RNN之所以称为循环神经网路，即一个序列当前的输出与前面的输出也有关。具体的表现形式为网络会对前面的信息进行记忆并应用于当前输出的计算中，即隐藏层之间的节点不再无连接而是有连接的，并且隐藏层的输入不仅包括输入层的输出还包括上一时刻隐藏层的输出。
RNN的应用领域有很多, 可以说只要考虑时间先后顺序的问题都可以使用RNN来解决.这里主要说一下几个常见的应用领域:

自然语言处理(NLP): 主要有视频处理, 文本生成, 语言模型, 图像处理
机器翻译, 机器写小说
语音识别
图像描述生成
文本相似度计算
音乐推荐、网易考拉商品推荐、Youtube视频推荐等新的应用领域.

RNN

RNN层级结构, 它主要有输入层,Hidden Layer, 输出层组成.
![RNN层级结构][base64str1]

其中，

\[
S_{t} = f(Ux_{t} + WS_{t-1}) \\
o_{t} = g(V S_{t})
\]

其中,f和g均为激活函数. 其中f可以是tanh,relu,sigmoid等激活函数，g通常是softmax也可以是其他。时间就向前推进，此时的状态s1作为时刻1的记忆状态将参与下一个时刻的预测活动。
注意:

这里的W,U,V在每个时刻都是相等的(权重共享).
隐藏状态可以理解为: S=f(现有的输入+过去记忆总结)

RNN的反向传播

由于每一步的输出不仅仅依赖当前步的网络，并且还需要前若干步网络的状态，那么这种BP改版的算法叫做Backpropagation Through Time(BPTT) , 也就是将输出端的误差值反向传递,运用梯度下降法进行更新.

设每一次的输出值$O_t$都会产生一个误差值$E_t$, 则总的误差可以表示为:

\[
E = \sum_t e_t
\]

损失函数可以使用交叉熵损失函数也可以使用平方误差损失函数.
以$t = 3$时刻为例, 根据链式求导法则可以得到$t = 3$时刻的偏导数为:

\[
\frac{\partial E_3}{\partial W} = \frac{\partial E_3}{\partial o_3} \frac{\partial o_3}{\partial S_3} \frac{\partial S_3}{\partial W}
\]

此时, 根据公式$ S_ = f(Ux_ + WS_)$我们会发现, $ S_3$除了和$W$有关之外, 还和前一时刻$S_2$有关.
对于$S_3$直接展开得到下面的式子:

\[
\frac{\partial S_3}{\partial W} = \frac{\partial S_3}{\partial S_3} * \frac{\partial S_3^+}{\partial W}+ \frac{\partial S_3}{\partial S_2} *\frac{\partial S_2}{\partial W}
\]

对于$S_2$直接展开得到下面的式子:

\[
\frac{\partial S_2}{\partial W} = \frac{\partial S_2}{\partial S_2} * \frac{\partial S_2^+}{\partial W}+ \frac{\partial S_2}{\partial S_1} *\frac{\partial S_1}{\partial W}
\]

对于$S_1$直接展开得到下面的式子:

\[
\frac{\partial S_1}{\partial W} = \frac{\partial S_1}{\partial S_1} * \frac{\partial S_1^+}{\partial W}+ \frac{\partial S_1}{\partial S_0} *\frac{\partial S_0}{\partial W}
\]

将上述三个式子合并得到:

\[
\frac{\partial S_3}{\partial W} = \sum_{k=0}^3
\frac{\partial S_3}{\partial S_k} * \frac{\partial S_k^+}{\partial W}
\]

这样就得到了公式:

\[
\frac{\partial E_3}{\partial W} = \sum_{k=0}^3 \frac{\partial E_3}{\partial o_3} \frac{\partial o_3}{\partial S_3} \frac{\partial S_3}{\partial S_k} \frac{\partial^+ S_k}{\partial W}
\]

