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d49a4611
编写于
3月 14, 2017
作者:
T
Travis CI
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develop/doc/_sources/howto/usage/cmd_parameter/arguments_en.md.txt
...oc/_sources/howto/usage/cmd_parameter/arguments_en.md.txt
+0
-10
develop/doc/_sources/howto/usage/cmd_parameter/detail_introduction_en.md.txt
...s/howto/usage/cmd_parameter/detail_introduction_en.md.txt
+0
-9
develop/doc/howto/usage/cmd_parameter/arguments_en.html
develop/doc/howto/usage/cmd_parameter/arguments_en.html
+0
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develop/doc/howto/usage/cmd_parameter/detail_introduction_en.html
...doc/howto/usage/cmd_parameter/detail_introduction_en.html
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develop/doc/searchindex.js
develop/doc/searchindex.js
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develop/doc_cn/_sources/howto/usage/cmd_parameter/arguments_cn.md.txt
...cn/_sources/howto/usage/cmd_parameter/arguments_cn.md.txt
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develop/doc_cn/_sources/howto/usage/cmd_parameter/detail_introduction_cn.md.txt
...s/howto/usage/cmd_parameter/detail_introduction_cn.md.txt
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develop/doc_cn/howto/usage/cmd_parameter/arguments_cn.html
develop/doc_cn/howto/usage/cmd_parameter/arguments_cn.html
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develop/doc_cn/howto/usage/cmd_parameter/detail_introduction_cn.html
..._cn/howto/usage/cmd_parameter/detail_introduction_cn.html
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develop/doc_cn/searchindex.js
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未找到文件。
develop/doc/_sources/howto/usage/cmd_parameter/arguments_en.md.txt
浏览文件 @
d49a4611
...
...
@@ -228,16 +228,6 @@ It looks like there are a lot of arguments. However, most of them are for develo
<td class="left"></td><td class="left"></td><td class="left">√</td><td class="left">√</td>
</tr>
<tr>
<td class="left" rowspan = "2">metric learning</td><td class="left">external</td>
<td class="left">√</td><td class="left">√</td><td class="left">√</td><td class="left">√</td>
</tr>
<tr>
<td class="left">data_server_port</td>
<td class="left"></td><td class="left">√</td><td class="left"></td><td class="left">√</td>
</tr>
<tr>
<td class="left" rowspan = "16">PServer</td><td class="left">start_pserver</td>
<td class="left"></td><td class="left">√</td><td class="left"></td><td class="left">√</td>
...
...
develop/doc/_sources/howto/usage/cmd_parameter/detail_introduction_en.md.txt
浏览文件 @
d49a4611
...
...
@@ -184,15 +184,6 @@
- Specify shared dynamic library. It can be defined out of paddle by user.
- type: string (default: "", null).
## Metric Learning
* `--external`
- Whether to use external machine for metric learning.
- type: bool (default: 0).
* `--data_server_port`
- Listening port for dserver (data server), dserver is mainly used in metric learning.
- type: int32 (default: 21134).
## DataProvider
* `--memory_threshold_on_load_data`
...
...
develop/doc/howto/usage/cmd_parameter/arguments_en.html
浏览文件 @
d49a4611
...
...
@@ -351,12 +351,6 @@
<td
class=
"left"
>
diy_beam_search_prob_so
</td>
<td
class=
"left"
></td><td
class=
"left"
></td><td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td>
</tr><tr>
<td
class=
"left"
rowspan =
"2"
>
metric learning
</td><td
class=
"left"
>
external
</td>
<td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td>
</tr><tr>
<td
class=
"left"
>
data_server_port
</td>
<td
class=
"left"
></td><td
class=
"left"
>
√
</td><td
class=
"left"
></td><td
class=
"left"
>
√
</td>
</tr><tr>
<td
class=
"left"
rowspan =
"16"
>
PServer
</td><td
class=
"left"
>
start_pserver
</td>
<td
class=
"left"
></td><td
class=
"left"
>
√
</td><td
class=
"left"
></td><td
class=
"left"
>
√
</td>
</tr><tr>
...
...
develop/doc/howto/usage/cmd_parameter/detail_introduction_en.html
浏览文件 @
d49a4611
...
...
