提交 baaf9d8b 编写于 作者: G guru4elephant

refine imagenet benchmark profiling

上级 9795e29e
# 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.
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
args = benchmark_args()
def single_func(idx, resource):
if args.request == "rpc":
reader = ImageReader()
fetch = ["score"]
client = Client()
client.load_client_config(args.model)
client.connect([resource["endpoint"][idx % 4]])
start = time.time()
for i in range(1000):
with open("./data/n01440764_10026.JPEG") as f:
img = f.read()
img = reader.process_image(img).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 = []
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})
print(result)
......@@ -19,7 +19,7 @@ import time
client = Client()
client.load_client_config(sys.argv[1])
client.connect(["127.0.0.1:9292"])
client.connect(["127.0.0.1:9295"])
reader = ImageReader()
start = time.time()
......
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