PPML FL change clientID from String to Int

python/ppml/example/fgboost_regression/fgboost_regression_party_1.py

@@ -82,7 +82,7 @@ def FillNaWithMean(data, columnList):
 @click.command()
 @click.option('--load_model', default=False)
 def run_client(load_model):
-    client_id = '1'
+    client_id = 1
     init_fl_context(client_id)
 
     df_train = pd.read_csv('./python/ppml/example/fgboost_regression/data/house-prices-train-1.csv')

python/ppml/example/fgboost_regression/fgboost_regression_party_2.py

@@ -82,7 +82,7 @@ def FillNaWithMean(data, columnList):
 @click.command()
 @click.option('--load_model', default=False)
 def run_client(load_model):
-    client_id = '2'
+    client_id = 2
     init_fl_context(client_id)
 
     df_train = pd.read_csv('./python/ppml/example/fgboost_regression/data/house-prices-train-2.csv')

python/ppml/example/pytorch_nn_lr/pytorch_nn_lr_1.py

@@ -56,7 +56,7 @@ def forward(self, x: List[Tensor]):
 @click.option('--load_model', default=False)
 @click.option('--data_path', default="./data/diabetes-vfl-1.csv")
 def run_client(load_model, data_path):
-    init_fl_context('1')
+    init_fl_context(1)
     df_train = pd.read_csv(data_path)   
 
     df_train['ID'] = df_train['ID'].astype(str)

python/ppml/example/pytorch_nn_lr/pytorch_nn_lr_2.py

@@ -42,7 +42,7 @@ def forward(self, x):
 @click.option('--load_model', default=False)
 @click.option('--data_path', default="./data/diabetes-vfl-2.csv")
 def run_client(load_model, data_path):
-    init_fl_context('2')
+    init_fl_context(2)
     df_train = pd.read_csv(data_path)
     df_train['ID'] = df_train['ID'].astype(str)
     psi = PSI()

python/ppml/src/bigdl/ppml/fl/nn/fl_context.py

@@ -16,7 +16,7 @@
 
 from ..nn.fl_client import FLClient
 
-def init_fl_context(client_id, target="localhost:8980"):
+def init_fl_context(client_id: int, target="localhost:8980"):
     FLClient.load_config()
     FLClient.set_client_id(client_id)
     # target can be set in config file, and also could be overwritten here

python/ppml/src/bigdl/ppml/fl/nn/generated/fgboost_service_pb2_grpc.py

@@ -4,6 +4,7 @@
 
 import fgboost_service_pb2 as fgboost__service__pb2
 
+
 class FGBoostServiceStub(object):
     """Missing associated documentation comment in .proto file."""
 
@@ -48,6 +49,16 @@ def __init__(self, channel):
                 request_serializer=fgboost__service__pb2.PredictRequest.SerializeToString,
                 response_deserializer=fgboost__service__pb2.PredictResponse.FromString,
                 )
+        self.saveServerModel = channel.unary_unary(
+                '/fgboost.FGBoostService/saveServerModel',
+                request_serializer=fgboost__service__pb2.SaveModelRequest.SerializeToString,
+                response_deserializer=fgboost__service__pb2.SaveModelResponse.FromString,
+                )
+        self.loadServerModel = channel.unary_unary(
+                '/fgboost.FGBoostService/loadServerModel',
+                request_serializer=fgboost__service__pb2.LoadModelRequest.SerializeToString,
+                response_deserializer=fgboost__service__pb2.LoadModelResponse.FromString,
+                )
 
 
 class FGBoostServiceServicer(object):
@@ -95,6 +106,18 @@ def predict(self, request, context):
         context.set_details('Method not implemented!')
         raise NotImplementedError('Method not implemented!')
 
+    def saveServerModel(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def loadServerModel(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
 
 def add_FGBoostServiceServicer_to_server(servicer, server):
     rpc_method_handlers = {
@@ -133,6 +156,16 @@ def add_FGBoostServiceServicer_to_server(servicer, server):
                     request_deserializer=fgboost__service__pb2.PredictRequest.FromString,
                     response_serializer=fgboost__service__pb2.PredictResponse.SerializeToString,
             ),
+            'saveServerModel': grpc.unary_unary_rpc_method_handler(
+                    servicer.saveServerModel,
+                    request_deserializer=fgboost__service__pb2.SaveModelRequest.FromString,
+                    response_serializer=fgboost__service__pb2.SaveModelResponse.SerializeToString,
+            ),
+            'loadServerModel': grpc.unary_unary_rpc_method_handler(
+                    servicer.loadServerModel,
+                    request_deserializer=fgboost__service__pb2.LoadModelRequest.FromString,
+                    response_serializer=fgboost__service__pb2.LoadModelResponse.SerializeToString,
+            ),
     }
     generic_handler = grpc.method_handlers_generic_handler(
             'fgboost.FGBoostService', rpc_method_handlers)
@@ -261,3 +294,37 @@ def predict(request,
             fgboost__service__pb2.PredictResponse.FromString,
             options, channel_credentials,
             insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def saveServerModel(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/fgboost.FGBoostService/saveServerModel',
+            fgboost__service__pb2.SaveModelRequest.SerializeToString,
+            fgboost__service__pb2.SaveModelResponse.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def loadServerModel(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/fgboost.FGBoostService/loadServerModel',
+            fgboost__service__pb2.LoadModelRequest.SerializeToString,
+            fgboost__service__pb2.LoadModelResponse.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)