

Returns
TypeDescription
Google\Cloud\AIPlatform\V1\Scheduling|null

hasScheduling

clearScheduling

setScheduling

Scheduling options for a CustomJob.

Parameter
NameDescription
var Google\Cloud\AIPlatform\V1\Scheduling
Returns
TypeDescription
$this

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.

Returns
TypeDescription
string

setServiceAccount

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.

Parameter
NameDescription
var string
Returns
TypeDescription
$this

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.

Returns
TypeDescription
string

setNetwork

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.

Parameter
NameDescription
var string
Returns
TypeDescription
$this

getReservedIpRanges

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'].

Returns
TypeDescription
Google\Protobuf\Internal\RepeatedField

setReservedIpRanges

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'].

Parameter
NameDescription
var string[]
Returns
TypeDescription
$this

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/
Returns
TypeDescription
Google\Cloud\AIPlatform\V1\GcsDestination|null

hasBaseOutputDirectory

clearBaseOutputDirectory

setBaseOutputDirectory

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/
Parameter
NameDescription
var Google\Cloud\AIPlatform\V1\GcsDestination
Returns
TypeDescription
$this

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}

Returns
TypeDescription
string

setTensorboard

Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}

Parameter
NameDescription
var string
Returns
TypeDescription
$this

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).

Returns
TypeDescription
bool

setEnableWebAccess

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).

Parameter
NameDescription
var bool
Returns
TypeDescription
$this

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).

Returns
TypeDescription
bool

setEnableDashboardAccess

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).

Parameter
NameDescription
var bool
Returns
TypeDescription
$this

getExperiment

Optional. The Experiment associated with this job.

Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

Returns
TypeDescription
string

setExperiment

Optional. The Experiment associated with this job.

Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

Parameter
NameDescription
var string
Returns
TypeDescription
$this

getExperimentRun

Optional. The Experiment Run associated with this job.

Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

Returns
TypeDescription
string

setExperimentRun

Optional. The Experiment Run associated with this job.

Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

Parameter
NameDescription
var string
Returns
TypeDescription
$this