hyperparameter_tuning_jobs

Creates, updates, deletes, gets or lists a hyperparameter_tuning_jobs resource.

Overview

Name	`hyperparameter_tuning_jobs`
Type	Resource
Id	`google.aiplatform.hyperparameter_tuning_jobs`

Fields

The following fields are returned by SELECT queries:

get
list

Successful response

Name	Datatype	Description
`name`	`string`	Output only. Resource name of the HyperparameterTuningJob.
`createTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob was created.
`displayName`	`string`	Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
`encryptionSpec`	`object`	Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key. (id: GoogleCloudAiplatformV1EncryptionSpec)
`endTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
`error`	`object`	Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED. (id: GoogleRpcStatus)
`labels`	`object`	The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
`maxFailedTrialCount`	`integer (int32)`	The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
`maxTrialCount`	`integer (int32)`	Required. The desired total number of Trials.
`parallelTrialCount`	`integer (int32)`	Required. The desired number of Trials to run in parallel.
`satisfiesPzi`	`boolean`	Output only. Reserved for future use.
`satisfiesPzs`	`boolean`	Output only. Reserved for future use.
`startTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.
`state`	`string`	Output only. The detailed state of the job.
`studySpec`	`object`	Required. Study configuration of the HyperparameterTuningJob. (id: GoogleCloudAiplatformV1StudySpec)
`trialJobSpec`	`object`	Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials. (id: GoogleCloudAiplatformV1CustomJobSpec)
`trials`	`array`	Output only. Trials of the HyperparameterTuningJob.
`updateTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob was most recently updated.

Successful response

Name	Datatype	Description
`name`	`string`	Output only. Resource name of the HyperparameterTuningJob.
`createTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob was created.
`displayName`	`string`	Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
`encryptionSpec`	`object`	Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key. (id: GoogleCloudAiplatformV1EncryptionSpec)
`endTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
`error`	`object`	Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED. (id: GoogleRpcStatus)
`labels`	`object`	The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
`maxFailedTrialCount`	`integer (int32)`	The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
`maxTrialCount`	`integer (int32)`	Required. The desired total number of Trials.
`parallelTrialCount`	`integer (int32)`	Required. The desired number of Trials to run in parallel.
`satisfiesPzi`	`boolean`	Output only. Reserved for future use.
`satisfiesPzs`	`boolean`	Output only. Reserved for future use.
`startTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.
`state`	`string`	Output only. The detailed state of the job.
`studySpec`	`object`	Required. Study configuration of the HyperparameterTuningJob. (id: GoogleCloudAiplatformV1StudySpec)
`trialJobSpec`	`object`	Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials. (id: GoogleCloudAiplatformV1CustomJobSpec)
`trials`	`array`	Output only. Trials of the HyperparameterTuningJob.
`updateTime`	`string (google-datetime)`	Output only. Time when the HyperparameterTuningJob was most recently updated.

Methods

The following methods are available for this resource:

Name	Accessible by	Required Params	Optional Params	Description
`get`	`select`	`projectsId`, `locationsId`, `hyperparameterTuningJobsId`		Gets a HyperparameterTuningJob
`list`	`select`	`projectsId`, `locationsId`	`filter`, `pageSize`, `pageToken`, `readMask`	Lists HyperparameterTuningJobs in a Location.
`create`	`insert`	`projectsId`, `locationsId`		Creates a HyperparameterTuningJob
`delete`	`delete`	`projectsId`, `locationsId`, `hyperparameterTuningJobsId`		Deletes a HyperparameterTuningJob.
`cancel`	`exec`	`projectsId`, `locationsId`, `hyperparameterTuningJobsId`		Cancels a HyperparameterTuningJob. Starts asynchronous cancellation on the HyperparameterTuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetHyperparameterTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the HyperparameterTuningJob is not deleted; instead it becomes a job with a HyperparameterTuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and HyperparameterTuningJob.state is set to `CANCELLED`.

