def update_deployed_model(ws, aci_service_name, model_name, mlapp_env, entry_script): inference_config = InferenceConfig(source_directory=os.getcwd(), entry_script=entry_script, environment=mlapp_env) model = Model(ws, name=model_name) service = Webservice(name=aci_service_name, workspace=ws) service.update(models=[model], inference_config=inference_config) print(service.state) print(service.get_logs())
from azureml.core import Workspace from azureml.core import Webservice ws = Workspace.from_config() service = Webservice(ws, 'lpr') scoring_uri = service.scoring_ui primary, secondary = service.get_keys() print(primary) print(service.get_logs())