fix bad code style in other .py files by yapf

python/paddle_serving_server/__init__.py

@@ -54,8 +54,8 @@ class OpMaker(object):
 
     def create(self, node_type, engine_name=None, inputs=[], outputs=[]):
         if node_type not in self.op_dict:
-            raise Exception(
-                "Op type {} is not supported right now".format(node_type))
+            raise Exception("Op type {} is not supported right now".format(
+                node_type))
         node = server_sdk.DAGNode()
         # node.name will be used as the infer engine name
         if engine_name:
@@ -104,8 +104,8 @@ class OpSeqMaker(object):
                 if node.dependencies[0].name != self.workflow.nodes[-1].name:
                     raise Exception(
                         'You must add op in order in OpSeqMaker. The previous op is {}, but the current op is followed by {}.'
-                        .format(node.dependencies[0].name,
-                                self.workflow.nodes[-1].name))
+                        .format(node.dependencies[0].name, self.workflow.nodes[
+                            -1].name))
         self.workflow.nodes.extend([node])
 
     def get_op_sequence(self):
@@ -308,8 +308,8 @@ class Server(object):
                 self.model_config_paths[node.name] = path
             print("You have specified multiple model paths, please ensure "
                   "that the input and output of multiple models are the same.")
-            workflow_oi_config_path = list(
-                self.model_config_paths.items())[0][1]
+            workflow_oi_config_path = list(self.model_config_paths.items())[0][
+                1]
         else:
             raise Exception("The type of model_config_paths must be str or "
                             "dict({op: model_path}), not {}.".format(
@@ -569,20 +569,20 @@ class MultiLangServerServiceServicer(multi_lang_general_model_service_pb2_grpc.
                     tensor.data = model_result[name].tobytes()
                 else:
                     if v_type == 0:  # int64
-                        tensor.int64_data.extend(
-                            model_result[name].reshape(-1).tolist())
+                        tensor.int64_data.extend(model_result[name].reshape(-1)
+                                                 .tolist())
                     elif v_type == 1:  # float32
-                        tensor.float_data.extend(
-                            model_result[name].reshape(-1).tolist())
+                        tensor.float_data.extend(model_result[name].reshape(-1)
+                                                 .tolist())
                     elif v_type == 2:  # int32
-                        tensor.int_data.extend(
-                            model_result[name].reshape(-1).tolist())
+                        tensor.int_data.extend(model_result[name].reshape(-1)
+                                               .tolist())
                     else:
                         raise Exception("error type.")
                 tensor.shape.extend(list(model_result[name].shape))
                 if name in self.lod_tensor_set_:
-                    tensor.lod.extend(
-                        model_result["{}.lod".format(name)].tolist())
+                    tensor.lod.extend(model_result["{}.lod".format(name)]
+                                      .tolist())
                 inst.tensor_array.append(tensor)
             model_output.insts.append(inst)
             model_output.engine_name = model_name
@@ -601,7 +601,8 @@ class MultiLangServerServiceServicer(multi_lang_general_model_service_pb2_grpc.
     def Inference(self, request, context):
         feed_dict, fetch_names, is_python, log_id = \
                 self._unpack_inference_request(request)
-        ret = self.bclient_.predict(feed=feed_dict,
+        ret = self.bclient_.predict(
+            feed=feed_dict,
             fetch=fetch_names,
             need_variant_tag=True,
             log_id=log_id)
@@ -684,11 +685,12 @@ class MultiLangServer(object):
         default_port = 12000
         self.port_list_ = []
         for i in range(1000):
-            if default_port + i != port and self._port_is_available(
-                    default_port + i):
+            if default_port + i != port and self._port_is_available(default_port
+                                                                    + i):
                 self.port_list_.append(default_port + i)
                 break
-        self.bserver_.prepare_server(workdir=workdir,
+        self.bserver_.prepare_server(
+            workdir=workdir,
             port=self.port_list_[0],
             device=device,
             cube_conf=cube_conf)
@@ -704,8 +706,8 @@ class MultiLangServer(object):
         return result != 0
 
