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e1b45851
编写于
12月 21, 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:
ad979089
上级
ab4121f5
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
122 addition
and
10 deletion
+122
-10
develop/doc/api/v2/fluid/layers.html
develop/doc/api/v2/fluid/layers.html
+60
-4
develop/doc/searchindex.js
develop/doc/searchindex.js
+1
-1
develop/doc_cn/api/v2/fluid/layers.html
develop/doc_cn/api/v2/fluid/layers.html
+60
-4
develop/doc_cn/searchindex.js
develop/doc_cn/searchindex.js
+1
-1
未找到文件。
develop/doc/api/v2/fluid/layers.html
浏览文件 @
e1b45851
...
@@ -956,9 +956,34 @@ LOD_Tensor.</p>
...
@@ -956,9 +956,34 @@ LOD_Tensor.</p>
<dl
class=
"function"
>
<dl
class=
"function"
>
<dt>
<dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant
</code><span
class=
"sig-paren"
>
(
</span><em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
out=None
</em><span
class=
"sig-paren"
>
)
</span></dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant
</code><span
class=
"sig-paren"
>
(
</span><em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
out=None
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
This function creates a tensor , with shape as mentioned in the input and
<dd><p><strong>
fill_constant
</strong></p>
specified dtype and fills this up with a constant value that
<p>
This function creates a tensor of specified
<em>
shape
</em>
and
comes in the input. It also sets the stop_gradient to be True.
</p>
<em>
dtype
</em>
, and initializes this with a constant supplied in
<em>
value
</em>
.
</p>
<p>
It also sets
<em>
stop_gradient
</em>
to True.
</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>
shape
</strong>
(
<em>
tuple|list|None
</em>
)
–
Shape of output tensor
</li>
<li><strong>
dtype
</strong>
(
<em>
np.dtype|core.DataType|str
</em>
)
–
Data type of output tensor
</li>
<li><strong>
value
</strong>
(
<em>
float
</em>
)
–
Constant value to initialize the output tensor
</li>
<li><strong>
out
</strong>
(
<em>
Variable
</em>
)
–
Output Variable to initialize
</li>
</ul>
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
Returns:
</th><td
class=
"field-body"
><p
class=
"first"
>
The tensor variable storing the output
</p>
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Return type:
</th><td
class=
"field-body"
><p
class=
"first last"
>
Variable
</p>
</td>
</tr>
</tbody>
</table>
<p
class=
"rubric"
>
Examples
</p>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"n"
>
data
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
fluid
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
layers
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
fill_constant
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
shape
</span><span
class=
"o"
>
=
</span><span
class=
"p"
>
[
</span><span
class=
"mi"
>
1
</span><span
class=
"p"
>
],
</span>
<span
class=
"n"
>
value
</span><span
class=
"o"
>
=
</span><span
class=
"mi"
>
0
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
dtype
</span><span
class=
"o"
>
=
</span><span
class=
"s1"
>
'
int64
'
</span><span
class=
"p"
>
)
</span>
</pre></div>
</div>
</dd></dl>
</dd></dl>
</div>
</div>
...
@@ -967,7 +992,38 @@ comes in the input. It also sets the stop_gradient to be True.</p>
...
@@ -967,7 +992,38 @@ comes in the input. It also sets the stop_gradient to be True.</p>
<dl
class=
"function"
>
<dl
class=
"function"
>
<dt>
<dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant_batch_size_like
</code><span
class=
"sig-paren"
>
(
</span><em>
input
</em>
,
<em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
input_dim_idx=0
</em>
,
<em>
output_dim_idx=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant_batch_size_like
</code><span
class=
"sig-paren"
>
(
</span><em>
input
</em>
,
<em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
input_dim_idx=0
</em>
,
<em>
output_dim_idx=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd></dd></dl>
<dd><p><strong>
fill_constant_batch_size_like
</strong></p>
<p>
This function creates a tensor of specified
<em>
shape
</em>
,
<em>
dtype
</em>
and batch size,
and initializes this with a constant supplied in
<em>
value
</em>
. The batch size is
obtained from the
<cite>
input
</cite>
tensor.
</p>
<p>
It also sets
<em>
stop_gradient
</em>
to True.
