Class JobServiceClient (1.10.0)

  JobServiceClient 
 ( 
 * 
 , 
 credentials 
 : 
 Optional 
 [ 
 google 
 . 
 auth 
 . 
 credentials 
 . 
 Credentials 
 ] 
 = 
 None 
 , 
 transport 
 : 
 Optional 
 [ 
 Union 
 [ 
 str 
 , 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 services 
 . 
 job_service 
 . 
 transports 
 . 
 base 
 . 
 JobServiceTransport 
 ]] 
 = 
 None 
 , 
 client_options 
 : 
 Optional 
 [ 
 google 
 . 
 api_core 
 . 
 client_options 
 . 
 ClientOptions 
 ] 
 = 
 None 
 , 
 client_info 
 : 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 client_info 
 . 
 ClientInfo 
 = 
< google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 client_info 
 . 
 ClientInfo 
 object 
> )

A service for creating and managing Vertex AI's jobs.

Inheritance

builtins.object > JobServiceClient

Properties

transport

Returns the transport used by the client instance.

Returns
Type Description
JobServiceTransport The transport used by the client instance.

Methods

JobServiceClient

  JobServiceClient 
 ( 
 * 
 , 
 credentials 
 : 
 Optional 
 [ 
 google 
 . 
 auth 
 . 
 credentials 
 . 
 Credentials 
 ] 
 = 
 None 
 , 
 transport 
 : 
 Optional 
 [ 
 Union 
 [ 
 str 
 , 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 services 
 . 
 job_service 
 . 
 transports 
 . 
 base 
 . 
 JobServiceTransport 
 ]] 
 = 
 None 
 , 
 client_options 
 : 
 Optional 
 [ 
 google 
 . 
 api_core 
 . 
 client_options 
 . 
 ClientOptions 
 ] 
 = 
 None 
 , 
 client_info 
 : 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 client_info 
 . 
 ClientInfo 
 = 
< google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 client_info 
 . 
 ClientInfo 
 object 
> )

Instantiates the job service client.

Parameters
Name Description
credentials Optional[google.auth.credentials.Credentials]

The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport Union[str, JobServiceTransport]

The transport to use. If set to None, a transport is chosen automatically.
client_options google.api_core.client_options.ClientOptions

Custom options for the client. It won't take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.
client_info google.api_core.gapic_v1.client_info.ClientInfo

The client info used to send a user-agent string along with API requests. If None , then default info will be used. Generally, you only need to set this if you're developing your own client library.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If mutual TLS transport creation failed for any reason.

__exit__

  __exit__ 
 ( 
 type 
 , 
 value 
 , 
 traceback 
 )

Releases underlying transport's resources.

batch_prediction_job_path

  batch_prediction_job_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 batch_prediction_job 
 : 
 str 
 )

Returns a fully-qualified batch_prediction_job string.

cancel_batch_prediction_job

  cancel_batch_prediction_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CancelBatchPredictionJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Cancels a BatchPredictionJob.

Starts asynchronous cancellation on the BatchPredictionJob. The server makes the best effort to cancel the job, but success is not guaranteed. Clients can use xref_JobService.GetBatchPredictionJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On a successful cancellation, the BatchPredictionJob is not deleted;instead its xref_BatchPredictionJob.state is set to CANCELLED . Any files already outputted by the job are not deleted.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CancelBatchPredictionJobRequest , dict]

The request object. Request message for JobService.CancelBatchPredictionJob .
name str

Required. The name of the BatchPredictionJob to cancel. Format: projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

cancel_custom_job

  cancel_custom_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CancelCustomJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

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

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CancelCustomJobRequest , dict]

The request object. Request message for JobService.CancelCustomJob .
name str

Required. The name of the CustomJob to cancel. Format: projects/{project}/locations/{location}/customJobs/{custom_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

cancel_data_labeling_job

  cancel_data_labeling_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CancelDataLabelingJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Cancels a DataLabelingJob. Success of cancellation is not guaranteed.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CancelDataLabelingJobRequest , dict]

The request object. Request message for JobService.CancelDataLabelingJob .
name str

Required. The name of the DataLabelingJob. Format: projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

cancel_hyperparameter_tuning_job

  cancel_hyperparameter_tuning_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CancelHyperparameterTuningJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

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 xref_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 xref_HyperparameterTuningJob.error value with a google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED , and xref_HyperparameterTuningJob.state is set to CANCELLED .

