Google Cloud Ai Platform V1 Client - Class CustomJobSpec (0.11.1)

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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
Name	Description
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).

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
Type	Description
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
Name	Description
var	array<Google\Cloud\AIPlatform\V1\WorkerPoolSpec>

Returns
Type	Description
$this

getScheduling

Scheduling options for a CustomJob.

Returns
Type	Description
Google\Cloud\AIPlatform\V1\Scheduling|null

hasScheduling

clearScheduling

setScheduling

Scheduling options for a CustomJob.

Parameter
Name	Description
var	Google\Cloud\AIPlatform\V1\Scheduling

Returns
Type	Description
$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
Type	Description
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
Name	Description
var	string

Returns
Type	Description
$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
Type	Description
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
Name	Description
var	string

Returns
Type	Description
$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
Type	Description
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
Name	Description
var	string[]

Returns
Type	Description
$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
Type	Description
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
Name	Description
var	Google\Cloud\AIPlatform\V1\GcsDestination

Returns
Type	Description
$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
Type	Description
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
Name	Description
var	string

Returns
Type	Description
$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
Type	Description
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
Name	Description
var	bool

Returns
Type	Description
$this