variational_autoencoder.py 文件源码

def __init__(self, network_architecture, transfer_fct=tf.nn.softplus, 
                 learning_rate=0.001, batch_size=100):
        self.network_architecture = network_architecture
        self.transfer_fct = transfer_fct
        self.learning_rate = learning_rate
        self.batch_size = batch_size

        # tf Graph input
        self.x = tf.placeholder(tf.float32, [None, network_architecture["n_input"]])

        # Create autoencoder network
        self._create_network()
        # Define loss function based variational upper-bound and 
        # corresponding optimizer
        self._create_loss_optimizer()

        # Initializing the tensor flow variables
        init = tf.initialize_all_variables()

        # Launch the session
        self.sess = tf.InteractiveSession()
        self.sess.run(init)