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CancelHyperparameterTuningJobRequest , dict]

The request object. Request message for JobService.CancelHyperparameterTuningJob .
name str

Required. The name of the HyperparameterTuningJob to cancel. Format: projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

 
  common_billing_account_path 
 ( 
 billing_account 
 : 
 str 
 )

Returns a fully-qualified billing_account string.

common_folder_path

  common_folder_path 
 ( 
 folder 
 : 
 str 
 )

Returns a fully-qualified folder string.

common_location_path

  common_location_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 )

Returns a fully-qualified location string.

common_organization_path

  common_organization_path 
 ( 
 organization 
 : 
 str 
 )

Returns a fully-qualified organization string.

common_project_path

  common_project_path 
 ( 
 project 
 : 
 str 
 )

Returns a fully-qualified project string.

create_batch_prediction_job

  create_batch_prediction_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CreateBatchPredictionJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 batch_prediction_job 
 : 
 Optional 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 batch_prediction_job 
 . 
 BatchPredictionJob 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CreateBatchPredictionJobRequest , dict]

The request object. Request message for JobService.CreateBatchPredictionJob .
parent str

Required. The resource name of the Location to create the BatchPredictionJob in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
batch_prediction_job google.cloud.aiplatform_v1.types.BatchPredictionJob

Required. The BatchPredictionJob to create. This corresponds to the batch_prediction_job field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.BatchPredictionJob A job that uses a Model to produce predictions on multiple [input instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.

create_custom_job

  create_custom_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CreateCustomJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 custom_job 
 : 
 Optional 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 custom_job 
 . 
 CustomJob 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Creates a CustomJob. A created CustomJob right away will be attempted to be run.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CreateCustomJobRequest , dict]

The request object. Request message for JobService.CreateCustomJob .
parent str

Required. The resource name of the Location to create the CustomJob in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
custom_job google.cloud.aiplatform_v1.types.CustomJob

Required. The CustomJob to create. This corresponds to the custom_job field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.CustomJob Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).

create_data_labeling_job

  create_data_labeling_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CreateDataLabelingJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 data_labeling_job 
 : 
 Optional 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 data_labeling_job 
 . 
 DataLabelingJob 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Creates a DataLabelingJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CreateDataLabelingJobRequest , dict]

The request object. Request message for JobService.CreateDataLabelingJob .
parent str

Required. The parent of the DataLabelingJob. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
data_labeling_job google.cloud.aiplatform_v1.types.DataLabelingJob

Required. The DataLabelingJob to create. This corresponds to the data_labeling_job field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.DataLabelingJob DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:

create_hyperparameter_tuning_job

  create_hyperparameter_tuning_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CreateHyperparameterTuningJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 hyperparameter_tuning_job 
 : 
 Optional 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 hyperparameter_tuning_job 
 . 
 HyperparameterTuningJob 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Creates a HyperparameterTuningJob

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CreateHyperparameterTuningJobRequest , dict]

The request object. Request message for JobService.CreateHyperparameterTuningJob .
parent str

Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
hyperparameter_tuning_job google.cloud.aiplatform_v1.types.HyperparameterTuningJob

Required. The HyperparameterTuningJob to create. This corresponds to the hyperparameter_tuning_job field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.HyperparameterTuningJob Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.

create_model_deployment_monitoring_job

  create_model_deployment_monitoring_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 CreateModelDeploymentMonitoringJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 model_deployment_monitoring_job 
 : 
 Optional 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 model_deployment_monitoring_job 
 . 
 ModelDeploymentMonitoringJob 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.CreateModelDeploymentMonitoringJobRequest , dict]

The request object. Request message for JobService.CreateModelDeploymentMonitoringJob .
parent str

