From 9b9d83761d0324430f496b44a9feb054aa4cfa08 Mon Sep 17 00:00:00 2001 From: TeslaZhao Date: Thu, 20 Aug 2020 17:24:22 +0800 Subject: [PATCH] fix bad code style in other .py files by yapf --- python/paddle_serving_server/__init__.py | 54 +++---- python/paddle_serving_server_gpu/__init__.py | 144 +++++++++---------- python/paddle_serving_server_gpu/serve.py | 15 +- 3 files changed, 105 insertions(+), 108 deletions(-) diff --git a/python/paddle_serving_server/__init__.py b/python/paddle_serving_server/__init__.py index a73fcdf0..675dcb13 100644 --- a/python/paddle_serving_server/__init__.py +++ b/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 @@ -601,10 +601,11 @@ 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, - fetch=fetch_names, - need_variant_tag=True, - log_id=log_id) + ret = self.bclient_.predict( + feed=feed_dict, + fetch=fetch_names, + need_variant_tag=True, + log_id=log_id) return self._pack_inference_response(ret, fetch_names, is_python) def GetClientConfig(self, request, context): @@ -684,14 +685,15 @@ 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, - port=self.port_list_[0], - device=device, - cube_conf=cube_conf) + self.bserver_.prepare_server( + workdir=workdir, + port=self.port_list_[0], + device=device, + cube_conf=cube_conf) self.set_port(port) def _launch_brpc_service(self, bserver): @@ -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_)] diff --git a/python/paddle_serving_server_gpu/__init__.py b/python/paddle_serving_server_gpu/__init__.py index 99ad8dc9..7a5c2688 100644 --- a/python/paddle_serving_server_gpu/__init__.py +++ b/python/paddle_serving_server_gpu/__init__.py @@ -40,55 +40,49 @@ 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", - 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( + "--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("--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", - 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", - type=int, - default=512 * 1024 * 1024, - help="Limit sizes of messages") - parser.add_argument("--use_multilang", - default=False, - action="store_true", - help="Use Multi-language-service") - parser.add_argument("--product_name", - type=str, - default=None, - help="product_name for authentication") - parser.add_argument("--container_id", - type=str, - default=None, - help="container_id for authentication") + 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", + type=int, + default=512 * 1024 * 1024, + help="Limit sizes of messages") + parser.add_argument( + "--use_multilang", + default=False, + action="store_true", + help="Use Multi-language-service") + parser.add_argument( + "--product_name", + type=str, + default=None, + help="product_name for authentication") + parser.add_argument( + "--container_id", + type=str, + default=None, + help="container_id for authentication") return parser.parse_args() @@ -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 @@ -668,10 +662,11 @@ 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, - fetch=fetch_names, - need_variant_tag=True, - log_id=log_id) + ret = self.bclient_.predict( + feed=feed_dict, + fetch=fetch_names, + need_variant_tag=True, + log_id=log_id) return self._pack_inference_response(ret, fetch_names, is_python) def GetClientConfig(self, request, context): @@ -748,14 +743,15 @@ 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, - port=self.port_list_[0], - device=device, - cube_conf=cube_conf) + self.bserver_.prepare_server( + workdir=workdir, + port=self.port_list_[0], + device=device, + cube_conf=cube_conf) self.set_port(port) def _launch_brpc_service(self, bserver): @@ -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_)] diff --git a/python/paddle_serving_server_gpu/serve.py b/python/paddle_serving_server_gpu/serve.py index 79d191f7..9755b188 100644 --- a/python/paddle_serving_server_gpu/serve.py +++ b/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=( - i, - gpu_id, - args, - )) + p = Process( + target=start_gpu_card_model, args=( + i, + gpu_id, + 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__) -- GitLab