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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 AI Platform's jobs.
Inheritance
builtins.object > JobServiceClientProperties
transport
Return the transport used by the client instance.
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>)
Instantiate 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 |
google.api_core.client_options.ClientOptions
Custom options for the client. It won't take effect if a |
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 |
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)
Return 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
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
BatchPredictionJob.state
is set to CANCELLED
. Any files already outputted by the job
are not deleted.
Name | Description |
request |
google.cloud.aiplatform_v1.types.CancelBatchPredictionJobRequest
The request object. Request message for |
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
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
CustomJob.error
value with a google.rpc.Status.code
of
1, corresponding to Code.CANCELLED
, and
CustomJob.state
is
set to CANCELLED
.
Name | Description |
request |
google.cloud.aiplatform_v1.types.CancelCustomJobRequest
The request object. Request message for |
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 |
google.cloud.aiplatform_v1.types.CancelDataLabelingJobRequest
The request object. Request message for [DataLabelingJobService.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
JobService.GetHyperparameterTuningJob
or other methods to check whether the cancellation succeeded or
whether the job completed despite cancellation. On successful
cancellation, the HyperparameterTuningJob is not deleted;
instead it becomes a job with a
HyperparameterTuningJob.error
value with a google.rpc.Status.code
of
1, corresponding to Code.CANCELLED
, and
HyperparameterTuningJob.state
is set to CANCELLED
.
Name | Description |
request |
google.cloud.aiplatform_v1.types.CancelHyperparameterTuningJobRequest
The request object. Request message for |
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)
Return a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str)
Return a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str)
Return a fully-qualified location string.
common_organization_path
common_organization_path(organization: str)
Return a fully-qualified organization string.
common_project_path
common_project_path(project: str)
Return 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 |
google.cloud.aiplatform_v1.types.CreateBatchPredictionJobRequest
The request object. Request message for |
parent |
str
Required. The resource name of the Location to create the BatchPredictionJob in. Format: |
batch_prediction_job |
google.cloud.aiplatform_v1.types.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 |
google.cloud.aiplatform_v1.types.CreateCustomJobRequest
The request object. Request message for |
parent |
str
Required. The resource name of the Location to create the CustomJob in. Format: |
custom_job |
google.cloud.aiplatform_v1.types.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 |
google.cloud.aiplatform_v1.types.CreateDataLabelingJobRequest
The request object. Request message for [DataLabelingJobService.CreateDataLabelingJob][]. |
parent |
str
Required. The parent of the DataLabelingJob. Format: |
data_labeling_job |
google.cloud.aiplatform_v1.types.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 |
google.cloud.aiplatform_v1.types.CreateHyperparameterTuningJobRequest
The request object. Request message for |
parent |
str
Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: |
hyperparameter_tuning_job |
google.cloud.aiplatform_v1.types.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)
Return a fully-qualified custom_job string.
data_labeling_job_path
data_labeling_job_path(project: str, location: str, data_labeling_job: str)
Return a fully-qualified data_labeling_job string.
dataset_path
dataset_path(project: str, location: str, dataset: str)
Return 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 |
google.cloud.aiplatform_v1.types.DeleteBatchPredictionJobRequest
The request object. Request message for |
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.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[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 |
google.cloud.aiplatform_v1.types.DeleteCustomJobRequest
The request object. Request message for |
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.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[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 |
google.cloud.aiplatform_v1.types.DeleteDataLabelingJobRequest
The request object. Request message for |
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.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[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 |
google.cloud.aiplatform_v1.types.DeleteHyperparameterTuningJobRequest
The request object. Request message for |
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.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 {}. |
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 |
JobServiceClient | 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 |
JobServiceClient | 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 |
JobServiceClient | 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 |
google.cloud.aiplatform_v1.types.GetBatchPredictionJobRequest
The request object. Request message for |
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 |
google.cloud.aiplatform_v1.types.GetCustomJobRequest
The request object. Request message for |
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 |
google.cloud.aiplatform_v1.types.GetDataLabelingJobRequest
The request object. Request message for [DataLabelingJobService.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 |
google.cloud.aiplatform_v1.types.GetHyperparameterTuningJobRequest
The request object. Request message for |
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. |
hyperparameter_tuning_job_path
hyperparameter_tuning_job_path(
project: str, location: str, hyperparameter_tuning_job: str
)
Return 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 |
google.cloud.aiplatform_v1.types.ListBatchPredictionJobsRequest
The request object. Request message for |
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.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[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 |
google.cloud.aiplatform_v1.types.ListCustomJobsRequest
The request object. Request message for |
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.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[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 |
google.cloud.aiplatform_v1.types.ListDataLabelingJobsRequest
The request object. Request message for [DataLabelingJobService.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.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[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 |
google.cloud.aiplatform_v1.types.ListHyperparameterTuningJobsRequest
The request object. Request message for |
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.ListHyperparameterTuningJobsPager | 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)
Return a fully-qualified model string.
parse_batch_prediction_job_path
parse_batch_prediction_job_path(path: str)
Parse 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)
Parse a custom_job path into its component segments.
parse_data_labeling_job_path
parse_data_labeling_job_path(path: str)
Parse a data_labeling_job path into its component segments.
parse_dataset_path
parse_dataset_path(path: str)
Parse a dataset path into its component segments.
parse_hyperparameter_tuning_job_path
parse_hyperparameter_tuning_job_path(path: str)
Parse a hyperparameter_tuning_job path into its component segments.
parse_model_path
parse_model_path(path: str)
Parse a model path into its component segments.
parse_trial_path
parse_trial_path(path: str)
Parse a trial path into its component segments.
trial_path
trial_path(project: str, location: str, study: str, trial: str)
Return a fully-qualified trial string.