     def run_server(self):
-        p_bserver = Process(target=self._launch_brpc_service,
-                            args=(self.bserver_, ))
+        p_bserver = Process(
+            target=self._launch_brpc_service, args=(self.bserver_, ))
         p_bserver.start()
         options = [('grpc.max_send_message_length', self.body_size_),
                    ('grpc.max_receive_message_length', self.body_size_)]

python/paddle_serving_server_gpu/__init__.py

@@ -40,52 +40,46 @@ from concurrent import futures
 
 def serve_args():
     parser = argparse.ArgumentParser("serve")
-    parser.add_argument("--thread",
-                        type=int,
-                        default=2,
-                        help="Concurrency of server")
-    parser.add_argument("--model",
-                        type=str,
-                        default="",
-                        help="Model for serving")
-    parser.add_argument("--port",
-                        type=int,
-                        default=9292,
-                        help="Port of the starting gpu")
-    parser.add_argument("--workdir",
+    parser.add_argument(
+        "--thread", type=int, default=2, help="Concurrency of server")
+    parser.add_argument(
+        "--model", type=str, default="", help="Model for serving")
+    parser.add_argument(
+        "--port", type=int, default=9292, help="Port of the starting gpu")
+    parser.add_argument(
+        "--workdir",
         type=str,
         default="workdir",
         help="Working dir of current service")
-    parser.add_argument("--device",
-                        type=str,
-                        default="gpu",
-                        help="Type of device")
+    parser.add_argument(
+        "--device", type=str, default="gpu", help="Type of device")
     parser.add_argument("--gpu_ids", type=str, default="", help="gpu ids")
-    parser.add_argument("--name",
-                        type=str,
-                        default="None",
-                        help="Default service name")
-    parser.add_argument("--mem_optim_off",
+    parser.add_argument(
+        "--name", type=str, default="None", help="Default service name")
+    parser.add_argument(
+        "--mem_optim_off",
         default=False,
         action="store_true",
         help="Memory optimize")
-    parser.add_argument("--ir_optim",
-                        default=False,
-                        action="store_true",
-                        help="Graph optimize")
-    parser.add_argument("--max_body_size",
+    parser.add_argument(
+        "--ir_optim", default=False, action="store_true", help="Graph optimize")
+    parser.add_argument(
+        "--max_body_size",
         type=int,
         default=512 * 1024 * 1024,
         help="Limit sizes of messages")
-    parser.add_argument("--use_multilang",
+    parser.add_argument(
+        "--use_multilang",
         default=False,
         action="store_true",
         help="Use Multi-language-service")
-    parser.add_argument("--product_name",
+    parser.add_argument(
+        "--product_name",
         type=str,
         default=None,
         help="product_name for authentication")
-    parser.add_argument("--container_id",
+    parser.add_argument(
+        "--container_id",
         type=str,
         default=None,
         help="container_id for authentication")
@@ -108,8 +102,8 @@ class OpMaker(object):
 
     def create(self, node_type, engine_name=None, inputs=[], outputs=[]):
         if node_type not in self.op_dict:
-            raise Exception(
-                "Op type {} is not supported right now".format(node_type))
+            raise Exception("Op type {} is not supported right now".format(
+                node_type))
         node = server_sdk.DAGNode()
         # node.name will be used as the infer engine name
         if engine_name:
@@ -158,8 +152,8 @@ class OpSeqMaker(object):
                 if node.dependencies[0].name != self.workflow.nodes[-1].name:
                     raise Exception(
                         'You must add op in order in OpSeqMaker. The previous op is {}, but the current op is followed by {}.'
-                        .format(node.dependencies[0].name,
-                                self.workflow.nodes[-1].name))
+                        .format(node.dependencies[0].name, self.workflow.nodes[
+                            -1].name))
         self.workflow.nodes.extend([node])
 