@@ -181,7 +181,6 @@
<li><a
class=
"reference internal"
href=
"#test"
>
Test
</a></li>
<li><a
class=
"reference internal"
href=
"#gpu"
>
GPU
</a></li>
<li><a
class=
"reference internal"
href=
"#nlp-rnn-lstm-gru"
>
NLP: RNN/LSTM/GRU
</a></li>
<li><a
class=
"reference internal"
href=
"#metric-learning"
>
Metric Learning
</a></li>
<li><a
class=
"reference internal"
href=
"#dataprovider"
>
DataProvider
</a></li>
<li><a
class=
"reference internal"
href=
"#unit-test"
>
Unit Test
</a></li>
<li><a
class=
"reference internal"
href=
"#parameter-server-and-distributed-communication"
>
Parameter Server and Distributed Communication
</a></li>
...
...
@@ -463,21 +462,6 @@
</li>
</ul>
</div>
<div
class=
"section"
id=
"metric-learning"
>
<span
id=
"metric-learning"
></span><h2>
Metric Learning
<a
class=
"headerlink"
href=
"#metric-learning"
title=
"Permalink to this headline"
>
¶
</a></h2>
<ul
class=
"simple"
>
<li><code
class=
"docutils literal"
><span
class=
"pre"
>
--external
</span></code><ul>
<li>
Whether to use external machine for metric learning.
</li>
<li>
type: bool (default: 0).
</li>
</ul>
</li>
<li><code
class=
"docutils literal"
><span
class=
"pre"
>
--data_server_port
</span></code><ul>
<li>
Listening port for dserver (data server), dserver is mainly used in metric learning.
</li>
<li>
type: int32 (default: 21134).
</li>
</ul>
</li>
</ul>
</div>
<div
class=
"section"
id=
"dataprovider"
>
<span
id=
"dataprovider"
></span><h2>
DataProvider
<a
class=
"headerlink"
href=
"#dataprovider"
title=
"Permalink to this headline"
>
¶
</a></h2>
<ul
class=
"simple"
>
...
...
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d49a4611
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:[
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:
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:[
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:
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:[
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56
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:
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"
:[
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:[
26
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27
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49
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:[
11
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17
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25
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26
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34
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54
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56
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float
"
:[
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7
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15
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16
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20
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25
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34
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36
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47
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50
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54
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:[
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5
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8
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11
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55
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56
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57
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:[
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23
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32
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54
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57
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"
:[
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9
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11
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12
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16
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17
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20
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24
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41
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52
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54
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55
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"
:[
2
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10
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11
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16
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17
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20
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27
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36
,
55
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56
],
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"
:[
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33
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35
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42
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43
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48
,
52
,
55
,
56
],
"
null
"
:[
10
,
34
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39
,
54
],
"
public
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:[
34
,
37
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42
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43
,
56
],
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return
"
:[
3
,
8
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9
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10
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11
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16
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17
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19
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20
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22
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23
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34
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42
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48
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52
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53
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54
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57
],
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short
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:[
10
,
11
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16
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17
,
25
,
54
,
55
,
56
],
"
static
"
:[
10
,
42
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"
super
"
:
34
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switch
"
:[
42
,
56
],
"
throw
"
:
42
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"
:[
3
,
7
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9
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10
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11
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12
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15
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16
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19
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20
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55
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57
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try
"
:[
12
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24
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36
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48
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54
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"
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"
:
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"
:[
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,
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7
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9
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15
,
20
,
24
,
32
,
39
,
48
,
52
,
56
,
57
],
AGE
:[
42
,
43
],
AND
:
54
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ARE
:
54
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AWS
:[
35
,
44
,
45
],
Abs
:
6
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Age
:
53
,
And
:[
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9
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10
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27
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29
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33
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41
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42
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43
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47
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50
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54
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56
,
57
],
But
:[
3
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10
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11
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16
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17
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EOS
:[
10
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16
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For
:[
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56
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57
],
Going
:
56
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Has
:
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IDs
:
52
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Ids
:
52
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Into
:
42
,
Its
:[
3
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32
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42
,
54
],
Not
:[
23
,
37
],
ONE
:
3
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One
:[
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10
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11
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17
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32
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34
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39
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48
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52
,
56
,
57
],
QoS
:
43
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THE
:
3
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TLS
:[
23
,
42
],
That
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10
,
16
,
20
,
24
,
27
,
39
,
41
],
The
:[
2
,
3
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7
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8
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11
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49
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50
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52
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53
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54
,
55
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56
,
57
],
Their
:[
3
,
10
,
16
],
Then
:[
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10
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26
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27
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32
,
33
,
34
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36
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42
,
43
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47
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49
,
54
,
55
,
56
],
There
:[
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16
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22
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23
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25