Required. The parent of the ModelDeploymentMonitoringJob. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
model_deployment_monitoring_job google.cloud.aiplatform_v1.types.ModelDeploymentMonitoringJob

Required. The ModelDeploymentMonitoringJob to create This corresponds to the model_deployment_monitoring_job field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.ModelDeploymentMonitoringJob Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.

custom_job_path

  custom_job_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 custom_job 
 : 
 str 
 )

Returns a fully-qualified custom_job string.

data_labeling_job_path

  data_labeling_job_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 data_labeling_job 
 : 
 str 
 )

Returns a fully-qualified data_labeling_job string.

dataset_path

  dataset_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 dataset 
 : 
 str 
 )

Returns a fully-qualified dataset string.

delete_batch_prediction_job

  delete_batch_prediction_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 DeleteBatchPredictionJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Deletes a BatchPredictionJob. Can only be called on jobs that already finished.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.DeleteBatchPredictionJobRequest , dict]

The request object. Request message for JobService.DeleteBatchPredictionJob .
name str

Required. The name of the BatchPredictionJob resource to be deleted. Format: projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

delete_custom_job

  delete_custom_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 DeleteCustomJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Deletes a CustomJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.DeleteCustomJobRequest , dict]

The request object. Request message for JobService.DeleteCustomJob .
name str

Required. The name of the CustomJob resource to be deleted. Format: projects/{project}/locations/{location}/customJobs/{custom_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

delete_data_labeling_job

  delete_data_labeling_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 DeleteDataLabelingJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Deletes a DataLabelingJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.DeleteDataLabelingJobRequest , dict]

The request object. Request message for JobService.DeleteDataLabelingJob .
name str

Required. The name of the DataLabelingJob to be deleted. Format: projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

delete_hyperparameter_tuning_job

  delete_hyperparameter_tuning_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 DeleteHyperparameterTuningJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Deletes a HyperparameterTuningJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.DeleteHyperparameterTuningJobRequest , dict]

The request object. Request message for JobService.DeleteHyperparameterTuningJob .
name str

Required. The name of the HyperparameterTuningJob resource to be deleted. Format: projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

delete_model_deployment_monitoring_job

  delete_model_deployment_monitoring_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 DeleteModelDeploymentMonitoringJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Deletes a ModelDeploymentMonitoringJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.DeleteModelDeploymentMonitoringJobRequest , dict]

The request object. Request message for JobService.DeleteModelDeploymentMonitoringJob .
name str

Required. The resource name of the model monitoring job to delete. Format: projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

endpoint_path

  endpoint_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 endpoint 
 : 
 str 
 )

Returns a fully-qualified endpoint string.

  from_service_account_file 
 ( 
 filename 
 : 
 str 
 , 
 * 
 args 
 , 
 ** 
 kwargs 
 )

Creates an instance of this client using the provided credentials file.

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
JobServiceClient The constructed client. 
  from_service_account_info 
 ( 
 info 
 : 
 dict 
 , 
 * 
 args 
 , 
 ** 
 kwargs 
 )

Creates an instance of this client using the provided credentials info.

Parameter
Name Description
info dict

The service account private key info.
Returns
Type Description
JobServiceClient The constructed client. 
  from_service_account_json 
 ( 
 filename 
 : 
 str 
 , 
 * 
 args 
 , 
 ** 
 kwargs 
 )

Creates an instance of this client using the provided credentials file.

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
JobServiceClient The constructed client.

get_batch_prediction_job

  get_batch_prediction_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 GetBatchPredictionJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Gets a BatchPredictionJob

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.GetBatchPredictionJobRequest , dict]

The request object. Request message for JobService.GetBatchPredictionJob .
name str

Required. The name of the BatchPredictionJob resource. Format: projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.BatchPredictionJob A job that uses a Model to produce predictions on multiple [input instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.

get_custom_job

  get_custom_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 GetCustomJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Gets a CustomJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.GetCustomJobRequest , dict]

The request object. Request message for JobService.GetCustomJob .
name str

Required. The name of the CustomJob resource. Format: projects/{project}/locations/{location}/customJobs/{custom_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.CustomJob Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).

