model.py 文件源码

def build_encoder_w2v(tparams, options):
    """
    Computation graph for encoder, given pre-trained word embeddings
    """
    opt_ret = dict()

    trng = RandomStreams(1234)

    # word embedding (source)
    embedding = tensor.tensor3('embedding', dtype='float32')
    x_mask = tensor.matrix('x_mask', dtype='float32')

    # encoder
    proj = get_layer(options['encoder'])[1](tparams, embedding, None, options,
                                            prefix='encoder',
                                            mask=x_mask)
    ctx = proj[0][-1]

    return trng, embedding, x_mask, ctx