# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # pylint: disable=doc-string-missing import sys from image_reader import ImageReader from paddle_serving_client import Client from paddle_serving_client.utils import MultiThreadRunner from paddle_serving_client.utils import benchmark_args import time import os args = benchmark_args() def single_func(idx, resource): file_list = [] for file_name in os.listdir("./image_data/n01440764"): file_list.append(file_name) img_list = [] for i in range(1000): img_list.append(open("./image_data/n01440764/" + file_list[i]).read()) if args.request == "rpc": reader = ImageReader() fetch = ["score"] client = Client() client.load_client_config(args.model) client.connect([resource["endpoint"][idx % len(resource["endpoint"])]]) start = time.time() for i in range(1000): img = reader.process_image(img_list[i]).reshape(-1) fetch_map = client.predict(feed={"image": img}, fetch=["score"]) end = time.time() return [[end - start]] return [[end - start]] if __name__ == "__main__": multi_thread_runner = MultiThreadRunner() endpoint_list = ["127.0.0.1:9393"] #card_num = 4 #for i in range(args.thread): # endpoint_list.append("127.0.0.1:{}".format(9295 + i % card_num)) result = multi_thread_runner.run(single_func, args.thread, {"endpoint": endpoint_list}) avg_cost = 0 for i in range(args.thread): avg_cost += result[0][i] avg_cost = avg_cost / args.thread print("average total cost {} s.".format(avg_cost))