get_data_labeling_job

  get_data_labeling_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 GetDataLabelingJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Gets a DataLabelingJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.GetDataLabelingJobRequest , dict]

The request object. Request message for JobService.GetDataLabelingJob .
name str

Required. The name of the DataLabelingJob. Format: projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.DataLabelingJob DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:

get_hyperparameter_tuning_job

  get_hyperparameter_tuning_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 GetHyperparameterTuningJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Gets a HyperparameterTuningJob

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.GetHyperparameterTuningJobRequest , dict]

The request object. Request message for JobService.GetHyperparameterTuningJob .
name str

Required. The name of the HyperparameterTuningJob resource. Format: projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.HyperparameterTuningJob Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.

get_model_deployment_monitoring_job

  get_model_deployment_monitoring_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 GetModelDeploymentMonitoringJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Gets a ModelDeploymentMonitoringJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.GetModelDeploymentMonitoringJobRequest , dict]

The request object. Request message for JobService.GetModelDeploymentMonitoringJob .
name str

Required. The resource name of the ModelDeploymentMonitoringJob. Format: projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.ModelDeploymentMonitoringJob Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.

get_mtls_endpoint_and_cert_source

  get_mtls_endpoint_and_cert_source 
 ( 
 client_options 
 : 
 Optional 
 [ 
 google 
 . 
 api_core 
 . 
 client_options 
 . 
 ClientOptions 
 ] 
 = 
 None 
 , 
 )

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variabel is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114 .

Parameter
Name Description
client_options google.api_core.client_options.ClientOptions

Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If any errors happen.
Returns
Type Description
Tuple[str, Callable[[], Tuple[bytes, bytes]]] returns the API endpoint and the client cert source to use.

hyperparameter_tuning_job_path

  hyperparameter_tuning_job_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 hyperparameter_tuning_job 
 : 
 str 
 )

Returns a fully-qualified hyperparameter_tuning_job string.

list_batch_prediction_jobs

  list_batch_prediction_jobs 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 ListBatchPredictionJobsRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Lists BatchPredictionJobs in a Location.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.ListBatchPredictionJobsRequest , dict]

The request object. Request message for JobService.ListBatchPredictionJobs .
parent str

Required. The resource name of the Location to list the BatchPredictionJobs from. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.job_service.pagers.ListBatchPredictionJobsPager Response message for JobService.ListBatchPredictionJobs Iterating over this object will yield results and resolve additional pages automatically.

list_custom_jobs

  list_custom_jobs 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 ListCustomJobsRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Lists CustomJobs in a Location.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.ListCustomJobsRequest , dict]

The request object. Request message for JobService.ListCustomJobs .
parent str

Required. The resource name of the Location to list the CustomJobs from. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.job_service.pagers.ListCustomJobsPager Response message for JobService.ListCustomJobs Iterating over this object will yield results and resolve additional pages automatically.

list_data_labeling_jobs

  list_data_labeling_jobs 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 ListDataLabelingJobsRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Lists DataLabelingJobs in a Location.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.ListDataLabelingJobsRequest , dict]

The request object. Request message for JobService.ListDataLabelingJobs .
parent str

Required. The parent of the DataLabelingJob. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.job_service.pagers.ListDataLabelingJobsPager Response message for JobService.ListDataLabelingJobs . Iterating over this object will yield results and resolve additional pages automatically.

list_hyperparameter_tuning_jobs

  list_hyperparameter_tuning_jobs 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 ListHyperparameterTuningJobsRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Lists HyperparameterTuningJobs in a Location.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.ListHyperparameterTuningJobsRequest , dict]

The request object. Request message for JobService.ListHyperparameterTuningJobs .
parent str

Required. The resource name of the Location to list the HyperparameterTuningJobs from. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.job_service.pagers.ListHyperparameterTuningJobsPager Response message for JobService.ListHyperparameterTuningJobs Iterating over this object will yield results and resolve additional pages automatically.

list_model_deployment_monitoring_jobs

  list_model_deployment_monitoring_jobs 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 ListModelDeploymentMonitoringJobsRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 parent 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Lists ModelDeploymentMonitoringJobs in a Location.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.ListModelDeploymentMonitoringJobsRequest , dict]

