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单韦乔
Toy-MT-Introduction
Commits
7f78e16e
Commit
7f78e16e
authored
Oct 27, 2019
by
xiaotong
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2 个修改的文件
包含
294 行增加
和
9 行删除
+294
-9
Section05-Neural-Networks-and-Language-Modeling/section05-test.tex
+95
-9
Section05-Neural-Networks-and-Language-Modeling/section05.tex
+199
-0
没有找到文件。
Section05-Neural-Networks-and-Language-Modeling/section05-test.tex
查看文件 @
7f78e16e
...
@@ -120,17 +120,103 @@
...
@@ -120,17 +120,103 @@
\subsection
{
词嵌入
}
\subsection
{
词嵌入
}
%%%------------------------------------------------------------------------------------------------------------
%%%------------------------------------------------------------------------------------------------------------
%%%
用实例理解词的分布式表示
%%%
上下文表示模型
\begin{frame}
{
分布式表示的可视化
}
\begin{frame}
{
表示更长的片段 - 上下文表示模型
}
\begin{itemize}
\begin{itemize}
\item
\textbf
{
一个著名的例子
}
:国王
$
\to
$
王后
\\
\item
在语言模型中已经包含了每个位置的上下文表示信息
\begin{displaymath}
\begin{itemize}
\vv
{
\textrm
{
国王
}}
-
\vv
{
\textrm
{
男人
}}
+
\vv
{
\textrm
{
女人
}}
=
\vv
{
\textrm
{
王后
}}
\item
以RNN LM为例,位置
$
i
$
的隐层输出就是一种
$
w
_
1
...w
_
i
$
的表示
\end{displaymath}
\end{itemize}
这里,
$
\vv
{
\textrm
{
word
}}$
表示单词的分布式向量表示
\item
更多的词的可视化:相似的词聚在一起
\end{itemize}
\end{itemize}
\vspace
{
-0.5em
}
\begin{center}
\begin{tikzpicture}
\begin{scope}
\tikzstyle
{
rnnnode
}
= [draw,inner sep=5pt,minimum width=4em,minimum height=1.5em,fill=green!30!white,blur shadow=
{
shadow xshift=1pt,shadow yshift=-1pt
}
]
\node
[anchor=west,rnnnode] (node11) at (0,0)
{
\scriptsize
{
RNN Cell
}}
;
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[anchor=west,rnnnode] (node12) at ([xshift=2em]node11.east)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=west,rnnnode] (node13) at ([xshift=2em]node12.east)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=west,rnnnode] (node14) at ([xshift=2em]node13.east)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e1) at ([yshift=-1.2em]node11.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e2) at ([yshift=-1.2em]node12.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e3) at ([yshift=-1.2em]node13.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e4) at ([yshift=-1.2em]node14.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north] (w1) at ([yshift=-1em]e1.south)
{
\footnotesize
{
乔布斯
}}
;
\node
[anchor=north] (w2) at ([yshift=-1em]e2.south)
{
\footnotesize
{
任职
}}
;
\node
[anchor=north] (w3) at ([yshift=-1em]e3.south)
{
\footnotesize
{
于
}}
;
\node
[anchor=north] (w4) at ([yshift=-1em]e4.south)
{
\footnotesize
{
苹果
}}
;
\draw
[->,thick] ([yshift=0.1em]w1.north)--([yshift=-0.1em]e1.south);
\draw
[->,thick] ([yshift=0.1em]w2.north)--([yshift=-0.1em]e2.south);
\draw
[->,thick] ([yshift=0.1em]w3.north)--([yshift=-0.1em]e3.south);
\draw
[->,thick] ([yshift=0.1em]w4.north)--([yshift=-0.1em]e4.south);
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[->,thick] ([yshift=0.1em]e1.north)--([yshift=-0.1em]node11.south);
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[->,thick] ([yshift=0.1em]e2.north)--([yshift=-0.1em]node12.south);
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[->,thick] ([yshift=0.1em]e3.north)--([yshift=-0.1em]node13.south);
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[->,thick] ([yshift=0.1em]e4.north)--([yshift=-0.1em]node14.south);
\node
[anchor=south,rnnnode] (node21) at ([yshift=1.5em]node11.north)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=south,rnnnode] (node22) at ([yshift=1.5em]node12.north)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=south,rnnnode] (node23) at ([yshift=1.5em]node13.north)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=south,rnnnode] (node24) at ([yshift=1.5em]node14.north)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=south] (node31) at ([yshift=1.0em]node21.north)
