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JobServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1.services.job_service.transports.base.JobServiceTransport] = 'grpc_asyncio', client_options: <module 'google.api_core.client_options' from '/workspace/python-aiplatform/.nox/docfx/lib/python3.8/site-packages/google/api_core/client_options.py'> = 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 > JobServiceAsyncClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
JobServiceTransport | The transport used by the client instance. |
Methods
JobServiceAsyncClient
JobServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1.services.job_service.transports.base.JobServiceTransport] = 'grpc_asyncio', client_options: <module 'google.api_core.client_options' from '/workspace/python-aiplatform/.nox/docfx/lib/python3.8/site-packages/google/api_core/client_options.py'> = 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.
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 |
ClientOptions
Custom options for the client. It won't take effect if a |
Type | Description |
google.auth.exceptions.MutualTlsChannelError | If mutual TLS transport creation failed for any reason. |
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[google.cloud.aiplatform_v1.types.job_service.CancelBatchPredictionJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <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.
Name | Description |
request |
CancelBatchPredictionJobRequest
The request object. Request message for JobService.CancelBatchPredictionJob. |
name |
`str`
Required. The name of the BatchPredictionJob to cancel. Format: |
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[google.cloud.aiplatform_v1.types.job_service.CancelCustomJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <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
.
Name | Description |
request |
CancelCustomJobRequest
The request object. Request message for JobService.CancelCustomJob. |
name |
`str`
Required. The name of the CustomJob to cancel. Format: |
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[google.cloud.aiplatform_v1.types.job_service.CancelDataLabelingJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Cancels a DataLabelingJob. Success of cancellation is not guaranteed.
Name | Description |
request |
CancelDataLabelingJobRequest
The request object. Request message for JobService.CancelDataLabelingJob. |
name |
`str`
Required. The name of the DataLabelingJob. Format: |
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[google.cloud.aiplatform_v1.types.job_service.CancelHyperparameterTuningJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <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
.
Name | Description |
request |
CancelHyperparameterTuningJobRequest
The request object. Request message for JobService.CancelHyperparameterTuningJob. |
name |
`str`
Required. The name of the HyperparameterTuningJob to cancel. Format: |
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
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[google.cloud.aiplatform_v1.types.job_service.CreateBatchPredictionJobRequest] = None, *, parent: Optional[str] = None, batch_prediction_job: Optional[google.cloud.aiplatform_v1.types.batch_prediction_job.BatchPredictionJob] = None, retry: google.api_core.retry.Retry = <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.
Name | Description |
request |
CreateBatchPredictionJobRequest
The request object. Request message for JobService.CreateBatchPredictionJob. |
parent |
`str`
Required. The resource name of the Location to create the BatchPredictionJob in. Format: |
batch_prediction_job |
BatchPredictionJob
Required. The BatchPredictionJob to create. This corresponds to the |
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. |
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[google.cloud.aiplatform_v1.types.job_service.CreateCustomJobRequest] = None, *, parent: Optional[str] = None, custom_job: Optional[google.cloud.aiplatform_v1.types.custom_job.CustomJob] = None, retry: google.api_core.retry.Retry = <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.
Name | Description |
request |
CreateCustomJobRequest
The request object. Request message for JobService.CreateCustomJob. |
parent |
`str`
Required. The resource name of the Location to create the CustomJob in. Format: |
custom_job |
CustomJob
Required. The CustomJob to create. This corresponds to the |
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. |
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[google.cloud.aiplatform_v1.types.job_service.CreateDataLabelingJobRequest] = None, *, parent: Optional[str] = None, data_labeling_job: Optional[google.cloud.aiplatform_v1.types.data_labeling_job.DataLabelingJob] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a DataLabelingJob.
Name | Description |
request |
CreateDataLabelingJobRequest
The request object. Request message for JobService.CreateDataLabelingJob. |
parent |
`str`
Required. The parent of the DataLabelingJob. Format: |
data_labeling_job |
DataLabelingJob
Required. The DataLabelingJob to create. This corresponds to the |
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. |
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[google.cloud.aiplatform_v1.types.job_service.CreateHyperparameterTuningJobRequest] = None, *, parent: Optional[str] = None, hyperparameter_tuning_job: Optional[google.cloud.aiplatform_v1.types.hyperparameter_tuning_job.HyperparameterTuningJob] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a HyperparameterTuningJob
Name | Description |
request |
CreateHyperparameterTuningJobRequest
The request object. Request message for JobService.CreateHyperparameterTuningJob. |
parent |
`str`
Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: |
hyperparameter_tuning_job |
HyperparameterTuningJob
Required. The HyperparameterTuningJob to create. This corresponds to the |
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. |
Type | Description |
google.cloud.aiplatform_v1.types.HyperparameterTuningJob | Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification. |
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[google.cloud.aiplatform_v1.types.job_service.DeleteBatchPredictionJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a BatchPredictionJob. Can only be called on jobs that already finished.
