def delete_deployment(self, name):
"""
Delete the deployment with name ``name``.
:param name: Name of deployment to delete
:return: None
"""
try:
service = Webservice(self.workspace, name)
service.delete()
except WebserviceException as e:
if 'WebserviceNotFound' not in e.message:
_logger.info(
'Deployment with name {} not found, no service to delete'.
format(name))
return
raise MlflowException(
'There was an error deleting the deployment: \n{}'.format(
e.message)) from e
def deploy_model(ws, aci_service_name, experiment_name, asset_name,
asset_label, run_id, cpu_cores, memory_gb, entry_script):
env = create_env_from_requirements(endpoint=True)
inference_config = InferenceConfig(source_directory=os.getcwd(),
entry_script=entry_script,
environment=env)
deployment_config = AciWebservice.deploy_configuration(cpu_cores=cpu_cores,
memory_gb=memory_gb)
# model name
model_name = get_model_register_name(run_id)
try:
model = Model(ws, name=model_name)
except:
# creating directory for download Model files for Model register
tmp_path = create_tempdir(name='download_tmp')
register_path = create_directory(AML_MLAPP_FOLDER, path=tmp_path)
# getting RUN context
experiment = Experiment(workspace=ws, name=experiment_name)
tags = {"run_id": run_id, "asset_name": asset_name}
if asset_label is not None:
tags["asset_label"] = asset_label
selected_run_id = None
for run in Run.list(experiment,
tags=tags,
include_children=True,
status='Completed'):
run_metrics = run.get_metrics()
exp_saved_run_id = run_metrics.get("run_id")
if exp_saved_run_id == run_id:
selected_run_id = run.id
break
if selected_run_id is None:
raise Exception(
'ERROR: there is no matching Run object that associated with the run id %s in this experiment.'
% str(run_id))
current_run = Run(experiment=experiment, run_id=selected_run_id)
# download files from run object
current_run.download_files(output_directory=register_path)
# register model
model = Model.register(ws,
model_path=register_path,
model_name=model_name,
tags=tags,
description=asset_name)
# deletes tmp dir and all content
delete_directory_with_all_contents(tmp_path)
# deploy model
service = None
try:
service = Webservice(ws, name=aci_service_name)
service.update(models=[model], inference_config=inference_config)
except WebserviceException as e:
if service:
service.delete()
service = Model.deploy(ws, aci_service_name, [model], inference_config,
deployment_config)
service.wait_for_deployment(True)
)
args = parser.parse_args()
run = Run.get_context()
ws = run.experiment.workspace
freezer_environment = ws.environments["sktime_freezer_environment"]
try:
service = Webservice(ws, args.webservicename)
except WebserviceException:
service = None
if args.redeploy:
if service is not None:
service.delete()
print("deleted existing Webservice.")
model = Model(ws, "sktime_freezer_classifier")
inference_config = InferenceConfig(
entry_script="score.py", source_directory="./", environment=freezer_environment
)
aci_config = AciWebservice.deploy_configuration(cpu_cores=1, memory_gb=1)
service = Model.deploy(
workspace=ws,
name=args.webservicename,
models=[model],
inference_config=inference_config,
