evaluation.py 文件源码

def ae_reconstruction(enc, dec, eval_folder, gpu, data_iter, batch_size=32, img_chan=3, img_size=64):
    @chainer.training.make_extension()
    def sample_reconstruction(trainer):
        xp = enc.xp
        batch = data_iter.next()
        d_real = xp.zeros((batch_size, img_chan, img_size, img_size)).astype("f")
        for i in range(batch_size):
            d_real[i, :] = xp.asarray(batch[i])
        x = Variable(d_real, volatile=True)
        imgs = dec(enc(x, test=True), test=True)
        save_images_grid(imgs, path=eval_folder+"/iter_"+str(trainer.updater.iteration)+".rec.jpg",
            grid_w=batch_size//8, grid_h=8)
        save_images_grid(d_real, path=eval_folder+"/iter_"+str(trainer.updater.iteration)+".real.jpg",
            grid_w=batch_size//8, grid_h=8)

    return sample_reconstruction