Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
Parameters:
-
human_task_ui_name
(Optional[HumanTaskUiName], default:
None
)
–
The name of the user interface you are creating.
-
tags
(Optional[TagList], default:
None
)
–
An array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.
Raises:
-
ResourceInUse
–
Resource being accessed is in use.
-
ResourceLimitExceeded
–
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
-
UnknownServiceError
–
The service returned an error code this client does not model.
Source code in docs_src/capo_sagemaker/_services/sage_maker.py
| def create_human_task_ui(
self,
*,
config_overrides: Optional[SageMakerClientConfig] = None,
human_task_ui_name: Optional[
"capo_sagemaker.types.human_task_ui_name.HumanTaskUiName"
] = None,
ui_template: Optional["capo_sagemaker.types.ui_template.UiTemplate"] = None,
tags: Optional["capo_sagemaker.types.tag_list.TagList"] = None,
) -> "capo_sagemaker.types.create_human_task_ui_response.CreateHumanTaskUiResponse":
"""<p>Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.</p>
Args:
human_task_ui_name: <p>The name of the user interface you are creating.</p>
tags: <p>An array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.</p>
Raises:
capo_sagemaker.errors.resource_in_use.ResourceInUse: <p>Resource being accessed is in use.</p>
capo_sagemaker.errors.resource_limit_exceeded.ResourceLimitExceeded: <p> You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. </p>
capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_sagemaker.types.create_human_task_ui_request.CreateHumanTaskUiRequest]",
) -> OperationResponse[
"capo_sagemaker.types.create_human_task_ui_response.CreateHumanTaskUiResponse"
]:
import capo_sagemaker._operations.sage_maker.create_human_task_ui
output, http_response = (
capo_sagemaker._operations.sage_maker.create_human_task_ui.create_human_task_ui(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("CreateHumanTaskUi")
)
input_: capo_sagemaker.types.create_human_task_ui_request.CreateHumanTaskUiRequest = {}
if human_task_ui_name is not None:
input_["human_task_ui_name"] = human_task_ui_name
if ui_template is not None:
input_["ui_template"] = ui_template
if tags is not None:
input_["tags"] = tags
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|