https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/autoencoder.py の最後の部分を変更する.

tensorflow_middle_output.py

canvas_orig = np.empty((28 * n, 28 * n))
canvas_recon = np.empty((28 * n, 28 * n))
canvas_middle = np.empty((16 * n, 8 * n))
for i in range(n):
    # MNIST test set
    batch_x, _ = mnist.test.next_batch(n)
    # ここで中間層の出力値を取得することができる
    # 取り出しはここが全て
    m = sess.run(encoder_op, feed_dict={X: batch_x})
    # Encode and decode the digit image
   	g = sess.run(decoder_op, feed_dict={X: batch_x})

    # Display original images
    for j in range(n):
        # Draw the original digits
        canvas_orig[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = batch_x[j].reshape([28, 28])
        # Display reconstructed images
	  for j in range(n):
        # Draw the middle digits
        canvas_middle[i * 16:(i + 1) * 16, j * 8:(j + 1) * 8] = m[j].reshape([16, 8])
        # Display reconstructed images
	  for j in range(n):
        # Draw the reconstructed digits
        canvas_recon[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = g[j].reshape([28, 28])

print("Original Images")
plt.figure(figsize=(n, n))
plt.imshow(canvas_orig, origin="upper", cmap="gray")
plt.show()

print("Middle Images")
plt.figure(figsize=(n, n))
plt.imshow(canvas_middle, origin="upper", cmap="gray")
plt.show()

print("Reconstructed Images")
plt.figure(figsize=(n, n))
plt.imshow(canvas_recon, origin="upper", cmap="gray")
plt.show()