char_lm_gcnn.py 文件源码

def LM(batch_size, window_size=3, vocsize=20000, embed_dim=20, hidden_dim=30, nb_layers=1):
    x = Input(batch_shape=(batch_size, None))
    # mebedding
    y = Embedding(vocsize+2, embed_dim, mask_zero=False)(x)
    for i in range(nb_layers-1):
        y = GCNN(hidden_dim, window_size=window_size,
                 name='gcnn{}'.format(i + 1))(y)
    y = GCNN(hidden_dim, window_size=window_size, 
             name='gcnn{}'.format(nb_layers))(y)
    y = TimeDistributed(Dense(vocsize+2, activation='softmax', name='dense{}'.format(nb_layers)))(y)

    model = Model(inputs=x, outputs=y)

    return model