RNN 展开实现LSTM按时间步迭代时，有必要令reuse=true么

Question

我看到很多样例代码中， 展开实现LSTM按时间步迭代时，都如下加上了一句
if timestep > 0:
tf.get_variable_scope().reuse_variables()

with tf.variable_scope('RNN'):
    for timestep in range(timestep_size):
        if timestep > 0:
            tf.get_variable_scope().reuse_variables()
        # 这里的state保存了每一层 LSTM 的状态
        (cell_output, state) = mlstm_cell(X[:, timestep, :], state)

我查了各类RNNCELL类的源代码，发现除了call函数外，还有build函数（此函数似乎是在创建所有的变量），且此函数只调用一次，并且是在call调用之前调用，并且查看源码注释时发现是这样写的：
For backwards compatibility purposes, most RNNCell instances allow their call methods to instantiate variables via tf.get_variable. The underlying variable scope thus keeps track of any variables, and returning cached versions. This is atypical of tf.layer objects, which separate this
part of layer building into a build method that is only called once.

Here we provide a subclass for RNNCell objects that act exactly as
Layer objects do. They must provide a build method and their
call methods do not access Variables tf.get_variable
所以我个人认为这句不需要加，求各位帮忙解答下，该不该加这句话

Answer 1

构造CNN以及LSTM等模型的时候，需要重复使用共享权重
如果你不要重复使用共享权重，就不要这一句