,
29
,
36
,
42
,
48
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49
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50
,
51
,
52
,
54
,
57
],
These
:[
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,
41
,
49
,
55
],
USE
:
54
,
USING
:
54
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Use
:[
3
,
23
,
24
,
34
,
36
,
39
,
40
,
42
,
54
],
Used
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11
,
17
],
Useful
:
3
,
Using
:[
43
,
56
],
VPS
:
42
,
WITH
:
33
,
Will
:
20
,
With
:[
3
,
10
,
11
,
16
,
17
,
25
,
48
,
55
],
Yes
:
27
,
___fc_layer_0__
:
42
,
__init__
:
34
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__list_to_map__
:
54
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__main__
:
50
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__meta__
:
54
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__name__
:
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__rnn_step__
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_error
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_link
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,
17
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_proj
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,
16
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_res2_1_branch1_bn
:
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_source_language_embed
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32
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47
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_target_language_embed
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32
,
47
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aaaaaaaaaaaaa
:
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,
abc
:[
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,
16
],
abl
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,
16
,
23
,
48
,
56
],
about
:[
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,
10
,
11
,
16
,
17
,
25
,
27
,
36
,
38
,
39
,
42
,
46
,
55
,
56
,
57
],
abov
:[
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,
5
,
10
,
16
,
23
,
25
,
27
,
36
,
42
,
43
,
48
,
50
,
52
,
55
],
abs
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11
,
17
,
48
],
absolut
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2
,
37
],
academ
:
53
,
acceler
:
41
,
accept
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3
,
5
,
20
,
23
,
24
,
52
,
55
],
acceptor
:
55
,
access
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,
10
,
11
,
17
,
23
,
32
,
57
],
accessmod
:
42
,
accident
:
53
,
accord
:[
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3
,
9
,
10
,
16
,
32
,
33
,
37
,
38
,
39
,
41
],
accordingli
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5
,
34
],
accordingto
:
55
,
accrod
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11
,
17
],
accuraci
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,
34
,
52
,
53
,
56
],
achiev
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36
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ack
:
39
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acl
:
56
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aclimdb
:
56
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aclimdb_v1
:
20
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across
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act
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11
,
16
,
17
,
25
,
32
,
52
],
act_typ
:
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action
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42
,
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],
activ
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4
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10
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11
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16
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17
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21
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25
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26
,
34
,
39
,
52
,
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],
activi
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actual
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10
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16
,
25
,
27
],
adadelta
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12
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],
adagrad
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adam
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12
,
23
,
52
,
56
,
57
],
adamax
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12
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],
adamoptim
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,
52
,
56
,
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],
adapt
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12
,
25
,
56
,
57
],
add
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,
10
,
11
,
16
,
17
,
20
,
25
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26
,
33
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34
,
36
,
41
,
52
,
54
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add_input
:
34
,
add_test
:
34
,
add_to
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,
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],
add_unittest_without_exec
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,
addbia
:
34
,
added
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3
,
9
,
34
],
adding
:
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,
addit
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,
11
,
16
,
17
,
27
,
52
],
address
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27
,
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,
39
],
addrow
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34
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addtion
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addto
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10
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addtolay
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adject
:
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,
adjust
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25
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admin
:
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adopt
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advanc
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advantag
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27
,
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],
adventur
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53
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adverb
:
56
,
adversari
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24
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advic
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36
,
affect
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10
,
16
],
afi
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3
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aforement
:
37
,
after
:[
10
,
16
,
26
,
29
,
32
,
34
,
37
,
39
,
41
,
42
,
43
,
48
,
49
,
50
,
52
,
54
,
55
,
56
,
57
],
again
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,
36
],
against
:
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,
age
:
54
,
agg_level
:[
10
,
16
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aggreg
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42
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aggregatelevel
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10
,
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aid
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36
,
aim
:[
56
,
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],
aircraft
:
57
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airplan
:
49
,
aistat
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alex
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16
,
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alexnet_pass1
:
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alexnet_pass2
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,
algorithm
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,
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,
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,
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,
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,
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,
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alia
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,
7
,
13
,
14
,
15
],
align
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,
16
,
17
,
20
,
57
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all
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3
,
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,
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,
10
,
12
,
15
,
16
,
22
,
23
,
25
,
27
,
32
,
33
,
34
,
36
,
37
,
38
,
39
,
41
,
42
,
43
,
47
,
48
,
50
,
52
,
53
,
54
,
55
,
56
,
57
],
alloc
:[
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,
15
,
34
,
41
],
allow
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23
,
27
,
33
,
34
,
36
,
39
,
42
,
52
],
allow_only_one_model_on_one_gpu
:[
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,
39
,
41
],
almost
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,
17
,
25
,
37
,
47
],
along
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alreadi
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,
36
,
37
,
39
,
42
,
43
,
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alreali
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38
,
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pnpairvalidationpredict_fil
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pod
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pod_nam
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point
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polar
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polici
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polit
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poll
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poo
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pool3
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positive_label
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possibl
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post1
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potenti
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power
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precis
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pred
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predefin
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predic
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predicate_dict
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predicate_dict_fil
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predicate_slot
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predict
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predict_fil
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predict_output_dir
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predict_sampl
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predicted_label_id
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predictor
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predin
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prefer
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prefetch
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prefix
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pregrad
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preinstal
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premodel
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prepar
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preprcess
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preprocess
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prevent
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price
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primari
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primarili