其中$\frac{\partial^+ S_k}{\partial W}$表示的是$S_k$对$W$直接求导, 不考虑$S_$的影响.
其次是对U的更新方法. 由于参数U求解和W求解类似,这里就不在赘述了,最终得到的具体的公式如下:

\[
\frac{\partial E_3}{\partial U} = \sum_{k=0}^3 \frac{\partial E_3}{\partial o_3} \frac{\partial o_3}{\partial S_3} \frac{\partial W^{3-k} a_k}{\partial U} \frac{\partial^+ S_3}{\partial f}
$$

最后,给出$V$的更新公式($V$只和输出$O$有关):
$$
\frac{\partial E_3}{\partial V} = \frac{\partial E_3}{\partial O_3}
\frac{\partial O_3}{\partial V}
$$

累乘会导致激活函数导数的累乘，进而会导致“梯度消失“和“梯度爆炸“现象的发生。在实际操作中，
激活函数一般选取sigmoid或者tanh函数，他们的导数最大都不大于1，随着时间序列的不断深入，小数的累乘就会导致梯度越来越小直到接近于0，这就是“梯度消失“现象。但，tanh函数相对于sigmoid函数来说梯度较大，收敛速度更快且引起梯度消失更慢。还有一个原因是sigmoid函数还有一个缺点，Sigmoid函数输出不是零中心对称。sigmoid的输出均大于0，这就使得输出不是0均值，称为偏移现象，这将导致后一层的神经元将上一层输出的非0均值的信号作为输入。关于原点对称的输入和中心对称的输出，网络会收敛地更好。
解决“梯度消失“的方法主要有：
1、选取更好的激活函数
如ReLU函数,ReLU函数的左侧导数为0，右侧导数恒为1，这就避免了“梯度消失“的发生。但恒为1的导数容易导致“梯度爆炸“，但设定合适的阈值可以解决这个问题。还有一点就是如果左侧横为0的导数有可能导致把神经元学死，不过设置合适的步长也可以有效避免这个问题的发生。
2、改变传播结构
如长短时记忆（LSTM）或门限递归单元（GRU）结构等。

# LSTM
LSTM (Long Short Term Memory networks)解决了传统RNN的长期依赖性问题。
和RNN不同的是: RNN中$h_t=U x_t+W S_{t-1}$,就是个简单的线性求和的过程. 而LSTM可以通过“门”结构来去除或者增加“细胞状态”的信息,实现了对重要内容的保留和对不重要内容的去除。通过Sigmoid层输出一个0到1之间的概率值，描述每个部分有多少量可以通过，0表示“不允许任务变量通过”，1表示“运行所有变量通过 ”。

结构如下：

![LSTM层级结构][base64str2]

相比RNN只有一个传递状态$ h^t $ ，LSTM有两个传输状态，一个$ c^t $（cell state），和一个 $ h^t $（hidden state）。（Tips：RNN中的$ h^t $对于LSTM中的$ c^t $）。
其中对于传递下去的$ c^t $改变得很慢，通常输出的$ c^t $是上一个状态传过来的$ c^{t-1} $加上一些数值。

> $ c^t $作为记忆单元(cell state)，综合了当前词$x_t$和前一时刻记忆单元$c_{t-1}$的信息。这和ResNet中的残差逼近思想十分相似，通过从$c_{t-1}$到$c_t$的”短路连接”，梯度得已有效地反向传播。当$f_t$处于闭合状态时， $c_t$的梯度可以直接沿着最下面的短路线传递到$c_{t-1}$，不受参数$W$的影响，这是LSTM能有效地缓解梯度消失现象的关键所在。

而$ h^t $则在不同节点下往往会有很大的区别。
首先使用LSTM的当前输入$ x^t $和上一个状态传递下来的$ h^{t-1} $拼接训练得到四个状态。

![LSTM四个状态][base64str3]
![LSTM四个状态][base64str4]

其中，$ z^f $，$ z^i $，$ z^o $ 是由拼接向量乘以权重矩阵之后，再通过一个 $sigmoid$ 激活函数转换成0到1之间的数值，来作为一种门控状态。而$z$则是将结果通过一个 $tanh$ 激活函将转换成-1到1之间的值（这里使用 $tanh$ 是因为这里是将其做为输入数据，而不是门控信号）。

