''' 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]