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principl
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print
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printallstatu
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printer
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printstatu
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prite
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privileg
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prob
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probabilist
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probability_of_label_0
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probability_of_label_1
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probabl
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32
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50
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problem
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proc
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proc_from_raw_data
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proce
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24
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procedur
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proceed
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process
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process_pr
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process_test
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process_train
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processdata
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processor
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produc
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24
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product
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42
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52
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productgraph
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profil
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proflier
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program
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programm
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progress
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proivid
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proj
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project
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promis
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prompt
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prone
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prop
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propag
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properli
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properti
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propos
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proposit
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protect
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proto
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protobuf
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protocol
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proven
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provid
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providermemory_threshold_on_load_data
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provis
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provod
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prune
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pserver
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pserver_num_thread
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pserverstart_pserv
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pseudo
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psize
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pull
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punctuat
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purchas
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purpos
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push_back
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put
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pvc
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pwd
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py_paddl
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pydataprovid
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pydataprovider2
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32
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pydataproviderwrapp
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pyramid
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pyramid_height
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python
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8
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16
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26
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27
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pythonpath
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pzo
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qualifi
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qualiti
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queri
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question
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quick
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quick_start
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quick_start_data
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quickli
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quickstart
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quit
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quot
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rais
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ramnath
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ran
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rand
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random
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randomli
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randomnumberse
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rang
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49
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rank
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23
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50
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rare
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rate
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12
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15
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34
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37
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,
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rather
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42
,
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ratio
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raw_meta
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rdma
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rdma_tcp
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reach
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read
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23
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24
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32
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42
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read_from_realistic_imag
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read_from_rng
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read_mnist_imag
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read_ranking_model_data
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reader
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reader_creator_bool
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reader_creator_random_imag
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reader_creator_random_image_and_label
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reader_dict
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readi
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43
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readm
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,
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readonesamplefromfil
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readwritemani
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real
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24
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25
,
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realist
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reason
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17
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23
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27
,
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rebas
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recal
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receiv
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8
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recent
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reciev
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recogn
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recognit
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50
,
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recommand
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recommend
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17
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34
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recommonmark
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recompil
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record
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recordio
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recov
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rectangular
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recurr
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recurrent_group
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17
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recurrent_lay
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recurrentgroup
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recurrentlay
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recurs
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recv
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reduc
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39
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refer
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referenc
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regard
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regardless
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regex
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region
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regist
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register_gpu_profil
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register_lay
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register_timer_info
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registri
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regress
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regression_cost
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regular
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rel
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17
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relat
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relationship
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releas
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42
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53
