[ZH] 13-3 Inline latex broken

[xcastilla]

Hi @JonathanSum ! Just for your info,
There seems to be some inline latex broken on lecture 13-3:

The rest of the lectures I've checked seem to be fine.

[JonathanSum]

I tried to fix it, but it looks like the latex is the same as the one in the English version.

[JonathanSum]

Chinese version:

在自我注意力机制中，我们有一个输入集$\lbrace\boldsymbol{x}_{i}\rbrace^{t}{i=1}$。不像序列那样，它没有顺序的。
隐藏向量$\boldsymbol{h}$是由集之中的向量的线性组合得出来的。
我们可以用矩阵向量乘法来以$\boldsymbol{X}\boldsymbol{a}$去表达这个东西，这里$\boldsymbol{a}$包含一些会缩放向量$\boldsymbol{x}{i}$的系数。

English version

In self-attention, we have a set of input $\lbrace\boldsymbol{x}_{i}\rbrace^{t}{i=1}$.
Unlike a sequence, it does not have an order.
Hidden vector $\boldsymbol{h}$ is given by linear combination of the vectors in the set.
We can express this as $\boldsymbol{X}\boldsymbol{a}$ using matrix vector multiplication, where $\boldsymbol{a}$ contains coefficients that scale the input vector $\boldsymbol{x}{i}$.

The following Latex that has issue in the Chinese version:

$\lbrace\boldsymbol{x}_{i}\rbrace^{t}_{i=1}$

$\boldsymbol{h}$

$\boldsymbol{X}\boldsymbol{a}$

$\boldsymbol{a}$

$\boldsymbol{x}_{i}$

[JonathanSum]

Pull request to fix this issue: #619

I will follow this to fix when I have time:
Guide line to fix: #576

But I think why xcastilla posted this issue here. It is because the latex is the same as the English one, but the Chinese version still has an issue.

[Atcold]

@JonathanSum, you may have to escape the _ like \_. Let me know if it works.

[JonathanSum]

I am still fixing it and testing it on my repo:
https://jonathansum.github.io/pytorch-Deep-Learning/zh/week13/13-3/

Updated: I tried to change_to be \_ .

[Atcold]

Was this fixed?

[JonathanSum]

Let's hope this pull request can fix them all. I checked out my repo. It looks like the one in above is fixed. There is another one. I will try to see this pull request can fix them all or not.
@#697

[Atcold]

Thank, going over the PRs right now.

[JonathanSum]

Problems are solved. I think we can close it.
You can see it here: https://atcold.github.io/pytorch-Deep-Learning/zh/week13/13-3/