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import tensorflow as tf
import matplotlib.pyplot as plt


    

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%matplotlib inline


    

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interactive_session=tf.InteractiveSession()


    

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global_steps=tf.Variable(0)


    

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learning_rate=tf.train.exponential_decay(0.1,global_steps,100,0.96,staircase=False)


    

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x=tf.constant([[3.0,4.0]])


    

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w=tf.Variable([[1.1],[2.0]])


    

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y_=tf.matmul(x,w)


    

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y=tf.constant([[20.0]])


    

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loss=tf.abs(tf.reduce_mean(y-y_))


    

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learning_step=tf.train.GradientDescentOptimizer(learning_rate).minimize(loss,global_step=global_steps)


    

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init_op=tf.initialize_all_variables()


    

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interactive_session.run(init_op)


    

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x_plot=[]
y_plot=[]


    

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for i in range(1000):
    interactive_session.run(learning_step)
    realtime_learning_rate=interactive_session.run(learning_rate)
    x_plot.append(i)
    y_plot.append(realtime_learning_rate)


    

In [16]:

    

plt.scatter(x_plot,y_plot)


    

    
Out[16]:





<matplotlib.collections.PathCollection at 0x7f2500237160>






    

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