如何在单隐藏层全连接神经网络中关闭单个神经元？

我整理了一个针对MNIST手写数字数据集训练的简单神经网络模型，它的隐藏层设置了600个节点，相关的前置导入代码和参数配置如下：

前置依赖导入代码 #

from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, InputLayer, Activation
from keras.optimizers import RMSprop, Adam
import numpy as np
import h5py
import matplotlib.pyplot as plt
from keras import backend as K
import tensorflow as tf

MNIST数据集加载与训练参数 #

• batch_size = 128
• num_classes = 10
• epochs = ...

内容的提问来源于stack exchange，提问作者Eruditio