     def get_op_sequence(self):
@@ -372,8 +366,8 @@ class Server(object):
                 self.model_config_paths[node.name] = path
             print("You have specified multiple model paths, please ensure "
                   "that the input and output of multiple models are the same.")
-            workflow_oi_config_path = list(
-                self.model_config_paths.items())[0][1]
+            workflow_oi_config_path = list(self.model_config_paths.items())[0][
+                1]
         else:
             raise Exception("The type of model_config_paths must be str or "
                             "dict({op: model_path}), not {}.".format(
@@ -636,20 +630,20 @@ class MultiLangServerServiceServicer(multi_lang_general_model_service_pb2_grpc.
                     tensor.data = model_result[name].tobytes()
                 else:
                     if v_type == 0:  # int64
-                        tensor.int64_data.extend(
-                            model_result[name].reshape(-1).tolist())
+                        tensor.int64_data.extend(model_result[name].reshape(-1)
+                                                 .tolist())
                     elif v_type == 1:  # float32
-                        tensor.float_data.extend(
-                            model_result[name].reshape(-1).tolist())
+                        tensor.float_data.extend(model_result[name].reshape(-1)
+                                                 .tolist())
                     elif v_type == 2:  # int32
-                        tensor.int_data.extend(
-                            model_result[name].reshape(-1).tolist())
+                        tensor.int_data.extend(model_result[name].reshape(-1)
+                                               .tolist())
                     else:
                         raise Exception("error type.")
                 tensor.shape.extend(list(model_result[name].shape))
                 if name in self.lod_tensor_set_:
-                    tensor.lod.extend(
-                        model_result["{}.lod".format(name)].tolist())
+                    tensor.lod.extend(model_result["{}.lod".format(name)]
+                                      .tolist())
                 inst.tensor_array.append(tensor)
             model_output.insts.append(inst)
             model_output.engine_name = model_name
@@ -668,7 +662,8 @@ class MultiLangServerServiceServicer(multi_lang_general_model_service_pb2_grpc.
     def Inference(self, request, context):
         feed_dict, fetch_names, is_python, log_id \
                 = self._unpack_inference_request(request)
-        ret = self.bclient_.predict(feed=feed_dict,
+        ret = self.bclient_.predict(
+            feed=feed_dict,
             fetch=fetch_names,
             need_variant_tag=True,
             log_id=log_id)
@@ -748,11 +743,12 @@ class MultiLangServer(object):
         default_port = 12000
         self.port_list_ = []
         for i in range(1000):
-            if default_port + i != port and self._port_is_available(
-                    default_port + i):
+            if default_port + i != port and self._port_is_available(default_port
+                                                                    + i):
                 self.port_list_.append(default_port + i)
                 break
-        self.bserver_.prepare_server(workdir=workdir,
+        self.bserver_.prepare_server(
+            workdir=workdir,
             port=self.port_list_[0],
             device=device,
             cube_conf=cube_conf)
@@ -768,8 +764,8 @@ class MultiLangServer(object):
         return result != 0
 
     def run_server(self):
-        p_bserver = Process(target=self._launch_brpc_service,
-                            args=(self.bserver_, ))
+        p_bserver = Process(
+            target=self._launch_brpc_service, args=(self.bserver_, ))
         p_bserver.start()
         options = [('grpc.max_send_message_length', self.body_size_),
                    ('grpc.max_receive_message_length', self.body_size_)]

python/paddle_serving_server_gpu/serve.py

@@ -99,11 +99,11 @@ def start_multi_card(args):  # pylint: disable=doc-string-missing
     else:
         gpu_processes = []
         for i, gpu_id in enumerate(gpus):
-            p = Process(target=start_gpu_card_model, args=(
+            p = Process(
+                target=start_gpu_card_model, args=(
                     i,
                     gpu_id,
-                args,
-            ))
+                    args, ))
             gpu_processes.append(p)
         for p in gpu_processes:
             p.start()
@@ -125,9 +125,8 @@ if __name__ == "__main__":
                 gpu_ids = os.environ["CUDA_VISIBLE_DEVICES"]
         if len(gpu_ids) > 0:
             web_service.set_gpus(gpu_ids)
-        web_service.prepare_server(workdir=args.workdir,
-                                   port=args.port,
-                                   device=args.device)
+        web_service.prepare_server(
+            workdir=args.workdir, port=args.port, device=args.device)
         web_service.run_rpc_service()
 
         app_instance = Flask(__name__)