def export_model(self, param):
param_pb = nn_model_param_pb2.NNModelParam()
# save api_version
param_pb.api_version = param.api_version
# save pl model bytes
with tempfile.TemporaryDirectory() as d:
filepath = os.path.join(d, "model.ckpt")
self.pl_trainer.save_checkpoint(filepath)
with open(filepath, "rb") as f:
param_pb.saved_model_bytes = f.read()
# save header
param_pb.header.extend(self.header)
# save label mapping
if self.label_mapping is not None:
for label, mapped in self.label_mapping.items():
param_pb.label_mapping.add(label=json.dumps(label),
mapped=json.dumps(mapped))
# meta
meta_pb = nn_model_meta_pb2.NNModelMeta()
meta_pb.params.CopyFrom(param.generate_pb())
meta_pb.aggregate_iter = self.context.aggregation_iteration
return {
_consts.MODEL_META_NAME: meta_pb,
_consts.MODEL_PARAM_NAME: param_pb
}
def _get_param(self):
from federatedml.protobuf.generated import nn_model_param_pb2
param_pb = nn_model_param_pb2.NNModelParam()
param_pb.saved_model_bytes = self.nn_model.export_model()
param_pb.header.extend(self._header)
for label, mapped in self._label_align_mapping.items():
param_pb.label_mapping.add(label=json.dumps(label), mapped=json.dumps(mapped))
return param_pb
def export_model(self, param):
param_pb = nn_model_param_pb2.NNModelParam()
# save api_version
param_pb.api_version = param.api_version
meta_pb = nn_model_meta_pb2.NNModelMeta()
meta_pb.params.CopyFrom(param.generate_pb())
meta_pb.aggregate_iter = self.context.aggregation_iteration
return {
_consts.MODEL_META_NAME: meta_pb,
_consts.MODEL_PARAM_NAME: param_pb
}
def _get_param(self):
from federatedml.protobuf.generated import nn_model_param_pb2
param_pb = nn_model_param_pb2.NNModelParam()
param_pb.saved_model_bytes = self.nn_model.export_model()
return param_pb
def arbiter_get_param(self):
from federatedml.protobuf.generated import nn_model_param_pb2
param_pb = nn_model_param_pb2.NNModelParam()
return param_pb
