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())