> LSTM有三个门，用于保护和控制细胞的状态。
$ z^f $作为忘记门(forget gate)，控制上一时刻记忆单元$c_{t-1}$的信息融入记忆单元$c_t$。在理解一句话时，当前词$x_t$可能继续延续上文的意思继续描述，也可能从当前词$x_t$开始描述新的内容，与上文无关忘记门门的目的就是判断的是上一时刻的记忆单元$c_{t-1}$对计算当前记忆单元$c_t$的重要性。
$ z^i $作为输入门(input gate)，控制当前词$x_t$的信息融入记忆单元$c_t$。在理解一句话时，当前词$x_t$可能对整句话的意思很重要，也可能并不重要。输入门的目的就是判断当前词$x_t$对全局的重要性。
$ z^o $作为输出门(output gate): 是从记忆单元$c_t$产生隐层单元$h_t$。并不是$c_t$中的全部信息都和隐层单元$h_t$有关，$c_t$可能包含了很多对$h_t$无用的信息，因此，输出门的作用就是判断$c_t$中哪些部分是对$h_t$有用的，哪些部分是无用的。

![LSTM结构][base64str5]

其中，$\bigodot$是Hadamard Product，也就是操作矩阵中对应的元素相乘，因此要求两个相乘矩阵是同型的。$\bigoplus$则代表进行矩阵加法。
LSTM内部主要有三个阶段：
1. 忘记阶段。这个阶段主要是对上一个节点传进来的输入进行选择性忘记。简单来说就是会 “忘记不重要的，记住重要的”。
具体来说是通过计算得到的$z^f$（f表示forget）来作为忘记门控，来控制上一个状态的$c^{t-1}$ 哪些需要留哪些需要忘。

2. 选择记忆阶段。这个阶段将这个阶段的输入有选择性地进行“记忆”。主要是会对输入$x^{t}$ 进行选择记忆。哪些重要则着重记录下来，哪些不重要，则少记一些。当前的输入内容由前面计算得到的$z$表示。而选择的门控信号则是由$z^i$（i代表information）来进行控制。
>将上面两步得到的结果相加，即可得到传输给下一个状态的$c^t$。也就是上图中的第一个公式。
3. 输出阶段。这个阶段将决定哪些将会被当成当前状态的输出。主要是通过$z^o$来进行控制的。并且还对上一阶段得到的$z^o$进行了放缩（通过一个tanh激活函数进行变化）。

与普通RNN类似，输出$y^t$往往最终也是通过$h^t$变化得到。
LSTM的内部通过门控状态来控制传输状态，记住需要长时间记忆的，忘记不重要的信息；而不像普通的RNN那样只能够“呆萌”地仅有一种记忆叠加方式。对很多需要“长期记忆”的任务来说，尤其好用。
但也因为引入了很多内容，导致参数变多，也使得训练难度加大了很多。因此很多时候我们往往会使用效果和LSTM相当但参数更少的GRU来构建大训练量的模型。

# GRU
门控循环单元(GRU)将忘记和输入门组合成一个单一的“更新门”。它还将单元格状态和隐藏状态合并，并进行了一些其他更改。所得到的模型比标准LSTM模型更简单。相比LSTM，使用GRU能够达到相当的效果，并且相比之下更容易进行训练，能够很大程度上提高训练效率，因此很多时候会更倾向于使用GRU。
GRU的输入输出结构与普通的RNN是一样的。
有一个当前的输入$x_t$，和上一个节点传递下来的隐状态（hidden state）$h_{t-1}$，这个隐状态包含了之前节点的相关信息。
结合$x_t$和$h_{t-1}$，GRU会得到当前隐藏节点的输出$y_t$和传递给下一个节点的隐状态$h_t$。
首先，我们先通过上一个传输下来的状态$h_{t-1}$和当前节点的输入入$x_t$来获取两个门控状态。如下图所示，其中$r$控制重置的门控（reset gate），$z$为控制更新的门控（update gate）。