{
\scriptsize
{
的表示
}}
;
\node
[anchor=south west] (node31new) at ([yshift=-0.3em]node31.north west)
{
\scriptsize
{
``乔布斯''
}}
;
\node
[anchor=south] (node32) at ([yshift=1.0em]node22.north)
{
\scriptsize
{
的表示
\ \ \
}}
;
\node
[anchor=south west] (node32new) at ([yshift=-0.3em]node32.north west)
{
\scriptsize
{
``乔布斯 任职''
}}
;
\node
[anchor=south] (node33) at ([yshift=1.0em]node23.north)
{
\scriptsize
{
的表示
\ \ \ \ \ \ \ \
}}
;
\node
[anchor=south west] (node33new) at ([yshift=-0.3em]node33.north west)
{
\scriptsize
{
``乔布斯 任职 于''
}}
;
\node
[anchor=south] (node34) at ([yshift=1.0em]node24.north)
{
\scriptsize
{
的表示
\ \ \ \ \ \ \ \
}}
;
\node
[anchor=south west] (node34new) at ([yshift=-0.3em]node34.north west)
{
\scriptsize
{
``乔布斯 任职 于 苹果''
}}
;
\draw
[->,thick] ([yshift=0.1em]node21.north)--([yshift=-0.1em]node31.south);
\draw
[->,thick] ([yshift=0.1em]node22.north)--([yshift=-0.1em]node32.south);
\draw
[->,thick] ([yshift=0.1em]node23.north)--([yshift=-0.1em]node33.south);
\draw
[->,thick] ([yshift=0.1em]node24.north)--([yshift=-0.1em]node34.south);
\draw
[->,thick] ([xshift=-1em]node21.west)--([xshift=-0.1em]node21.west);
\draw
[->,thick] ([xshift=0.1em]node21.east)--([xshift=-0.1em]node22.west);
\draw
[->,thick] ([xshift=0.1em]node22.east)--([xshift=-0.1em]node23.west);
\draw
[->,thick] ([xshift=0.1em]node23.east)--([xshift=-0.1em]node24.west);
\draw
[->,thick] ([xshift=0.1em]node24.east)--([xshift=1em]node24.east);
\draw
[->,thick] ([yshift=0.1em]node11.north)--([yshift=-0.1em]node21.south);
\draw
[->,thick] ([yshift=0.1em]node12.north)--([yshift=-0.1em]node22.south);
\draw
[->,thick] ([yshift=0.1em]node13.north)--([yshift=-0.1em]node23.south);
\draw
[->,thick] ([yshift=0.1em]node14.north)--([yshift=-0.1em]node24.south);
\draw
[->,thick] ([xshift=-1em]node11.west)--([xshift=-0.1em]node11.west);
\draw
[->,thick] ([xshift=0.1em]node11.east)--([xshift=-0.1em]node12.west);
\draw
[->,thick] ([xshift=0.1em]node12.east)--([xshift=-0.1em]node13.west);
\draw
[->,thick] ([xshift=0.1em]node13.east)--([xshift=-0.1em]node14.west);
\draw
[->,thick] ([xshift=0.1em]node14.east)--([xshift=1em]node14.east);
\visible
<2->
{
\node
[anchor=south] (toplabel1) at ([yshift=2em,xshift=-2em]node32new.north)
{
\footnotesize
{
``苹果''的表示:
}}
;
\node
[anchor=west,fill=blue!20!white,minimum width=3em] (toplabel2) at (toplabel1.east)
{
\footnotesize
{
上下文
}}
;
}
\visible
<3->
{
\node
[anchor=west,fill=red!20!white,minimum width=3em] (toplabel3) at (toplabel2.east)
{
\footnotesize
{
词
}}
;
}
\begin{pgfonlayer}
{
background
}
\visible
<3->
{
\node
[rectangle,inner sep=2pt,draw,thick,dashed,red] [fit = (e4)] (r2)
{}
;
\draw
[->,thick,red] (r2.west) .. controls +(west:0.8) and +(south:2) .. ([xshift=1.3em]toplabel3.south);
}
\visible
<2->
{
\node
[rectangle,inner sep=2pt,draw,thick,dashed,ublue,fill=white] [fit = (node33) (node33new)] (r1)
{}
;
\draw
[->,thick,ublue] ([xshift=-2em]r1.north) .. controls +(north:0.7) and +(south:0.7) .. ([xshift=-0.5em]toplabel2.south);
}
\end{pgfonlayer}
\end{scope}
\end{tikzpicture}
\end{center}
\end{frame}
\end{frame}
%%%------------------------------------------------------------------------------------------------------------
%%%------------------------------------------------------------------------------------------------------------
...
...
Section05-Neural-Networks-and-Language-Modeling/section05.tex
查看文件 @
7f78e16e
...
@@ -4454,9 +4454,208 @@ $\textbf{V}, \textbf{U}, \textbf{W}$: 参数
...
