提交 d198eb35 编写于 作者: M MRXLT 提交者: GitHub

Merge pull request #709 from MRXLT/ce-script

fix cube demo
...@@ -29,6 +29,7 @@ args = benchmark_args() ...@@ -29,6 +29,7 @@ args = benchmark_args()
def single_func(idx, resource): def single_func(idx, resource):
client = Client() client = Client()
print([resource["endpoint"][idx % len(resource["endpoint"])]])
client.load_client_config('ctr_client_conf/serving_client_conf.prototxt') client.load_client_config('ctr_client_conf/serving_client_conf.prototxt')
client.connect(['127.0.0.1:9292']) client.connect(['127.0.0.1:9292'])
batch = 1 batch = 1
...@@ -40,27 +41,29 @@ def single_func(idx, resource): ...@@ -40,27 +41,29 @@ def single_func(idx, resource):
] ]
reader = dataset.infer_reader(test_filelists[len(test_filelists) - 40:], reader = dataset.infer_reader(test_filelists[len(test_filelists) - 40:],
batch, buf_size) batch, buf_size)
args.batch_size = 1
if args.request == "rpc": if args.request == "rpc":
fetch = ["prob"] fetch = ["prob"]
print("Start Time")
start = time.time() start = time.time()
itr = 1000 itr = 1000
for ei in range(itr): for ei in range(itr):
if args.batch_size == 1: if args.batch_size > 0:
data = reader().next() feed_batch = []
feed_dict = {} for bi in range(args.batch_size):
feed_dict['dense_input'] = data[0][0] data = reader().next()
for i in range(1, 27): feed_dict = {}
feed_dict["embedding_{}.tmp_0".format(i - 1)] = data[0][i] feed_dict['dense_input'] = data[0][0]
result = client.predict(feed=feed_dict, fetch=fetch) for i in range(1, 27):
feed_dict["embedding_{}.tmp_0".format(i - 1)] = data[0][
i]
feed_batch.append(feed_dict)
result = client.predict(feed=feed_batch, fetch=fetch)
else: else:
print("unsupport batch size {}".format(args.batch_size)) print("unsupport batch size {}".format(args.batch_size))
elif args.request == "http": elif args.request == "http":
raise ("Not support http service.") raise ("Not support http service.")
end = time.time() end = time.time()
qps = itr / (end - start) qps = itr * args.batch_size / (end - start)
return [[end - start, qps]] return [[end - start, qps]]
...@@ -70,6 +73,7 @@ if __name__ == '__main__': ...@@ -70,6 +73,7 @@ if __name__ == '__main__':
#result = single_func(0, {"endpoint": endpoint_list}) #result = single_func(0, {"endpoint": endpoint_list})
result = multi_thread_runner.run(single_func, args.thread, result = multi_thread_runner.run(single_func, args.thread,
{"endpoint": endpoint_list}) {"endpoint": endpoint_list})
print(result)
avg_cost = 0 avg_cost = 0
qps = 0 qps = 0
for i in range(args.thread): for i in range(args.thread):
......
