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  • 78、tensorflow滑动平均模型,用来更新迭代的衰减系数

    '''
    Created on 2017年4月21日
    
    @author: weizhen
    '''
    #4、滑动平均模型
    import tensorflow as tf
    #定义一个变量用于计算滑动平均,这个变量的初始值为0.
    #类型为tf.float32,因为所有需要计算滑动平均的变量必须是实数型
    v1=tf.Variable(0,dtype=tf.float32)
    #这里step变量模拟神经网络中迭代的轮数,可以用于动态控制衰减率
    step=tf.Variable(0,trainable=False)
    #定义一个滑动平均的类(class)。初始化时给定了衰减率(0.99)和控制衰减率的变量step
    ema=tf.train.ExponentialMovingAverage(0.99,step)
    #定义一个更新变量滑动平均的操作。这里需要给定一个列表,每次执行这个操作时
    #这个列表中的变量都会被更新
    maintain_averages_op=ema.apply([v1])
    with tf.Session() as sess:
        #初始化所有变量
        init_op=tf.global_variables_initializer()
        sess.run(init_op)
        
        #通过ema.average(v1)获取滑动平均之后变量的取值。在初始化之后变量v1的值和v1的滑动平均都为0
        print(sess.run([v1,ema.average(v1)]))   #输出[0.0,0.0]
        
        #更新变量v1的值到5
        sess.run(tf.assign(v1,5))
        #更新v1的滑动平均值。衰减率为min{0.99,(1+step)/(10+step)=0.1}=0.1
        #所以v1的滑动平均会被更新为0.1*0+0.9*5=4.5
        sess.run(maintain_averages_op)
        print(sess.run([v1,ema.average(v1)]))
        
        #更新step的值为10000
        sess.run(tf.assign(step,10000))
        #更新v1的值为10
        sess.run(tf.assign(v1,10))
        #更新v1的滑动平均值。衰减率为min{0.99,(1+step)/(10+step)=0.999}}=0.99
        #所以v1的滑动平均会被更新为0.99*4.5+0.01*10=4.555
        sess.run(maintain_averages_op)
        print(sess.run([v1,ema.average(v1)]))
        #输出[10.0,4.5549998]
        #再次更新滑动平均值,得到的新滑动平均值为0.99*4.555+0.01*10=4.60945
        sess.run(maintain_averages_op)
        print(sess.run([v1,ema.average(v1)]))
        #输出[10.0,4.6094499]

    输出的结果如下所示

    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "CountExtremelyRandomStats" device_type: "CPU"') for unknown op: CountExtremelyRandomStats
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "FinishedNodes" device_type: "CPU"') for unknown op: FinishedNodes
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "GrowTree" device_type: "CPU"') for unknown op: GrowTree
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "ReinterpretStringToFloat" device_type: "CPU"') for unknown op: ReinterpretStringToFloat
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "SampleInputs" device_type: "CPU"') for unknown op: SampleInputs
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "ScatterAddNdim" device_type: "CPU"') for unknown op: ScatterAddNdim
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "TopNInsert" device_type: "CPU"') for unknown op: TopNInsert
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "TopNRemove" device_type: "CPU"') for unknown op: TopNRemove
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "TreePredictions" device_type: "CPU"') for unknown op: TreePredictions
    E c:	f_jenkinshomeworkspace
    elease-windevicecpuoswindows	ensorflowcoreframeworkop_kernel.cc:943] OpKernel ('op: "UpdateFertileSlots" device_type: "CPU"') for unknown op: UpdateFertileSlots
    [0.0, 0.0]
    [5.0, 4.5]
    [10.0, 4.5549998]
    [10.0, 4.6094499]
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  • 原文地址:https://www.cnblogs.com/weizhen/p/6741705.html
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