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b7493ca8
编写于
8月 14, 2017
作者:
T
Travis CI
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develop/doc/api/v2/config/evaluators.html
develop/doc/api/v2/config/evaluators.html
+3
-3
develop/doc_cn/api/v2/config/evaluators.html
develop/doc_cn/api/v2/config/evaluators.html
+3
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未找到文件。
develop/doc/api/v2/config/evaluators.html
浏览文件 @
b7493ca8
...
...
@@ -417,7 +417,7 @@ F1-score of this label.</li>
<dd><p>
Positive-negative pair rate Evaluator which adapts to rank task like
learning to rank. This evaluator must contain at least three layers.
</p>
<p>
The simple usage:
</p>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"nb"
>
eval
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
evaluator
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
pnpair
</span><span
class=
"p"
>
(
</span><span
class=
"nb"
>
input
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
info
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
label
</span><span
class=
"p"
>
)
</span>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"nb"
>
eval
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
evaluator
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
pnpair
</span><span
class=
"p"
>
(
</span><span
class=
"nb"
>
input
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
label
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
info
</span><span
class=
"p"
>
)
</span>
</pre></div>
</div>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
...
...
@@ -425,12 +425,12 @@ learning to rank. This evaluator must contain at least three layers.</p>
<col
class=
"field-body"
/>
<tbody
valign=
"top"
>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Parameters:
</th><td
class=
"field-body"
><ul
class=
"first last simple"
>
<li><strong>
name
</strong>
(
<em>
None|basestring
</em>
)
–
Evaluator name.
</li>
<li><strong>
input
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Input Layer name. The output prediction of network.
</li>
<li><strong>
label
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Label layer name.
</li>
<li><strong>
info
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Label
layer name. (TODO, explaination)
</li>
<li><strong>
info
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Info
layer name. (TODO, explaination)
</li>
<li><strong>
weight
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Weight Layer name. It should be a matrix with size
[sample_num, 1]. (TODO, explaination)
</li>
<li><strong>
name
</strong>
(
<em>
None|basestring
</em>
)
–
Evaluator name.
</li>
</ul>
</td>
</tr>
...
...
develop/doc_cn/api/v2/config/evaluators.html
浏览文件 @
b7493ca8
...
...
@@ -422,7 +422,7 @@ F1-score of this label.</li>
<dd><p>
Positive-negative pair rate Evaluator which adapts to rank task like
learning to rank. This evaluator must contain at least three layers.
</p>
<p>
The simple usage:
</p>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"nb"
>
eval
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
evaluator
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
pnpair
</span><span
class=
"p"
>
(
</span><span
class=
"nb"
>
input
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
info
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
label
</span><span
class=
"p"
>
)
</span>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"nb"
>
eval
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
evaluator
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
pnpair
</span><span
class=
"p"
>
(
</span><span
class=
"nb"
>
input
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
label
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
info
</span><span
class=
"p"
>
)
</span>
</pre></div>
</div>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
...
...
@@ -430,12 +430,12 @@ learning to rank. This evaluator must contain at least three layers.</p>
<col
class=
"field-body"
/>
<tbody
valign=
"top"
>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
参数:
</th><td
class=
"field-body"
><ul
class=
"first last simple"
>
<li><strong>
name
</strong>
(
<em>
None|basestring
</em>
)
–
Evaluator name.
</li>
<li><strong>
input
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Input Layer name. The output prediction of network.
</li>
<li><strong>
label
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Label layer name.
</li>
<li><strong>
info
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Label
layer name. (TODO, explaination)
</li>
<li><strong>
info
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Info
layer name. (TODO, explaination)
</li>
<li><strong>
weight
</strong>
(
<em>
paddle.v2.config_base.Layer
</em>
)
–
Weight Layer name. It should be a matrix with size
[sample_num, 1]. (TODO, explaination)
</li>
<li><strong>
name
</strong>
(
<em>
None|basestring
</em>
)
–
Evaluator name.
</li>
</ul>
</td>
</tr>
...
...
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