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718e424b
编写于
10月 23, 2017
作者:
T
Travis CI
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Deploy to GitHub Pages:
43d69818
上级
7dd2ead4
变更
6
展开全部
隐藏空白更改
内联
并排
Showing
6 changed file
with
52 addition
and
52 deletion
+52
-52
develop/doc/api/v2/data.html
develop/doc/api/v2/data.html
+24
-24
develop/doc/searchindex.js
develop/doc/searchindex.js
+1
-1
develop/doc_cn/_sources/faq/local/index_cn.rst.txt
develop/doc_cn/_sources/faq/local/index_cn.rst.txt
+1
-1
develop/doc_cn/api/v2/data.html
develop/doc_cn/api/v2/data.html
+24
-24
develop/doc_cn/faq/local/index_cn.html
develop/doc_cn/faq/local/index_cn.html
+1
-1
develop/doc_cn/searchindex.js
develop/doc_cn/searchindex.js
+1
-1
未找到文件。
develop/doc/api/v2/data.html
浏览文件 @
718e424b
...
...
@@ -358,9 +358,9 @@ every element in this vector is either zero or one.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
non_value_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
binary vector. It means the input feature is a sparse vector and
the
e
very element in this vector is either zero or on
e.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
float_vector
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
vector. It means the input feature is a sparse vector. Most of
the
e
lements in this vector are zero, others could be any float valu
e.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<col
class=
"field-body"
/>
...
...
@@ -383,24 +383,18 @@ every element in this vector is either zero or one.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
value_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse vector. It means the input feature is a sparse vector. Most of the
elements in this vector are zero,
others could be any float value.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
float_vector_sequence
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Data type of a sequence of sparse vector, which most elements are zero,
others could be any float value.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<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 simple"
>
<li><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of this vector.
</li>
<li><strong>
seq_type
</strong>
(
<em>
int
</em>
)
–
sequence type of this input.
</li>
</ul>
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Parameters:
</th><td
class=
"field-body"
><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of sparse vector.
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
Returns:
</th><td
class=
"field-body"
><p
class=
"first"
>
An input type object.
</p>
</td>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
Returns:
</th><td
class=
"field-body"
>
An input type object
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Return type:
</th><td
class=
"field-body"
><p
class=
"first last"
>
InputType
</p>
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Return type:
</th><td
class=
"field-body"
>
InputType
</td>
</tr>
</tbody>
</table>
...
...
@@ -408,9 +402,9 @@ elements in this vector are zero, others could be any float value.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
vector
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
vector. It means the input feature is a sparse vector. Most of
the
e
lements in this vector are zero, others could be any float valu
e.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
non_value_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
binary vector. It means the input feature is a sparse vector and
the
e
very element in this vector is either zero or on
e.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<col
class=
"field-body"
/>
...
...
@@ -433,18 +427,24 @@ elements in this vector are zero, others could be any float value.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_v
ector_sequence
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Data type of a sequence of sparse vector, which most elements are zero,
others could be any float value.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_v
alue_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse vector. It means the input feature is a sparse vector. Most of the
elements in this vector are zero,
others could be any float value.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<col
class=
"field-body"
/>
<tbody
valign=
"top"
>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Parameters:
</th><td
class=
"field-body"
><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of sparse vector.
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Parameters:
</th><td
class=
"field-body"
><ul
class=
"first simple"
>
<li><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of this vector.
</li>
<li><strong>
seq_type
</strong>
(
<em>
int
</em>
)
–
sequence type of this input.
</li>
</ul>
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
Returns:
</th><td
class=
"field-body"
>
An input type object
</td>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
Returns:
</th><td
class=
"field-body"
><p
class=
"first"
>
An input type object.
</p>
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Return type:
</th><td
class=
"field-body"
>
InputType
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Return type:
</th><td
class=
"field-body"
><p
class=
"first last"
>
InputType
</p>
</td>
</tr>
</tbody>
</table>
...
...
develop/doc/searchindex.js
浏览文件 @
718e424b
因为 它太大了无法显示 source diff 。你可以改为
查看blob
。
develop/doc_cn/_sources/faq/local/index_cn.rst.txt
浏览文件 @
718e424b
...
...
@@ -174,7 +174,7 @@ decoder_inputs = paddle.layer.fc(
1. 两者都是对梯度的截断,但截断时机不同,前者在 :code:`optimzier` 更新网络参数时应用;后者在激活函数反向计算时被调用;
2. 截断对象不同:前者截断可学习参数的梯度,后者截断回传给前层的梯度;
除此之外,还可以通过减小学习
律
或者对数据进行归一化处理来解决这类问题。
除此之外,还可以通过减小学习
率
或者对数据进行归一化处理来解决这类问题。
5. 如何调用 infer 接口输出多个layer的预测结果
-----------------------------------------------
...