rm profile_log rm profile_log
batch_size=1 export FLAGS_profile_client=1
export FLAGS_profile_server=1
for thread_num in 1 2 4 8 16 for thread_num in 1 2 4 8 16
do do
$PYTHONROOT/bin/python benchmark.py --thread $thread_num --model ctr_client_conf/serving_client_conf.prototxt --request rpc > profile 2>&1 for batch_size in 1 4 16 64 256
do
$PYTHONROOT/bin/python benchmark.py --thread $thread_num --batch_size $batch_size --model serving_client_conf/serving_client_conf.prototxt --request rpc > profile 2>&1
echo "batch size : $batch_size"
echo "thread num : $thread_num"
echo "========================================" echo "========================================"
echo "batch size : $batch_size" >> profile_log echo "batch size : $batch_size" >> profile_log
$PYTHONROOT/bin/python ../util/show_profile.py profile $thread_num >> profile_log $PYTHONROOT/bin/python ../util/show_profile.py profile $thread_num >> profile_log
tail -n 2 profile >> profile_log tail -n 2 profile >> profile_log
done done
done
# -*- coding: utf-8 -*-
#
# 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
from paddle_serving_client import Client
import sys
import os
import criteo as criteo
import time
from paddle_serving_client.utils import MultiThreadRunner
from paddle_serving_client.utils import benchmark_args
from paddle_serving_client.metric import auc
args = benchmark_args()
def single_func(idx, resource):
client = Client()
print([resource["endpoint"][idx % len(resource["endpoint"])]])
client.load_client_config('ctr_client_conf/serving_client_conf.prototxt')
client.connect(['127.0.0.1:9292'])
batch = 1
buf_size = 100
dataset = criteo.CriteoDataset()
dataset.setup(1000001)
test_filelists = [
"./raw_data/part-%d" % x for x in range(len(os.listdir("./raw_data")))
]
reader = dataset.infer_reader(test_filelists[len(test_filelists) - 40:],
batch, buf_size)
if args.request == "rpc":
fetch = ["prob"]
start = time.time()
itr = 1000
for ei in range(itr):
if args.batch_size > 1:
feed_batch = []
for bi in range(args.batch_size):
data = reader().next()
feed_dict = {}
feed_dict['dense_input'] = data[0][0]
for i in range(1, 27):
feed_dict["embedding_{}.tmp_0".format(i - 1)] = data[0][
i]
feed_batch.append(feed_dict)
result = client.predict(feed=feed_batch, fetch=fetch)
else:
print("unsupport batch size {}".format(args.batch_size))
elif args.request == "http":
raise ("Not support http service.")
end = time.time()
qps = itr * args.batch_size / (end - start)
return [[end - start, qps]]
if __name__ == '__main__':
multi_thread_runner = MultiThreadRunner()
endpoint_list = ["127.0.0.1:9292"]
#result = single_func(0, {"endpoint": endpoint_list})
result = multi_thread_runner.run(single_func, args.thread,
{"endpoint": endpoint_list})
print(result)
avg_cost = 0
qps = 0
for i in range(args.thread):
avg_cost += result[0][i * 2 + 0]
qps += result[0][i * 2 + 1]
avg_cost = avg_cost / args.thread
print("average total cost {} s.".format(avg_cost))
print("qps {} ins/s".format(qps))
rm profile_log
for thread_num in 1 2 4 8 16
do
for batch_size in 1 2 4 8 16 32 64 128 256 512
do
$PYTHONROOT/bin/python benchmark_batch.py --thread $thread_num --batch_size $batch_size --model serving_client_conf/serving_client_conf.prototxt --request rpc > profile 2>&1
echo "========================================"
echo "batch size : $batch_size" >> profile_log
$PYTHONROOT/bin/python ../util/show_profile.py profile $thread_num >> profile_log
tail -n 2 profile >> profile_log
done
done
...@@ -16,7 +16,5 @@ ...@@ -16,7 +16,5 @@
mkdir -p cube_model mkdir -p cube_model
mkdir -p cube/data mkdir -p cube/data
./seq_generator ctr_serving_model/SparseFeatFactors ./cube_model/feature
./cube/cube-builder -dict_name=test_dict -job_mode=base -last_version=0 -cur_version=0 -depend_version=0 -input_path=./cube_model -output_path=${PWD}/cube/data -shard_num=1 -only_build=false ./cube/cube-builder -dict_name=test_dict -job_mode=base -last_version=0 -cur_version=0 -depend_version=0 -input_path=./cube_model -output_path=${PWD}/cube/data -shard_num=1 -only_build=false
mv ./cube/data/0_0/test_dict_part0/* ./cube/data/ cd cube && ./cube
cd cube && ./cube
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