Created by: imistyrain

paddlepaddle-gpu 1.2 ,训练用的卡为P40，单卡测 所用代码，已去除读取模块，由np生成的随机数直接灌入数据.

#coding=utf-8
import paddle.fluid as fluid
import numpy as np
import models
import time
import paddle.fluid.profiler as profiler

def test_speed():
    image = fluid.layers.data(name="image", shape=[3, 224, 224])
    #label = fluid.layers.data(name="label", shape=[1], dtype="int64")
    model=models.__dict__["AlexNet"]()
    predict=model.net(image)
    #place = fluid.CPUPlace()
    place=fluid.CUDAPlace(0) 
    exe = fluid.Executor(place)
    exe.run(fluid.default_startup_program())
    profiler.start_profiler('GPU')
    index=0
    while True:
        t1 = time.time()
        results=exe.run(feed={"image":np.random.random(size=(32, 3, 224, 224)).astype('float32')},
        fetch_list=[predict])
        t2=time.time()
        print("time:",t2-t1)
        if index==2:
            profiler.reset_profiler()
        if index>=4:
            profiler.stop_profiler('total', 'profile')
        index+=1
if __name__=="__main__":
    test_speed()

profile出来，GPU大段时间空闲，CPU中有80%的时间不知在干啥.