unet.py 文件源码

def validate_model(self, val_iter, epoch, step):
        labels, codes, images = next(val_iter)
        fake_imgs, real_imgs, d_loss, g_loss, l1_loss = self.generate_fake_samples(images, labels)
        print("Sample: d_loss: %.5f, g_loss: %.5f, l1_loss: %.5f" % (d_loss, g_loss, l1_loss))

        merged_fake_images = merge(scale_back(fake_imgs), [self.batch_size, 1])
        merged_real_images = merge(scale_back(real_imgs), [self.batch_size, 1])
        merged_pair = np.concatenate([merged_real_images, merged_fake_images], axis=1)

        model_id, _ = self.get_model_id_and_dir()

        model_sample_dir = os.path.join(self.sample_dir, model_id)
        if not os.path.exists(model_sample_dir):
            os.makedirs(model_sample_dir)

        sample_img_path = os.path.join(model_sample_dir, "sample_%02d_%04d.png" % (epoch, step))
        misc.imsave(sample_img_path, merged_pair)