def get_predict_dsl():
request_data = request.json
request_data['query_filters'] = ['inference_dsl']
retcode, retmsg, data = model_utils.query_model_info_from_file(
**request_data)
if data:
for d in data:
if d.get("f_role") in {"guest", "host"}:
_data = d
break
else:
return error_response(
210,
"can not found guest or host model, please get predict dsl on guest or host."
)
if request_data.get("filename"):
os.makedirs(TEMP_DIRECTORY, exist_ok=True)
temp_filepath = os.path.join(TEMP_DIRECTORY,
request_data.get("filename"))
with open(temp_filepath, "w") as fout:
fout.write(json_dumps(_data['f_inference_dsl'], indent=4))
return send_file(open(temp_filepath, "rb"),
as_attachment=True,
attachment_filename=request_data.get("filename"))
else:
return get_json_result(data=_data['f_inference_dsl'])
return error_response(
210,
"No model found, please check if arguments are specified correctly.")
def deploy():
request_data = request.json
require_parameters = ['model_id', 'model_version']
check_config(request_data, require_parameters)
model_id = request_data.get("model_id")
model_version = request_data.get("model_version")
retcode, retmsg, model_info = model_utils.query_model_info_from_file(
model_id=model_id, model_version=model_version, to_dict=True)
if not model_info:
raise Exception(
f'Deploy model failed, no model {model_id} {model_version} found.')
else:
for key, value in model_info.items():
version_check = model_utils.compare_version(
value.get('f_fate_version'), '1.5.0')
if version_check == 'lt':
continue
else:
init_role = key.split('/')[-2].split('#')[0]
init_party_id = key.split('/')[-2].split('#')[1]
model_init_role = value.get('f_initiator_role') if value.get(
'f_initiator_role') else value.get(
'f_train_runtime_conf', {}).get('initiator', {}).get(
'role', '')
model_init_party_id = value.get(
'f_initiator_role_party_id') if value.get(
'f_initiator_role_party_id') else value.get(
'f_train_runtime_conf', {}).get(
'initiator', {}).get('party_id', '')
if (init_role
== model_init_role) and (init_party_id
== str(model_init_party_id)):
break
else:
raise Exception(
"Deploy model failed, can not found model of initiator role or the fate version of model is older than 1.5.0"
)
# distribute federated deploy task
_job_id = job_utils.generate_job_id()
request_data['child_model_version'] = _job_id
initiator_party_id = model_init_party_id
initiator_role = model_init_role
request_data['initiator'] = {
'role': initiator_role,
'party_id': initiator_party_id
}
deploy_status = True
deploy_status_info = {}
deploy_status_msg = 'success'
deploy_status_info['detail'] = {}
for role_name, role_partys in value.get("f_train_runtime_conf",
{}).get('role', {}).items():
if role_name not in ['arbiter', 'host', 'guest']:
continue
deploy_status_info[role_name] = deploy_status_info.get(
role_name, {})
deploy_status_info['detail'][role_name] = {}
adapter = JobRuntimeConfigAdapter(
value.get("f_train_runtime_conf", {}))
work_mode = adapter.get_job_work_mode()
for _party_id in role_partys:
request_data['local'] = {
'role': role_name,
'party_id': _party_id
}
try:
response = federated_api(
job_id=_job_id,
method='POST',
endpoint='/model/deploy/do',
src_party_id=initiator_party_id,
dest_party_id=_party_id,
src_role=initiator_role,
json_body=request_data,
federated_mode=FederatedMode.MULTIPLE
if work_mode else FederatedMode.SINGLE)
deploy_status_info[role_name][_party_id] = response[
'retcode']
detail = {_party_id: {}}
detail[_party_id]['retcode'] = response['retcode']
detail[_party_id]['retmsg'] = response['retmsg']
deploy_status_info['detail'][role_name].update(detail)
if response['retcode']:
deploy_status = False
deploy_status_msg = 'failed'
except Exception as e:
stat_logger.exception(e)
deploy_status = False
deploy_status_msg = 'failed'
deploy_status_info[role_name][_party_id] = 100
deploy_status_info['model_id'] = request_data['model_id']
deploy_status_info['model_version'] = _job_id
return get_json_result(retcode=(0 if deploy_status else 101),
retmsg=deploy_status_msg,
data=deploy_status_info)