draw_sampleQ.py

def sampleQ(h_enc):
    """
    Samples Zt ~ normrnd(mu,sigma) via reparameterization trick for normal dist
    mu is (batch,z_size)
    """
    with tf.variable_scope("mu",reuse=DO_SHARE):
        mu=linear(h_enc,z_size)
    with tf.variable_scope("sigma",reuse=DO_SHARE):
        logsigma=linear(h_enc,z_size)
        sigma=tf.exp(logsigma)
    return (mu + sigma*e, mu, logsigma, sigma)