小编zij*_*iji的帖子

我正在尝试为以下对象创建自动编码器：

1. 训练模型
2. 分离式编码器和解码器
3. 可视化压缩数据（编码器）
4. 使用任意压缩数据获取输出（解码器）

from keras.layers import Input, Dense, Conv2D, MaxPooling2D, UpSampling2D
from keras.models import Model
from keras import backend as K
from keras.datasets import mnist
import numpy as np

(x_train, _), (x_test, _) = mnist.load_data()

x_train = x_train.astype('float32') / 255.
x_train = x_train[:100,:,:,]
x_test = x_test.astype('float32') / 255.
x_test = x_train
x_train = np.reshape(x_train, (len(x_train), 28, 28, 1))  # adapt this if using `channels_first` image data format
x_test = np.reshape(x_test, (len(x_test), 28, 28, 1))  # adapt this if …

我应该使用哪个图来描述这样的链：

Input data->preprocessing->preprocessed data->
algorithm 1->if a good result, next step, if not - do algorithm 1 again...