def do_load_model():
request_data = request.json
adapter_servings_config(request_data)
retcode, retmsg = publish_model.load_model(config_data=request_data)
try:
if not retcode:
with DB.connection_context():
model = MLModel.get_or_none(MLModel.f_role == request_data.get("local").get("role"),
MLModel.f_party_id == request_data.get("local").get("party_id"),
MLModel.f_model_id == request_data.get("job_parameters").get("model_id"),
MLModel.f_model_version == request_data.get("job_parameters").get("model_version"))
if model:
count = model.f_loaded_times
model.f_loaded_times = count + 1
model.save()
except Exception as modify_err:
stat_logger.exception(modify_err)
try:
party_model_id = gen_party_model_id(role=request_data.get("local").get("role"),
party_id=request_data.get("local").get("party_id"),
model_id=request_data.get("job_parameters").get("model_id"))
src_model_path = os.path.join(file_utils.get_project_base_directory(), 'model_local_cache', party_model_id,
request_data.get("job_parameters").get("model_version"))
dst_model_path = os.path.join(file_utils.get_project_base_directory(), 'loaded_model_backup',
party_model_id, request_data.get("job_parameters").get("model_version"))
if not os.path.exists(dst_model_path):
shutil.copytree(src=src_model_path, dst=dst_model_path)
except Exception as copy_err:
stat_logger.exception(copy_err)
operation_record(request_data, "load", "success" if not retcode else "failed")
return get_json_result(retcode=retcode, retmsg=retmsg)
def do_load_model():
request_data = request.json
request_data['servings'] = RuntimeConfig.SERVICE_DB.get_urls('servings')
role = request_data['local']['role']
party_id = request_data['local']['party_id']
model_id = request_data['job_parameters']['model_id']
model_version = request_data['job_parameters']['model_version']
party_model_id = model_utils.gen_party_model_id(model_id, role, party_id)
if get_base_config('enable_model_store', False):
pipeline_model = pipelined_model.PipelinedModel(
party_model_id, model_version)
component_parameters = {
'model_id': party_model_id,
'model_version': model_version,
'store_address': ServiceRegistry.MODEL_STORE_ADDRESS,
}
model_storage = get_model_storage(component_parameters)
if pipeline_model.exists() and not model_storage.exists(
**component_parameters):
stat_logger.info(
f'Uploading {pipeline_model.model_path} to model storage.')
model_storage.store(**component_parameters)
elif not pipeline_model.exists() and model_storage.exists(
**component_parameters):
stat_logger.info(
f'Downloading {pipeline_model.model_path} from model storage.')
model_storage.restore(**component_parameters)
if not model_utils.check_if_deployed(role, party_id, model_id,
model_version):
return get_json_result(
retcode=100,
retmsg=
"Only deployed models could be used to execute process of loading. "
"Please deploy model before loading.")
retcode, retmsg = publish_model.load_model(request_data)
try:
if not retcode:
with DB.connection_context():
model = MLModel.get_or_none(
MLModel.f_role == request_data["local"]["role"],
MLModel.f_party_id == request_data["local"]["party_id"],
MLModel.f_model_id == request_data["job_parameters"]
["model_id"], MLModel.f_model_version ==
request_data["job_parameters"]["model_version"])
if model:
model.f_loaded_times += 1
model.save()
except Exception as modify_err:
stat_logger.exception(modify_err)
operation_record(request_data, "load",
"success" if not retcode else "failed")
return get_json_result(retcode=retcode, retmsg=retmsg)