Name | Description |
request |
DeleteBatchPredictionJobRequest
The request object. Request message for JobService.DeleteBatchPredictionJob. |
name |
`str`
Required. The name of the BatchPredictionJob resource to be deleted. Format: |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | 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[google.cloud.aiplatform_v1.types.job_service.DeleteCustomJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a CustomJob.
Name | Description |
request |
DeleteCustomJobRequest
The request object. Request message for JobService.DeleteCustomJob. |
name |
`str`
Required. The name of the CustomJob resource to be deleted. Format: |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | 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[google.cloud.aiplatform_v1.types.job_service.DeleteDataLabelingJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a DataLabelingJob.
Name | Description |
request |
DeleteDataLabelingJobRequest
The request object. Request message for JobService.DeleteDataLabelingJob. |
name |
`str`
Required. The name of the DataLabelingJob to be deleted. Format: |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | 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[google.cloud.aiplatform_v1.types.job_service.DeleteHyperparameterTuningJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a HyperparameterTuningJob.
Name | Description |
request |
DeleteHyperparameterTuningJobRequest
The request object. Request message for JobService.DeleteHyperparameterTuningJob. |
name |
`str`
Required. The name of the HyperparameterTuningJob resource to be deleted. Format: |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | 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 {}. |
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
JobServiceAsyncClient | The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
JobServiceAsyncClient | The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
JobServiceAsyncClient | The constructed client. |
get_batch_prediction_job
get_batch_prediction_job(request: Optional[google.cloud.aiplatform_v1.types.job_service.GetBatchPredictionJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a BatchPredictionJob
Name | Description |
request |
GetBatchPredictionJobRequest
The request object. Request message for JobService.GetBatchPredictionJob. |
name |
`str`
Required. The name of the BatchPredictionJob resource. Format: |
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. |
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[google.cloud.aiplatform_v1.types.job_service.GetCustomJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a CustomJob.
Name | Description |
request |
GetCustomJobRequest
The request object. Request message for JobService.GetCustomJob. |
name |
`str`
Required. The name of the CustomJob resource. Format: |
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. |
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[google.cloud.aiplatform_v1.types.job_service.GetDataLabelingJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a DataLabelingJob.
Name | Description |
request |
GetDataLabelingJobRequest
The request object. Request message for JobService.GetDataLabelingJob. |
name |
`str`
Required. The name of the DataLabelingJob. Format: |
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. |
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[google.cloud.aiplatform_v1.types.job_service.GetHyperparameterTuningJobRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a HyperparameterTuningJob
Name | Description |
request |
GetHyperparameterTuningJobRequest
The request object. Request message for JobService.GetHyperparameterTuningJob. |
name |
`str`
Required. The name of the HyperparameterTuningJob resource. Format: |
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. |
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_transport_class
get_transport_class()
Returns an appropriate transport class.
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[google.cloud.aiplatform_v1.types.job_service.ListBatchPredictionJobsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists BatchPredictionJobs in a Location.
Name | Description |
request |
ListBatchPredictionJobsRequest
The request object. Request message for JobService.ListBatchPredictionJobs. |
parent |
`str`
Required. The resource name of the Location to list the BatchPredictionJobs from. Format: |
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. |
Type | Description |
google.cloud.aiplatform_v1.services.job_service.pagers.ListBatchPredictionJobsAsyncPager | 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[google.cloud.aiplatform_v1.types.job_service.ListCustomJobsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists CustomJobs in a Location.
Name | Description |
request |
ListCustomJobsRequest
The request object. Request message for JobService.ListCustomJobs. |
parent |
`str`
Required. The resource name of the Location to list the CustomJobs from. Format: |
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. |
Type | Description |
google.cloud.aiplatform_v1.services.job_service.pagers.ListCustomJobsAsyncPager | 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[google.cloud.aiplatform_v1.types.job_service.ListDataLabelingJobsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists DataLabelingJobs in a Location.
Name | Description |
request |
ListDataLabelingJobsRequest
The request object. Request message for JobService.ListDataLabelingJobs. |
parent |
`str`
Required. The parent of the DataLabelingJob. Format: |
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. |
Type | Description |
google.cloud.aiplatform_v1.services.job_service.pagers.ListDataLabelingJobsAsyncPager | 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[google.cloud.aiplatform_v1.types.job_service.ListHyperparameterTuningJobsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists HyperparameterTuningJobs in a Location.
Name | Description |
request |
ListHyperparameterTuningJobsRequest
The request object. Request message for JobService.ListHyperparameterTuningJobs. |
parent |
`str`
Required. The resource name of the Location to list the HyperparameterTuningJobs from. Format: |
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. |
Type | Description |
google.cloud.aiplatform_v1.services.job_service.pagers.ListHyperparameterTuningJobsAsyncPager | Response message for JobService.ListHyperparameterTuningJobs Iterating over this object will yield results and resolve additional pages automatically. |
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
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_hyperparameter_tuning_job_path
parse_hyperparameter_tuning_job_path(path: str)
Parses a hyperparameter_tuning_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_trial_path
parse_trial_path(path: str)
Parses a trial path into its component segments.
trial_path
trial_path(project: str, location: str, study: str, trial: str)
Returns a fully-qualified trial string.