layers.py 文件源码

def ar_layer(z0,hps,n_hidden=10):
    ''' old iaf layer '''
    # Repeat input
    z_rep = tf.reshape(tf.tile(z0,[1,hps.z_size]),[-1,hps.z_size])

    # make mask    
    mask = tf.sequence_mask(tf.range(hps.z_size),hps.z_size)[None,:,:]
    mask = tf.reshape(tf.tile(mask,[tf.shape(z0)[0],1,1]),[-1,hps.z_size])

    # predict mu and sigma
    z_mask = z_rep * tf.to_float(mask)
    mid = slim.fully_connected(z_mask,n_hidden,activation_fn=tf.nn.relu)
    pars = slim.fully_connected(mid,2,activation_fn=None)
    pars = tf.reshape(pars,[-1,hps.z_size,2])    
    mu, log_sigma = tf.unstack(pars,axis=2)
    return mu, log_sigma