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relev
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reli
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relu
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16
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reluactiv
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10
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remain
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remot
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15
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27
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33
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34
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37
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41
,
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remoteparameterupdat
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remov
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37
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39
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renam
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reorgan
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16
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repeat
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10
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replac
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repo
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33
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report
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36
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37
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repositori
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repres
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5
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10
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12
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16
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32
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34
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42
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49
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52
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53
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represent
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52
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reproduc
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request
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47
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requir
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9
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10
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16
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23
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34
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42
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48
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49
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52
,
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requrest
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33
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res5_3_branch2c_bn
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50
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res5_3_branch2c_conv
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50
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res
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55
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research
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16
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49
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53
,
56
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resembl
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56
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reserv
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3
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reserveoutput
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34
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reset
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16
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reshap
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24
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reshape_s
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10
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16
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residu
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50
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resnet
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51
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resnet_101
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50
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resnet_152
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50
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resnet_50
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50
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resolv
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33
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43
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resourc
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27
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42
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respect
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25
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34
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55
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respons
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16
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42
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rest
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16
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25
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restart
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restartpolici
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42
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43
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restrict
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39
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resu
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24
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result
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32
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52
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55
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result_fil
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32
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ret_val
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retir
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retran
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retriev
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43
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return_seq
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17
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reus
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24
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34
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reveal
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revers
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16
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17
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32
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55
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review
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52
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reviews_electronics_5
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revis
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52
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rewrit
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rgb
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16
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rgen
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rho
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rich
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right
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rmsprop
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52
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rmspropoptim
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rnn
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rnn_bias_attr
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rnn_layer_attr
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rnn_out
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rnn_step
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rnn_use_batch
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rnnlm
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robot
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role
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51
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roman
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romanc
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root
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42
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root_dir
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rot
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rotat
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roughli
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routin
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routledg
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row
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row_id
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rsize
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rule
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run
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runinitfunct
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runtim
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s_fusion
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s_id
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s_param
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s_recurrent_group
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sacrif
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sai
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sake
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sale
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same
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samping_id
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sample_dim
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sample_id
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zachari
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titles
:[
"
ABOUT
"
,
"
API
"
,
"
Introduction
"
,
"
PyDataProvider2
"
,
"
API
"
,
"
Python Prediction
"
,
"
Activations
"
,
"
Parameter Attributes
"
,
"
DataSources
"
,
"
Evaluators
"
,
"
Layers
"
,
"
Networks
"
,
"
Optimizers
"
,
"
Poolings
"
,
"
Activation
"
,
"
Parameter Attribute
"
,
"
Layers
"
,
"
Networks
"
,
"
Optimizer
"
,
"
Pooling
"
,
"
Datasets
"
,
"
Model Configuration
"
,
"
Training and Inference
"
,
"
PaddlePaddle Design Doc
"
,
"
Python Data Reader Design Doc
"
,
"
Simple Linear Regression
"
,
"
Installing from Sources
"
,
"
PaddlePaddle in Docker Containers
"
,
"
Install and Build
"
,
"
Debian Package installation guide
"
,
"
GET STARTED
"
,
"
RNN Models
"
,
"
RNN Configuration
"
,
"
Contribute Code
"
,
"
Write New Layers
"
,
"
HOW TO
"
,
"
Tune GPU Performance
"
,
"
Run Distributed Training
"
,
"
Argument Outline
"
,
"
Detail Description
"
,
"
Set Command-line Parameters
"
,
"
Use Case
"
,
"
Distributed PaddlePaddle Training on AWS with Kubernetes
"
,
"
Paddle On Kubernetes
"
,
"
<no title>
"
,
"
<no title>
"
,