@@ -4454,9 +4454,208 @@ $\textbf{V}, \textbf{U}, \textbf{W}$: 参数
\end{itemize}
\end{itemize}
\end{frame}
\end{frame}
%%%------------------------------------------------------------------------------------------------------------
%%% 神经语言模型中的词嵌入
\begin{frame}
{
神经语言模型中的词嵌入
}
\begin{itemize}
\item
在神经语言模型中,需要把词表示成它的分布式表示
\begin{itemize}
\item
<2-> 其中
$
\textbf
{
C
}$
是词嵌入矩阵,每一行对应一个词的分布式表示
\item
<3->
$
\textbf
{
C
}$
可以用语言模型训练,也可以利用其它模型训练,固定词嵌入,让语言模型专注长片段的学习
\end{itemize}
\end{itemize}
\vspace
{
-0.5em
}
\begin{center}
\begin{tikzpicture}
\begin{scope}
\node
[anchor=center,inner sep=2pt] (e) at (0,0)
{
\small
{$
e
=
w
$}}
;
\node
[anchor=west,inner sep=2pt] (c) at (e.east)
{
\small
{$
\textbf
{
C
}$}}
;
\begin{pgfonlayer}
{
background
}
\node
[rectangle,inner sep=0.4em,draw,fill=blue!20!white] [fit = (e) (c)] (box)
{}
;
\end{pgfonlayer}
\draw
[->,thick] ([yshift=-1em]box.south)--([yshift=-0.1em]box.south) node [pos=0,below] (bottom1)
{
\small
{
单词
$
w
$}}
;
\draw
[->,thick] ([yshift=0.1em]box.north)--([yshift=1em]box.north) node [pos=1,above] (top1)
{
\scriptsize
{$
e
$
=(8,.2,-1,.9,...,1)
}}
;
\node
[anchor=north] (bottom2) at ([yshift=0.3em]bottom1.south)
{
\scriptsize
{$
w
$
=(0,0,1,0,...,0)
}}
;
\node
[anchor=south] (top2) at ([yshift=-0.3em]top1.north)
{
\small
{$
w
$
的分布式表示
}}
;
\visible
<2->
{
\node
[anchor=north west,fill=red!20!white] (cmatrix) at ([xshift=3em,yshift=1.0em]c.north east)
{
\scriptsize
{$
\begin
{
pmatrix
}
1
&
.
2
&
-
.
2
&
8
&
...
&
0
\\
.
6
&
.
8
&
-
2
&
1
&
...
&
-
.
2
\\
8
&
.
2
&
-
1
&
.
9
&
...
&
2
.
3
\\
1
&
1
.
2
&
-
.
9
&
3
&
...
&
.
2
\\
...
&
...
&
...
&
...
&
...
&
...
\\
1
&
.
3
&
3
&
.
9
&
...
&
5
.
1
\end
{
pmatrix
}$}}
;
\node
[anchor=west,inner sep=2pt,fill=red!30!white] (c) at (e.east)
{
\small
{$
\textbf
{
C
}$}}
;
\draw
[<-,thick] (c.east) -- ([xshift=3em]c.east);
}
\visible
<3->
{
\node
[anchor=south,draw,fill=green!20!white] (e2) at ([yshift=1.5em]cmatrix.north)
{
\scriptsize
{
外部词嵌入系统得到的
$
\textbf
{
C
}$}}
;
\draw
[->,very thick,dashed] (e2.south) -- (cmatrix.north);
}
\end{scope}
\end{tikzpicture}
\end{center}
\vspace
{
-1.0em
}
\begin{itemize}
\item
<4-> 词嵌入如何学习得到?
\begin{itemize}
\item
可以和语言模型的其它部分一起训练,不过速度较慢
\item
也可以考虑使用效率更高的外部模型,如word2vec、 Glove等,这样可以使用更大规模的数据
\end{itemize}
\end{itemize}
\end{frame}
%%%------------------------------------------------------------------------------------------------------------
%%%------------------------------------------------------------------------------------------------------------
\subsection
{
句子表示模型及预训练
}
\subsection
{
句子表示模型及预训练
}
%%%------------------------------------------------------------------------------------------------------------
%%% 词嵌入的问题
\begin{frame}
{
不仅如``词''
}
\begin{itemize}
\item
词嵌入已经成为诸多NLP系统的标配,当然也衍生出各种花式玩法,甚至有``embed everything''的口号,但是词嵌入也有问题
\begin{itemize}
\item
每个词都对应唯一的向量表示,但是对于一词多义现象,词义需要通过上下文进行区分。一个著名的例子:
\end{itemize}
\vspace
{
0.3em
}
\hspace
{
6em
}
Jobs was the CEO of
\alert
{
\underline
{
apple
}}
.
\\
\hspace
{
6em
}
He finally ate the
\alert
{
\underline
{
apple
}}
.