![GRU门控][base64str6]
得到门控信号之后，首先使用重置门控来得到“重置”之后的数据$h_{t-1}^{'}=h_{t-1}\bigodot r$，再将$h_{t-1}^{'}$与输入$x_t$进行拼接，再通过一个tanh激活函数来将数据放缩到-1~1的范围内。即得到如下图所示的$h^{'}$ 。

![GRU$h^{'}$][base64str7]

这里的$h^{'}$主要是包含了当前输入的$x_t$数据。有针对性地对$h^{'}$添加到当前的隐藏状态，相当于”记忆了当前时刻的状态“。类似于LSTM的选择记忆阶段。

![GRU内部结构][base64str8]

> 图中的$\bigodot$是Hadamard Product，也就是操作矩阵中对应的元素相乘，因此要求两个相乘矩阵是同型的。$\bigoplus$则代表进行矩阵加法操作。

最后介绍GRU最关键的一个步骤，我们可以称之为”更新记忆“阶段。
在这个阶段，我们同时进行了遗忘了记忆两个步骤。我们使用了先前得到的更新门控$z$（update gate）。
更新表达式：
\]

h^{t = z \bigodot h} + (1-z) \bigodot h^{'}

首先再次强调一下，门控信号（这里的$z$）的范围为0~1。门控信号越接近1，代表”记忆“下来的数据越多；而越接近0则代表”遗忘“的越多。

GRU很聪明的一点就在于，我们使用了同一个门控$z$就同时可以进行遗忘和选择记忆（LSTM则要使用多个门控）。

$z \bigodot h^{t-1}$：表示对原本隐藏状态的选择性“遗忘”。这里的$z$可以想象成遗忘门（forget gate），忘记$h^{t-1}$维度中一些不重要的信息。
$(1-z) \bigodot h^{'}$：表示对包含当前节点信息的$h^{'}$进行选择性”记忆“。与上面类似，这里的$`-z`$同理会忘记$h^{'}$维度中的一些不重要的信息。或者，这里我们更应当看做是对$h^{'}$维度中的某些信息进行选择。
$h^t = z \bigodot h^{t-1} + (1-z) \bigodot h^{'}$：结合上述，这一步的操作就是忘记传递下来的$h^{t-1}$中的某些维度信息，并加入当前节点输入的某些维度信息。

> 可以看到，这里的遗忘$z$和选择$1-z$是联动的。也就是说，对于传递进来的维度信息，我们会进行选择性遗忘，则遗忘了多少权重（$z$），我们就会使用包含当前输入的$h^{'}$中所对应的权重进行弥补$1-z$。以保持一种”恒定“状态。

## LSTM与GRU的关系
$r$(reset gate)实际上与他的名字有点不符。我们仅仅使用它来获得了$h^{'}$ 。
那么这里的$h^{'}$实际上可以看成对应于LSTM中的hidden state；上一个节点传下来的$h^{t-1}$ 则对应于LSTM中的cell state。$z$对应的则是LSTM中的$z^f$ forget gate，那么$1-z$ 我们似乎就可以看成是选择门$z^i$了。
LSTM与GRU在从$t$ 到 $t-1$ 的更新时都引入了加法。这个加法的好处在于能防止梯度弥散，因此LSTM和GRU都比一般的RNN效果更好。

## 梯度消失或者梯度爆炸问题处理方法
LSTM 和 GRU对于梯度消失或者梯度爆炸的问题处理方法主要是:
对于梯度消失: 由于它们都有特殊的方式存储”记忆”，那么以前梯度比较大的”记忆”不会像简单的RNN一样马上被抹除，因此可以一定程度上克服梯度消失问题。
对于梯度爆炸:用来克服梯度爆炸的问题就是gradient clipping，也就是当你计算的梯度超过阈值c或者小于阈值-c的时候，便把此时的梯度设置成c或-c。

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