"
PaddlePaddle Documentation
"
,
"
Chinese Word Embedding Model Tutorial
"
,
"
Generative Adversarial Networks (GAN)
"
,
"
Image Classification Tutorial
"
,
"
Model Zoo - ImageNet
"
,
"
TUTORIALS
"
,
"
Quick Start
"
,
"
MovieLens Dataset
"
,
"
Regression MovieLens Ratting
"
,
"
Semantic Role labeling Tutorial
"
,
"
Sentiment Analysis Tutorial
"
,
"
Text generation Tutorial
"
],
titleterms
:{
"
case
"
:
41
,
"
class
"
:
34
,
"
function
"
:
47
,
"
new
"
:
34
,
"
return
"
:
24
,
AWS
:
42
,
Abs
:
14
,
DNS
:
42
,
EFS
:
42
,
For
:
43
,
KMS
:
42
,
Use
:[
41
,
43
],
Using
:[
27
,
33
],
about
:
0
,
absactiv
:
6
,
access
:
42
,
account
:
42
,
activ
:[
6
,
14
],
adadelta
:
18
,
adadeltaoptim
:
12
,
adagrad
:
18
,
adagradoptim
:
12
,
adam
:
18
,
adamax
:
18
,
adamaxoptim
:
12
,
adamoptim
:
12
,
add
:
42
,
address
:
42
,
addto
:
16
,
addto_lay
:
10
,
adversari
:
48
,
aggreg
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10
,
16
],
algorithm
:
52
,
analysi
:
56
,
api
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1
,
4
],
appendix
:
52
,
applic
:
4
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approach
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36
,
architectur
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32
,
52
],
argument
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24
,
38
,
41
,
52
],
asset
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42
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associ
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42
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async
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39
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attent
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32
,
attribut
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7
,
15
],
auc_evalu
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9
,
avg
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19
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avgpool
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13
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avx
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27
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aws
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42
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background
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25
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base
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9
,
10
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baseactiv
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6
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basepool
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19
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basepoolingtyp
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13
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basesgdoptim
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12
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batch
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24
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batch_norm
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16
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batch_norm_lay
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10
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batch_siz
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24
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beam_search
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10
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16
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between
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23
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bidirect
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56
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bidirectional_lstm
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11
,
17
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bilinear_interp
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16
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bilinear_interp_lay
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10
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bleu
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57
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block_expand
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16
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block_expand_lay
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10
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book
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27
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brelu
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14
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breluactiv
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6
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bucket
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42
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build
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26
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28
,
43
],
built
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36
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cach
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3
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cento
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26
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check
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16
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34
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37
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chines
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47
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choos
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42
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chunk_evalu
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cifar
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20
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classif
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classification_error_evalu
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classification_error_printer_evalu
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clone
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cloudform
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cluster
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code
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concept
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config
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contribut
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convolut
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core
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42
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cos_sim
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\ No newline at end of file
Search
.
setIndex
({
docnames
:[
"
about/index_en
"
,
"
api/index_en
"
,
"
api/v1/data_provider/dataprovider_en
"
,
"
api/v1/data_provider/pydataprovider2_en
"
,
"
api/v1/index_en
"
,
"
api/v1/predict/swig_py_paddle_en
"
,
"
api/v1/trainer_config_helpers/activations
"
,
"
api/v1/trainer_config_helpers/attrs
"
,
"
api/v1/trainer_config_helpers/data_sources
"
,
"
api/v1/trainer_config_helpers/evaluators
"
,
"
api/v1/trainer_config_helpers/layers
"
,
"
api/v1/trainer_config_helpers/networks
"
,
"
api/v1/trainer_config_helpers/optimizers
"
,
"
api/v1/trainer_config_helpers/poolings
"
,
"
api/v2/config/activation
"
,
"
api/v2/config/attr
"
,
"
api/v2/config/layer
"
,
"
api/v2/config/networks
"
,
"
api/v2/config/optimizer
"
,
"
api/v2/config/pooling
"
,
"
api/v2/data
"
,
"
api/v2/model_configs
"
,
"
api/v2/run_logic
"
,
"
design/api
"
,
"
design/reader/README
"
,
"
getstarted/basic_usage/index_en
"
,
"
getstarted/build_and_install/build_from_source_en
"
,
"
getstarted/build_and_install/docker_install_en
"
,
"
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24
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36
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48
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54
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"
void
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34
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"
while
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,
3
,
7
,
9
,
15
,
20
,
24
,
32
,
39
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48
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52
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56
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57
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AGE
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43
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AND
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54
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ARE
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54
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AWS
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44
,
45
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Abs
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,
Age
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53
,
And
:[
3
,
9
,
10
,
12
,
16
,
24
,
27
,
29
,
33
,
41
,
42
,
43
,
47
,
50
,
54
,
56
,
57
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But
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11
,
16
,
17
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EOS
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16
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For
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3
,
8
,
9
,
10
,
12
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16
,
20
,
23
,
24
,
25
,
26
,
27
,
32
,
34
,
36
,
37
,
38
,
39
,
41
,
47
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49
,
50
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52
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56
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57
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Going
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56
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Has
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IDs
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52
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Ids
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Into
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42
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Its
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One
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34
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QoS
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20
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39
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41
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The
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3
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5
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7
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8
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9
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10
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11
,
12
,
14
,
15
,
16
,
17
,
20
,
22
,
23
,
24
,
25
,
26
,
27
,
28
,
29
,
32
,
33
,
34
,
36
,
37
,
39
,
41
,
42
,
43
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47
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48
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49
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50
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52
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53
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54
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55
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56
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57
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Their
