def model()

in encoder.py [0:0]

• 13 lines of code
• 1 McCabe index (conditional complexity)

def model(X, S, M=None, reuse=False):
    nsteps = X.get_shape()[1]
    cstart, hstart = tf.unstack(S, num=hps.nstates)
    with tf.variable_scope('model', reuse=reuse):
        words = embd(X, hps.nembd)
        inputs = tf.unstack(words, nsteps, 1)
        hs, cells, cfinal, hfinal = mlstm(
            inputs, cstart, hstart, M, hps.nhidden, scope='rnn', wn=hps.rnn_wn)
        hs = tf.reshape(tf.concat(hs, 1), [-1, hps.nhidden])
        logits = fc(
            hs, hps.nvocab, act=lambda x: x, wn=hps.out_wn, scope='out')
    states = tf.stack([cfinal, hfinal], 0)
    return cells, states, logits