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, |
↳ 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 = |
↳ tensorboard |
string
Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: |
↳ enable_web_access |
bool
Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to |
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.
Generated from protobuf field repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];
| 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.
Generated from protobuf field repeated .google.cloud.aiplatform.v1.WorkerPoolSpec worker_pool_specs = 1 [(.google.api.field_behavior) = REQUIRED];
| Parameter | |
|---|---|
| Name | Description |
var |
array<Google\Cloud\AIPlatform\V1\WorkerPoolSpec>
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getScheduling
Scheduling options for a CustomJob.
Generated from protobuf field .google.cloud.aiplatform.v1.Scheduling scheduling = 3;
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\Scheduling|null | |
hasScheduling
clearScheduling
setScheduling
Scheduling options for a CustomJob.
Generated from protobuf field .google.cloud.aiplatform.v1.Scheduling scheduling = 3;
| 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.
Generated from protobuf field string service_account = 4;
| 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.
Generated from protobuf field string service_account = 4;
| 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.
Generated from protobuf field string network = 5 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = {
| 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.
Generated from protobuf field string network = 5 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = {
| 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'].
Generated from protobuf field repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];
| 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'].
Generated from protobuf field repeated string reserved_ip_ranges = 13 [(.google.api.field_behavior) = OPTIONAL];
| 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/
Generated from protobuf field .google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;
| 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/
Generated from protobuf field .google.cloud.aiplatform.v1.GcsDestination base_output_directory = 6;
| 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}
Generated from protobuf field string tensorboard = 7 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = {
| 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}
Generated from protobuf field string tensorboard = 7 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = {
| 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).
Generated from protobuf field bool enable_web_access = 10 [(.google.api.field_behavior) = OPTIONAL];
| 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).
Generated from protobuf field bool enable_web_access = 10 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
var |
bool
|
| Returns | |
|---|---|
| Type | Description |
$this | |