char_rnn.py 文件源码

def __init__(self, n_vocab, n_units, train=True):
        super(charRNN, self).__init__(
            embed=L.EmbedID(n_vocab, n_units),
            l1=L.LSTM(n_units, n_units),
            l2=L.LSTM(n_units, n_units),
            l3=L.Linear(n_units, n_vocab),
        )
        for param in self.params():
            param.data[...] = np.random.uniform(-0.1, 0.1, param.data.shape)

        self.train = train