The request object. Request message for JobService.ListModelDeploymentMonitoringJobs .
parent str

Required. The parent of the ModelDeploymentMonitoringJob. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.job_service.pagers.ListModelDeploymentMonitoringJobsPager Response message for JobService.ListModelDeploymentMonitoringJobs . Iterating over this object will yield results and resolve additional pages automatically.

model_deployment_monitoring_job_path

  model_deployment_monitoring_job_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 model_deployment_monitoring_job 
 : 
 str 
 )

Returns a fully-qualified model_deployment_monitoring_job string.

model_path

  model_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 model 
 : 
 str 
 )

Returns a fully-qualified model string.

network_path

  network_path 
 ( 
 project 
 : 
 str 
 , 
 network 
 : 
 str 
 )

Returns a fully-qualified network string.

parse_batch_prediction_job_path

  parse_batch_prediction_job_path 
 ( 
 path 
 : 
 str 
 )

Parses a batch_prediction_job path into its component segments.

  parse_common_billing_account_path 
 ( 
 path 
 : 
 str 
 )

Parse a billing_account path into its component segments.

parse_common_folder_path

  parse_common_folder_path 
 ( 
 path 
 : 
 str 
 )

Parse a folder path into its component segments.

parse_common_location_path

  parse_common_location_path 
 ( 
 path 
 : 
 str 
 )

Parse a location path into its component segments.

parse_common_organization_path

  parse_common_organization_path 
 ( 
 path 
 : 
 str 
 )

Parse a organization path into its component segments.

parse_common_project_path

  parse_common_project_path 
 ( 
 path 
 : 
 str 
 )

Parse a project path into its component segments.

parse_custom_job_path

  parse_custom_job_path 
 ( 
 path 
 : 
 str 
 )

Parses a custom_job path into its component segments.

parse_data_labeling_job_path

  parse_data_labeling_job_path 
 ( 
 path 
 : 
 str 
 )

Parses a data_labeling_job path into its component segments.

parse_dataset_path

  parse_dataset_path 
 ( 
 path 
 : 
 str 
 )

Parses a dataset path into its component segments.

parse_endpoint_path

  parse_endpoint_path 
 ( 
 path 
 : 
 str 
 )

Parses a endpoint path into its component segments.

parse_hyperparameter_tuning_job_path

  parse_hyperparameter_tuning_job_path 
 ( 
 path 
 : 
 str 
 )

Parses a hyperparameter_tuning_job path into its component segments.

parse_model_deployment_monitoring_job_path

  parse_model_deployment_monitoring_job_path 
 ( 
 path 
 : 
 str 
 )

Parses a model_deployment_monitoring_job path into its component segments.

parse_model_path

  parse_model_path 
 ( 
 path 
 : 
 str 
 )

Parses a model path into its component segments.

parse_network_path

  parse_network_path 
 ( 
 path 
 : 
 str 
 )

Parses a network path into its component segments.

parse_tensorboard_path

  parse_tensorboard_path 
 ( 
 path 
 : 
 str 
 )

Parses a tensorboard path into its component segments.

parse_trial_path

  parse_trial_path 
 ( 
 path 
 : 
 str 
 )

Parses a trial path into its component segments.

pause_model_deployment_monitoring_job

  pause_model_deployment_monitoring_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 PauseModelDeploymentMonitoringJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Pauses a ModelDeploymentMonitoringJob. If the job is running, the server makes a best effort to cancel the job. Will mark xref_ModelDeploymentMonitoringJob.state to 'PAUSED'.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.PauseModelDeploymentMonitoringJobRequest , dict]

The request object. Request message for JobService.PauseModelDeploymentMonitoringJob .
name str

Required. The resource name of the ModelDeploymentMonitoringJob to pause. Format: projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

resume_model_deployment_monitoring_job

  resume_model_deployment_monitoring_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 ResumeModelDeploymentMonitoringJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 name 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Resumes a paused ModelDeploymentMonitoringJob. It will start to run from next scheduled time. A deleted ModelDeploymentMonitoringJob can't be resumed.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.ResumeModelDeploymentMonitoringJobRequest , dict]