...
develop/doc_cn/api/v2/data.html
浏览文件 @
718e424b
...
...
@@ -372,9 +372,9 @@ every element in this vector is either zero or one.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
non_value_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
binary vector. It means the input feature is a sparse vector and
the
e
very element in this vector is either zero or on
e.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
float_vector
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
vector. It means the input feature is a sparse vector. Most of
the
e
lements in this vector are zero, others could be any float valu
e.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<col
class=
"field-body"
/>
...
...
@@ -397,24 +397,18 @@ every element in this vector is either zero or one.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
value_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse vector. It means the input feature is a sparse vector. Most of the
elements in this vector are zero,
others could be any float value.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
float_vector_sequence
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Data type of a sequence of sparse vector, which most elements are zero,
others could be any float value.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<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 simple"
>
<li><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of this vector.
</li>
<li><strong>
seq_type
</strong>
(
<em>
int
</em>
)
–
sequence type of this input.
</li>
</ul>
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
参数:
</th><td
class=
"field-body"
><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of sparse vector.
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
返回:
</th><td
class=
"field-body"
><p
class=
"first"
>
An input type object.
</p>
</td>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
返回:
</th><td
class=
"field-body"
>
An input type object
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
返回类型:
</th><td
class=
"field-body"
><p
class=
"first last"
>
InputType
</p>
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
返回类型:
</th><td
class=
"field-body"
>
InputType
</td>
</tr>
</tbody>
</table>
...
...
@@ -422,9 +416,9 @@ elements in this vector are zero, others could be any float value.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
vector
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
vector. It means the input feature is a sparse vector. Most of
the
e
lements in this vector are zero, others could be any float valu
e.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_
non_value_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse
binary vector. It means the input feature is a sparse vector and
the
e
very element in this vector is either zero or on
e.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<col
class=
"field-body"
/>
...
...
@@ -447,18 +441,24 @@ elements in this vector are zero, others could be any float value.</p>
<dl
class=
"function"
>
<dt>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_v
ector_sequence
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Data type of a sequence of sparse vector, which most elements are zero,
others could be any float value.
</p>
<code
class=
"descclassname"
>
paddle.v2.data_type.
</code><code
class=
"descname"
>
sparse_v
alue_slot
</code><span
class=
"sig-paren"
>
(
</span><em>
dim
</em>
,
<em>
seq_type=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
Sparse vector. It means the input feature is a sparse vector. Most of the
elements in this vector are zero,
others could be any float value.
</p>
<table
class=
"docutils field-list"
frame=
"void"
rules=
"none"
>
<col
class=
"field-name"
/>
<col
class=
"field-body"
/>
<tbody
valign=
"top"
>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
参数:
</th><td
class=
"field-body"
><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of sparse vector.
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
参数:
</th><td
class=
"field-body"
><ul
class=
"first simple"
>
<li><strong>
dim
</strong>
(
<em>
int
</em>
)
–
dimension of this vector.
</li>
<li><strong>
seq_type
</strong>
(
<em>
int
</em>
)
–
sequence type of this input.
</li>
</ul>
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
返回:
</th><td
class=
"field-body"
>
An input type object
</td>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
返回:
</th><td
class=
"field-body"
><p
class=
"first"
>
An input type object.
</p>
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
返回类型:
</th><td
class=
"field-body"
>
InputType
</td>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
返回类型:
</th><td
class=
"field-body"
><p
class=
"first last"
>
InputType
</p>
</td>
</tr>
</tbody>
</table>
...
...
develop/doc_cn/faq/local/index_cn.html
浏览文件 @
718e424b
...
...
@@ -414,7 +414,7 @@ layer_attr=paddle.attr.ExtraLayerAttribute(</p>
<li>
两者都是对梯度的截断,但截断时机不同,前者在
<code
class=
"code docutils literal"
><span
class=
"pre"
>
optimzier
</span></code>
更新网络参数时应用;后者在激活函数反向计算时被调用;
</li>
<li>
截断对象不同:前者截断可学习参数的梯度,后者截断回传给前层的梯度;
</li>
</ol>
<p>
除此之外,还可以通过减小学习
律
或者对数据进行归一化处理来解决这类问题。
</p>
<p>
除此之外,还可以通过减小学习
率
或者对数据进行归一化处理来解决这类问题。
</p>
</div>
<div
class=
"section"
id=
"infer-layer"
>
<h2><a
class=
"toc-backref"
href=
"#id20"
>
5. 如何调用 infer 接口输出多个layer的预测结果
</a><a
class=
"headerlink"
href=
"#infer-layer"
title=
"永久链接至标题"
>
¶
</a></h2>
...
...
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