更新：我不知道为什么要对此表示不满，非常感谢有人让我知道原因。谢谢
Now I have been looking RNN's for a while.
And the vanilla version seems pretty obvious to me, a model trains by running each word in a sequence through the network one at a time. Here in the rolled and unrolled version:
很简单，一个词遍及整个网络，然后遍历下一个。
Now i went on to look at lstm networks, where this model is used for a LSTM "cell"
The way it is decribed to me in many articles and videos, this cell is a model of what it looks like inside of a single neuron of the lstm network. This makes sense to me.
However, I then find a model like this:
在这里，似乎序列的每个元素都经过单个神经元，然后继续前进到下一个元素，这对我完全没有意义。 LSTM的意思是
1：整个网络的模型
2：一个单一神经元的模型，由于某种原因，一个单词/序列元素只需要在训练时通过一个神经元即可。
- 我完全误解了培训的工作方式
