def describe_training_job(client, training_job_name): return client.describe_training_job(TrainingJobName=training_job_name) def describe_model(client, model_name): return client.describe_model(ModelName=model_name) def describe_endpoint(client, endpoint_name): return client.describe_endpoint(EndpointName=endpoint_name) def delete_endpoint(client, endpoint_name): client.delete_endpoint(EndpointName=endpoint_name) waiter = client.get_waiter("endpoint_deleted") waiter.wait(EndpointName=endpoint_name) def describe_hpo_job(client, job_name): return client.describe_hyper_parameter_tuning_job( HyperParameterTuningJobName=job_name ) def describe_transform_job(client, job_name): return client.describe_transform_job(TransformJobName=job_name) def describe_workteam(client, workteam_name): return client.describe_workteam(WorkteamName=workteam_name) def list_workteams(client): return client.list_workteams() def get_cognito_member_definitions(client): # This is one way to get the user_pool and client_id for the SageMaker Workforce. # An alternative would be to take these values as user input via params or a config file. # The current mechanism expects that there exists atleast one private workteam in the region. default_workteam = list_workteams(client)["Workteams"][0]["MemberDefinitions"][0][ "CognitoMemberDefinition" ] return ( default_workteam["UserPool"], default_workteam["ClientId"], default_workteam["UserGroup"], ) def list_labeling_jobs_for_workteam(client, workteam_arn): return client.list_labeling_jobs_for_workteam(WorkteamArn=workteam_arn) def describe_labeling_job(client, labeling_job_name): return client.describe_labeling_job(LabelingJobName=labeling_job_name) def get_workteam_arn(client, workteam_name): response = describe_workteam(client, workteam_name) return response["Workteam"]["WorkteamArn"] def delete_workteam(client, workteam_name): client.delete_workteam(WorkteamName=workteam_name) def stop_labeling_job(client, labeling_job_name): client.stop_labeling_job(LabelingJobName=labeling_job_name) def describe_processing_job(client, processing_job_name): return client.describe_processing_job(ProcessingJobName=processing_job_name)