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16
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Then
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10
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26
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32
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There
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10
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16
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22
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23
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36
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These
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VPS
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Will
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academ
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accordingli
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ack
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acl
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allow
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andd
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anim
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parameter_nam
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parameter_serv
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person
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perspect
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pick
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pickl
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picklabl
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point
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polar
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polici
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polit
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poll
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poo
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port_num
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ports_num
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pos
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posit
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possibl
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post1
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potenti
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pred
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predicate_dict_fil
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predicate_slot
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predict
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predin
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prefix
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preprocess
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price
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primari
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primarili
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principl
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print
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printallstatu
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printer
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printstatu
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prite
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privileg
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prob
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probability_of_label_0
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probability_of_label_1
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probabl
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problem
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proc
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proc_from_raw_data
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proce
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procedur
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proceed
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process
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process_pr
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process_test
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process_train
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processdata
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processor
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produc
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product
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52
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productgraph
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profil
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proflier
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program
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37
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programm
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progress
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proivid
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proj
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project
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promis
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prompt
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prone
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prop
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propag
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properli
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properti
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propos
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proposit
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protect
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proto
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protobuf
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protocol
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prove
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proven
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provid
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providermemory_threshold_on_load_data
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provis
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42
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provod
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3
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prune
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pserver
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39
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pserver_num_thread
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39
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pserverstart_pserv
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pseudo
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psize
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pull
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punctuat
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purchas
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purpos
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push_back
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put
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pvc
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pwd
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py_paddl
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pydataprovid
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pydataprovider2
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pydataproviderwrapp
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pyramid
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pyramid_height
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python
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16
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pythonpath
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pzo
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qualifi
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qualiti
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queri
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question
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quick
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quick_start
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quick_start_data
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quickli
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quickstart
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quit
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quot
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rais
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ramnath
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ran
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rand
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random
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titles
:[
"
ABOUT
"
,
"
API
"
,
"
Introduction
"
,
"
PyDataProvider2
"
,
"
API
"
,
"
Python Prediction
"
,
"
Activations
"
,
"
Parameter Attributes
"
,
"
DataSources
"
,
"
Evaluators
"
,
"
Layers
"
,
"
Networks
"
,
"
Optimizers
"
,
"
Poolings
"
,
"
Activation
"
,
"
Parameter Attribute
"
,
"
Layers
"
,
"
Networks
"
,
"
Optimizer
"
,
"
Pooling
"
,
"
Datasets
"
,
"
Model Configuration
"
,
"
Training and Inference
"
,
"
PaddlePaddle Design Doc
"
,
"
Python Data Reader Design Doc
"
,
"
Simple Linear Regression
"
,
"
Installing from Sources
"
,
"
PaddlePaddle in Docker Containers
"
,
"
Install and Build
"
,
"
Debian Package installation guide
"
,
"
GET STARTED
"
,
"
RNN Models
"
,
"
RNN Configuration
"
,
"
Contribute Code
"
,
"
Write New Layers
"
,
"
HOW TO
"
,
"
Tune GPU Performance
"
,
"
Run Distributed Training
"
,
"
Argument Outline
"
,
"
Detail Description
"
,
"
Set Command-line Parameters
"
,
"
Use Case
"
,
"
Distributed PaddlePaddle Training on AWS with Kubernetes
"
,
"
Paddle On Kubernetes
"
,
"
<no title>
"
,
"
<no title>
"
,
"
PaddlePaddle Documentation
"
,
"
Chinese Word Embedding Model Tutorial
"
,
"
Generative Adversarial Networks (GAN)
"
,
"
Image Classification Tutorial
"
,
"
Model Zoo - ImageNet
"
,
"
TUTORIALS
"
,
"
Quick Start
"
,
"
MovieLens Dataset
"
,
"
Regression MovieLens Ratting
"
,
"
Semantic Role labeling Tutorial
"
,
"
Sentiment Analysis Tutorial
"
,
"
Text generation Tutorial
"
],
titleterms
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case
"
:
41
,
"
class
"
:
34
,
"
function
"
:
47
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"
new
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34
,
"
return
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AWS
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42
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DNS
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cach
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ctc
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16
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ctc_error_evalu
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ctc_layer
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cudnnmax
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custom
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dat
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data
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\ No newline at end of file
develop/doc_cn/_sources/howto/usage/cmd_parameter/arguments_cn.md.txt
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@@ -228,16 +228,6 @@
<td class="left"></td><td class="left"></td><td class="left">√</td><td class="left">√</td>
</tr>
<tr>
<td class="left" rowspan = "2">度量学习(metric learning)</td><td class="left">external</td>
<td class="left">√</td><td class="left">√</td><td class="left">√</td><td class="left">√</td>
</tr>
<tr>
<td class="left">data_server_port</td>
<td class="left"></td><td class="left">√</td><td class="left"></td><td class="left">√</td>
</tr>
<tr>
<td class="left" rowspan = "16">参数服务器(PServer)</td><td class="left">start_pserver</td>
<td class="left"></td><td class="left">√</td><td class="left"></td><td class="left">√</td>
...
