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  • 神经网络激活函数

    # Activation Functions
    #----------------------------------
    #
    # This function introduces activation
    # functions in TensorFlow
    
    # Implementing Activation Functions
    import matplotlib.pyplot as plt
    import numpy as np
    import tensorflow as tf
    from tensorflow.python.framework import ops
    ops.reset_default_graph()
    
    # Open graph session
    sess = tf.Session()
    
    # X range
    x_vals = np.linspace(start=-10., stop=10., num=100)
    
    # ReLU activation
    print(sess.run(tf.nn.relu([-3., 3., 10.])))
    y_relu = sess.run(tf.nn.relu(x_vals))
    
    # ReLU-6 activation
    print(sess.run(tf.nn.relu6([-3., 3., 10.])))
    y_relu6 = sess.run(tf.nn.relu6(x_vals))
    
    # Sigmoid activation
    print(sess.run(tf.nn.sigmoid([-1., 0., 1.])))
    y_sigmoid = sess.run(tf.nn.sigmoid(x_vals))
    
    # Hyper Tangent activation
    print(sess.run(tf.nn.tanh([-1., 0., 1.])))
    y_tanh = sess.run(tf.nn.tanh(x_vals))
    
    # Softsign activation
    print(sess.run(tf.nn.softsign([-1., 0., 1.])))
    y_softsign = sess.run(tf.nn.softsign(x_vals))
    
    # Softplus activation
    print(sess.run(tf.nn.softplus([-1., 0., 1.])))
    y_softplus = sess.run(tf.nn.softplus(x_vals))
    
    # Exponential linear activation
    print(sess.run(tf.nn.elu([-1., 0., 1.])))
    y_elu = sess.run(tf.nn.elu(x_vals))
    
    # Plot the different functions
    plt.plot(x_vals, y_softplus, 'r--', label='Softplus', linewidth=2)
    plt.plot(x_vals, y_relu, 'b:', label='ReLU', linewidth=2)
    plt.plot(x_vals, y_relu6, 'g-.', label='ReLU6', linewidth=2)
    plt.plot(x_vals, y_elu, 'k-', label='ExpLU', linewidth=0.5)
    plt.ylim([-1.5,7])
    plt.legend(loc='upper left')
    plt.show()
    
    plt.plot(x_vals, y_sigmoid, 'r--', label='Sigmoid', linewidth=2)
    plt.plot(x_vals, y_tanh, 'b:', label='Tanh', linewidth=2)
    plt.plot(x_vals, y_softsign, 'g-.', label='Softsign', linewidth=2)
    plt.ylim([-2,2])
    plt.legend(loc='upper left')
    plt.show()

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  • 原文地址:https://www.cnblogs.com/bonelee/p/8994319.html
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