\item
<2-> 引入上下文信息
\begin{itemize}
\item
上述问题引发了新的思考:不能简单地考虑词的表示,应同时考虑其上下文信息
\item
对于句子中的一个词(或者位置),同时表示词和上下文
\end{itemize}
\end{itemize}
\visible
<2->
{
\begin{center}
\begin{tikzpicture}
\begin{scope}
\node
[anchor=west] (node1) at (0,0)
{
\footnotesize
{
Jobs was the CEO of
}}
;
\node
[anchor=west] (node2) at ([xshift=-0.2em,yshift=-0.05em]node1.east)
{
\footnotesize
{
\alert
{
\underline
{
apple
}}}}
;
\node
[anchor=west] (node3) at ([xshift=-0.2em,yshift=-0.1em]node2.east)
{
\footnotesize
{
.
}}
;
\node
[anchor=south,inner sep=2pt,minimum width=2.4em,fill=red!20!white] (node4) at ([yshift=1.5em]node2.north)
{
\scriptsize
{
词
}}
;
\node
[anchor=north] (label) at ([xshift=1em]node1.south)
{
\scriptsize
{
\textbf
{
词表示模型
}}}
;
\draw
[->,thick] (node2.north) -- (node4.south);
\end{scope}
\begin{scope}
[xshift=2in]
\node
[anchor=west] (node1) at (0,0)
{
\footnotesize
{
Jobs was the CEO of
}}
;
\node
[anchor=west] (node2) at ([xshift=-0.2em,yshift=-0.05em]node1.east)
{
\footnotesize
{
\alert
{
\underline
{
apple
}}}}
;
\node
[anchor=west] (node3) at ([xshift=-0.2em,yshift=-0.1em]node2.east)
{
\footnotesize
{
.
}}
;
\node
[anchor=south,inner sep=2pt,minimum width=2.4em,fill=red!20!white] (node4) at ([yshift=1.5em]node2.north)
{
\scriptsize
{
词
}}
;
\node
[anchor=south,inner sep=2pt,minimum width=2.4em,fill=blue!20!white] (node5) at (node4.north)
{
\scriptsize
{
上下文
}}
;
\node
[anchor=north] (label) at ([xshift=1em]node1.south)
{
\scriptsize
{
\textbf
{
词+上下文表示模型
}}}
;
\draw
[->,thick] (node2.north) -- (node4.south);
\draw
[->] ([xshift=1em]node1.north west) .. controls +(north:1) and +(west:2) .. ([yshift=0.2em]node5.west);
\draw
[->] ([xshift=3em]node1.north west) .. controls +(north:0.8) and +(west:1.5) .. ([yshift=-0.2em]node5.west);
\node
[anchor=east] (morelines) at ([xshift=-1.5em]node4.west)
{
...
}
;
\end{scope}
\end{tikzpicture}
\end{center}
}
\end{frame}
%%%------------------------------------------------------------------------------------------------------------
%%% 上下文表示模型
\begin{frame}
{
表示更长的片段 - 上下文表示模型
}
\begin{itemize}
\item
在语言模型中已经包含了每个位置的上下文表示信息
\begin{itemize}
\item
以RNN LM为例,位置
$
i
$
的隐层输出就是一种
$
w
_
1
...w
_
i
$
的表示
\end{itemize}
\end{itemize}
\vspace
{
-0.5em
}
\begin{center}
\begin{tikzpicture}
\begin{scope}
\tikzstyle
{
rnnnode
}
= [draw,inner sep=5pt,minimum width=4em,minimum height=1.5em,fill=green!30!white,blur shadow=
{
shadow xshift=1pt,shadow yshift=-1pt
}
]
\node
[anchor=west,rnnnode] (node11) at (0,0)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=west,rnnnode] (node12) at ([xshift=2em]node11.east)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=west,rnnnode] (node13) at ([xshift=2em]node12.east)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=west,rnnnode] (node14) at ([xshift=2em]node13.east)
{
\scriptsize
{
RNN Cell
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e1) at ([yshift=-1.2em]node11.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e2) at ([yshift=-1.2em]node12.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e3) at ([yshift=-1.2em]node13.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north,rnnnode,fill=red!30!white] (e4) at ([yshift=-1.2em]node14.south)
{
\scriptsize
{
embedding
}}
;
\node
[anchor=north] (w1) at ([yshift=-1em]e1.south)
{
\footnotesize
{
乔布斯
}}
;
\node
[anchor=north] (w2) at ([yshift=-1em]e2.south)
{
\footnotesize
{
任职
}}
;
\node
[anchor=north] (w3) at ([yshift=-1em]e3.south)
{
\footnotesize
{
于
}}
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RNN Cell
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RNN Cell
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RNN Cell
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RNN Cell
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的表示
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``乔布斯''
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的表示
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``乔布斯 任职''
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的表示
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``乔布斯 任职 于''
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的表示
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``乔布斯 任职 于 苹果''
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``苹果''的表示:
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上下文
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词
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\end{document}
\end{document}
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