...
develop/doc_cn/_sources/howto/usage/cmd_parameter/detail_introduction_cn.md.txt
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...
@@ -180,15 +180,6 @@
- 用户可以自定义beam search的方法,编译成动态库,供PaddlePaddle加载。 该参数用于指定动态库路径.
- 类型: string (默认: "", null).
## 度量学习(Metric Learning)
* `--external`
- 指示是否使用外部机器进行度量学习.
- 类型: bool (默认: 0).
* `--data_server_port`
- 数据服务器(data server)的监听端口,主要用在度量学习中.
- 类型: int32 (默认: 21134).
## 数据支持(DataProvider)
* `--memory_threshold_on_load_data`
...
...
develop/doc_cn/howto/usage/cmd_parameter/arguments_cn.html
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...
...
@@ -358,12 +358,6 @@
<td
class=
"left"
>
diy_beam_search_prob_so
</td>
<td
class=
"left"
></td><td
class=
"left"
></td><td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td>
</tr><tr>
<td
class=
"left"
rowspan =
"2"
>
度量学习(metric learning)
</td><td
class=
"left"
>
external
</td>
<td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td><td
class=
"left"
>
√
</td>
</tr><tr>
<td
class=
"left"
>
data_server_port
</td>
<td
class=
"left"
></td><td
class=
"left"
>
√
</td><td
class=
"left"
></td><td
class=
"left"
>
√
</td>
</tr><tr>
<td
class=
"left"
rowspan =
"16"
>
参数服务器(PServer)
</td><td
class=
"left"
>
start_pserver
</td>
<td
class=
"left"
></td><td
class=
"left"
>
√
</td><td
class=
"left"
></td><td
class=
"left"
>
√
</td>
</tr><tr>
...
...
develop/doc_cn/howto/usage/cmd_parameter/detail_introduction_cn.html
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...
...
@@ -188,7 +188,6 @@
<li><a
class=
"reference internal"
href=
"#"
>
测试
</a></li>
<li><a
class=
"reference internal"
href=
"#gpu"
>
GPU
</a></li>
<li><a
class=
"reference internal"
href=
"#nlp-rnn-lstm-gru"
>
自然语言处理(NLP): RNN/LSTM/GRU
</a></li>
<li><a
class=
"reference internal"
href=
"#metric-learning"
>
度量学习(Metric Learning)
</a></li>
<li><a
class=
"reference internal"
href=
"#dataprovider"
>
数据支持(DataProvider)
</a></li>
<li><a
class=
"reference internal"
href=
"#"
>
单元测试
</a></li>
<li><a
class=
"reference internal"
href=
"#"
>
参数服务器和分布式通信
</a></li>
...
...
@@ -470,21 +469,6 @@
</li>
</ul>
</div>
<div
class=
"section"
id=
"metric-learning"
>
<span
id=
"metric-learning"
></span><h2>
度量学习(Metric Learning)
<a
class=
"headerlink"
href=
"#metric-learning"
title=
"永久链接至标题"
>
¶
</a></h2>
<ul
class=
"simple"
>
<li><code
class=
"docutils literal"
><span
class=
"pre"
>
--external
</span></code><ul>
<li>
指示是否使用外部机器进行度量学习.
</li>
<li>
类型: bool (默认: 0).
</li>
</ul>
</li>
<li><code
class=
"docutils literal"
><span
class=
"pre"
>
--data_server_port
</span></code><ul>
<li>
数据服务器(data server)的监听端口,主要用在度量学习中.
</li>
<li>
类型: int32 (默认: 21134).
</li>
</ul>
</li>
</ul>
</div>
<div
class=
"section"
id=
"dataprovider"
>
<span
id=
"dataprovider"
></span><h2>
数据支持(DataProvider)
<a
class=
"headerlink"
href=
"#dataprovider"
title=
"永久链接至标题"
>
¶
</a></h2>
<ul
class=
"simple"
>
...
...
develop/doc_cn/searchindex.js
浏览文件 @
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。
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