Parameters

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

Name	Datatype	Description
`hyperparameterTuningJobsId`	`string`
`locationsId`	`string`
`projectsId`	`string`
`filter`	`string`
`pageSize`	`integer (int32)`
`pageToken`	`string`
`readMask`	`string (google-fieldmask)`

`SELECT` examples

get
list

Gets a HyperparameterTuningJob

SELECT
name,
createTime,
displayName,
encryptionSpec,
endTime,
error,
labels,
maxFailedTrialCount,
maxTrialCount,
parallelTrialCount,
satisfiesPzi,
satisfiesPzs,
startTime,
state,
studySpec,
trialJobSpec,
trials,
updateTime
FROM google.aiplatform.hyperparameter_tuning_jobs
WHERE projectsId = '{{ projectsId }}' -- required
AND locationsId = '{{ locationsId }}' -- required
AND hyperparameterTuningJobsId = '{{ hyperparameterTuningJobsId }}' -- required;

Lists HyperparameterTuningJobs in a Location.

SELECT
name,
createTime,
displayName,
encryptionSpec,
endTime,
error,
labels,
maxFailedTrialCount,
maxTrialCount,
parallelTrialCount,
satisfiesPzi,
satisfiesPzs,
startTime,
state,
studySpec,
trialJobSpec,
trials,
updateTime
FROM google.aiplatform.hyperparameter_tuning_jobs
WHERE projectsId = '{{ projectsId }}' -- required
AND locationsId = '{{ locationsId }}' -- required
AND filter = '{{ filter }}'
AND pageSize = '{{ pageSize }}'
AND pageToken = '{{ pageToken }}'
AND readMask = '{{ readMask }}';

`INSERT` examples

create
Manifest

Creates a HyperparameterTuningJob

INSERT INTO google.aiplatform.hyperparameter_tuning_jobs (
data__displayName,
data__studySpec,
data__maxTrialCount,
data__parallelTrialCount,
data__maxFailedTrialCount,
data__trialJobSpec,
data__labels,
data__encryptionSpec,
projectsId,
locationsId
)
SELECT 
'{{ displayName }}',
'{{ studySpec }}',
{{ maxTrialCount }},
{{ parallelTrialCount }},
{{ maxFailedTrialCount }},
'{{ trialJobSpec }}',
'{{ labels }}',
'{{ encryptionSpec }}',
'{{ projectsId }}',
'{{ locationsId }}'
RETURNING
name,
createTime,
displayName,
encryptionSpec,
endTime,
error,
labels,
maxFailedTrialCount,
maxTrialCount,
parallelTrialCount,
satisfiesPzi,
satisfiesPzs,
startTime,
state,
studySpec,
trialJobSpec,
trials,
updateTime
;

# Description fields are for documentation purposes
- name: hyperparameter_tuning_jobs
  props:
    - name: projectsId
      value: string
      description: Required parameter for the hyperparameter_tuning_jobs resource.
    - name: locationsId
      value: string
      description: Required parameter for the hyperparameter_tuning_jobs resource.
    - name: displayName
      value: string
      description: >
        Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
        
    - name: studySpec
      value: object
      description: >
        Required. Study configuration of the HyperparameterTuningJob.
        
    - name: maxTrialCount
      value: integer
      description: >
        Required. The desired total number of Trials.
        
    - name: parallelTrialCount
      value: integer
      description: >
        Required. The desired number of Trials to run in parallel.
        
    - name: maxFailedTrialCount
      value: integer
      description: >
        The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
        
    - name: trialJobSpec
      value: object
      description: >
        Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.
        
    - name: labels
      value: object
      description: >
        The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
        
    - name: encryptionSpec
      value: object
      description: >
        Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.
        

`DELETE` examples

delete

Deletes a HyperparameterTuningJob.

DELETE FROM google.aiplatform.hyperparameter_tuning_jobs
WHERE projectsId = '{{ projectsId }}' --required
AND locationsId = '{{ locationsId }}' --required
AND hyperparameterTuningJobsId = '{{ hyperparameterTuningJobsId }}' --required;

Lifecycle Methods

cancel

Cancels a HyperparameterTuningJob. Starts asynchronous cancellation on the HyperparameterTuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetHyperparameterTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the HyperparameterTuningJob is not deleted; instead it becomes a job with a HyperparameterTuningJob.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED, and HyperparameterTuningJob.state is set to CANCELLED.

EXEC google.aiplatform.hyperparameter_tuning_jobs.cancel 
@projectsId='{{ projectsId }}' --required, 
@locationsId='{{ locationsId }}' --required, 
@hyperparameterTuningJobsId='{{ hyperparameterTuningJobsId }}' --required;

Overview​

Fields​

Methods​

Parameters​

SELECT examples​

INSERT examples​

DELETE examples​

Lifecycle Methods​