eval_rank.py 文件源码

def build_encoder(tparams, options):
    """
    Construct encoder
    """
    # inputs (image, sentence)
    im = tensor.matrix('im', dtype='float32')
    s = tensor.matrix('s', dtype='float32')

    # embeddings
    eim = get_layer('ff')[1](tparams, im, options, prefix='ff_im', activ='linear')
    es = get_layer('ff')[1](tparams, s, options, prefix='ff_s', activ='linear')

    # L2 norm of rows
    lim = l2norm(eim)
    ls = l2norm(es)

    return [im, s], lim, ls

# optimizers
# name(hyperp, tparams, grads, inputs (list), cost) = f_grad_shared, f_update