text: """
  Know more, visit my Python tutorial page: https://morvanzhou.github.io/tutorials/
  My Youtube Channel: https://www.youtube.com/user/MorvanZhou
  
  Dependencies:
  tensorflow: 1.1.0
  matplotlib
  """
  import tensorflow as tf
  import numpy as np
  import matplotlib.pyplot as plt
  
  # fake data
  x = np.linspace(-5, 5, 200)     # x data, shape=(100, 1)
  
  # following are popular activation functions
  y_relu = tf.nn.relu(x)
  y_sigmoid = tf.nn.sigmoid(x)
  y_tanh = tf.nn.tanh(x)
  y_softplus = tf.nn.softplus(x)
  # y_softmax = tf.nn.softmax(x)  softmax is a special kind of activation function, it is about probability
  
  sess = tf.Session()
  y_relu, y_sigmoid, y_tanh, y_softplus = sess.run([y_relu,
                                                    y_sigmoid,
                                                    y_tanh,
                                                    y_softplus])
  
  # plt to visualize these activation function
  plt.figure(1, figsize=(8, 6))
  plt.subplot(221)
  plt.plot(x, y_relu, c='red', label='relu')
  plt.ylim((-1, 5))
  plt.legend(loc='best')
  
  plt.subplot(222)
  plt.plot(x, y_sigmoid, c='red', label='sigmoid')
  plt.ylim((-0.2, 1.2))
  plt.legend(loc='best')
  
  plt.subplot(223)
  plt.plot(x, y_tanh, c='red', label='tanh')
  plt.ylim((-1.2, 1.2))
  plt.legend(loc='best')
  
  plt.subplot(224)
  plt.plot(x, y_softplus, c='red', label='softplus')
  plt.ylim((-0.2, 6))
  plt.legend(loc='best')
  
  plt.show()
  