The request object. Request message for JobService.ResumeModelDeploymentMonitoringJob .
name str

Required. The resource name of the ModelDeploymentMonitoringJob to resume. Format: projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

search_model_deployment_monitoring_stats_anomalies

  search_model_deployment_monitoring_stats_anomalies 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 SearchModelDeploymentMonitoringStatsAnomaliesRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 model_deployment_monitoring_job 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 deployed_model_id 
 : 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Searches Model Monitoring Statistics generated within a given time window.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.SearchModelDeploymentMonitoringStatsAnomaliesRequest , dict]

The request object. Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies .
model_deployment_monitoring_job str

Required. ModelDeploymentMonitoring Job resource name. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job} This corresponds to the model_deployment_monitoring_job field on the request instance; if request is provided, this should not be set.
deployed_model_id str

Required. The DeployedModel ID of the [ModelDeploymentMonitoringObjectiveConfig.deployed_model_id]. This corresponds to the deployed_model_id field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.job_service.pagers.SearchModelDeploymentMonitoringStatsAnomaliesPager Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies . Iterating over this object will yield results and resolve additional pages automatically.

tensorboard_path

  tensorboard_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 tensorboard 
 : 
 str 
 )

Returns a fully-qualified tensorboard string.

trial_path

  trial_path 
 ( 
 project 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 study 
 : 
 str 
 , 
 trial 
 : 
 str 
 )

Returns a fully-qualified trial string.

update_model_deployment_monitoring_job

  update_model_deployment_monitoring_job 
 ( 
 request 
 : 
 Optional 
 [ 
 Union 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 job_service 
 . 
 UpdateModelDeploymentMonitoringJobRequest 
 , 
 dict 
 ]] 
 = 
 None 
 , 
 * 
 , 
 model_deployment_monitoring_job 
 : 
 Optional 
 [ 
 google 
 . 
 cloud 
 . 
 aiplatform_v1 
 . 
 types 
 . 
 model_deployment_monitoring_job 
 . 
 ModelDeploymentMonitoringJob 
 ] 
 = 
 None 
 , 
 update_mask 
 : 
 Optional 
 [ 
 google 
 . 
 protobuf 
 . 
 field_mask_pb2 
 . 
 FieldMask 
 ] 
 = 
 None 
 , 
 retry 
 : 
 Union 
 [ 
 google 
 . 
 api_core 
 . 
 retry 
 . 
 Retry 
 , 
 google 
 . 
 api_core 
 . 
 gapic_v1 
 . 
 method 
 . 
 _MethodDefault 
 ] 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 : 
 Optional 
 [ 
 float 
 ] 
 = 
 None 
 , 
 metadata 
 : 
 Sequence 
 [ 
 Tuple 
 [ 
 str 
 , 
 str 
 ]] 
 = 
 ())

Updates a ModelDeploymentMonitoringJob.

Parameters
Name Description
request Union[ google.cloud.aiplatform_v1.types.UpdateModelDeploymentMonitoringJobRequest , dict]

The request object. Request message for JobService.UpdateModelDeploymentMonitoringJob .
model_deployment_monitoring_job google.cloud.aiplatform_v1.types.ModelDeploymentMonitoringJob

Required. The model monitoring configuration which replaces the resource on the server. This corresponds to the model_deployment_monitoring_job field on the request instance; if request is provided, this should not be set.
update_mask google.protobuf.field_mask_pb2.FieldMask

Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields. For the objective config, the user can either provide the update mask for model_deployment_monitoring_objective_configs or any combination of its nested fields, such as: model_deployment_monitoring_objective_configs.objective_config.training_dataset. Updatable fields: - display_name - model_deployment_monitoring_schedule_config - model_monitoring_alert_config - logging_sampling_strategy - labels - log_ttl - enable_monitoring_pipeline_logs . and - model_deployment_monitoring_objective_configs . or - model_deployment_monitoring_objective_configs.objective_config.training_dataset - model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config - model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be ModelDeploymentMonitoringJob Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.