</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>
input
</strong>
(
<em>
Variable
</em>
)
–
Tensor whose dimensions will be used to get batch size
</li>
<li><strong>
shape
</strong>
(
<em>
tuple|list|None
</em>
)
–
Shape of output tensor
</li>
<li><strong>
dtype
</strong>
(
<em>
np.dtype|core.DataType|str
</em>
)
–
Data type of output tensor
</li>
<li><strong>
value
</strong>
(
<em>
float
</em>
)
–
Constant value to initialize the output tensor
</li>
<li><strong>
input_dim_idx
</strong>
(
<em>
int
</em>
)
–
Index of input
’
s batch size dimension
</li>
<li><strong>
output_dim_idx
</strong>
(
<em>
int
</em>
)
–
Index of output
’
s batch size dimension
</li>
</ul>
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
Returns:
</th><td
class=
"field-body"
><p
class=
"first"
>
The tensor variable storing the output
</p>
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
Return type:
</th><td
class=
"field-body"
><p
class=
"first last"
>
Variable
</p>
</td>
</tr>
</tbody>
</table>
<p
class=
"rubric"
>
Examples
</p>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"n"
>
data
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
fluid
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
layers
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
fill_constant
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
shape
</span><span
class=
"o"
>
=
</span><span
class=
"p"
>
[
</span><span
class=
"mi"
>
1
</span><span
class=
"p"
>
],
</span>
<span
class=
"n"
>
value
</span><span
class=
"o"
>
=
</span><span
class=
"mi"
>
0
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
dtype
</span><span
class=
"o"
>
=
</span><span
class=
"s1"
>
'
int64
'
</span><span
class=
"p"
>
)
</span>
</pre></div>
</div>
</dd></dl>
</div>
</div>
<div
class=
"section"
id=
"ones"
>
<div
class=
"section"
id=
"ones"
>
...
...
develop/doc/searchindex.js
浏览文件 @
e1b45851
因为 它太大了无法显示 source diff 。你可以改为
查看blob
。
develop/doc_cn/api/v2/fluid/layers.html
浏览文件 @
e1b45851
...
@@ -969,9 +969,34 @@ LOD_Tensor.</p>
...
@@ -969,9 +969,34 @@ LOD_Tensor.</p>
<dl
class=
"function"
>
<dl
class=
"function"
>
<dt>
<dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant
</code><span
class=
"sig-paren"
>
(
</span><em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
out=None
</em><span
class=
"sig-paren"
>
)
</span></dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant
</code><span
class=
"sig-paren"
>
(
</span><em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
out=None
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd><p>
This function creates a tensor , with shape as mentioned in the input and
<dd><p><strong>
fill_constant
</strong></p>
specified dtype and fills this up with a constant value that
<p>
This function creates a tensor of specified
<em>
shape
</em>
and
comes in the input. It also sets the stop_gradient to be True.
</p>
<em>
dtype
</em>
, and initializes this with a constant supplied in
<em>
value
</em>
.
</p>
<p>
It also sets
<em>
stop_gradient
</em>
to True.
</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>
shape
</strong>
(
<em>
tuple|list|None
</em>
)
–
Shape of output tensor
</li>
<li><strong>
dtype
</strong>
(
<em>
np.dtype|core.DataType|str
</em>
)
–
Data type of output tensor
</li>
<li><strong>
value
</strong>
(
<em>
float
</em>
)
–
Constant value to initialize the output tensor
</li>
<li><strong>
out
</strong>
(
<em>
Variable
</em>
)
–
Output Variable to initialize
</li>
</ul>
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
返回:
</th><td
class=
"field-body"
><p
class=
"first"
>
The tensor variable storing the output
</p>
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
返回类型:
</th><td
class=
"field-body"
><p
class=
"first last"
>
Variable
</p>
</td>
</tr>
</tbody>
</table>
<p
class=
"rubric"
>
Examples
</p>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"n"
>
data
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
fluid
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
layers
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
fill_constant
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
shape
</span><span
class=
"o"
>
=
</span><span
class=
"p"
>
[
</span><span
class=
"mi"
>
1
</span><span
class=
"p"
>
],
</span>
<span
class=
"n"
>
value
</span><span
class=
"o"
>
=
</span><span
class=
"mi"
>
0
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
dtype
</span><span
class=
"o"
>
=
</span><span
class=
"s1"
>
'
int64
'
</span><span
class=
"p"
>
)
</span>
</pre></div>
</div>
</dd></dl>
</dd></dl>
</div>
</div>
...
@@ -980,7 +1005,38 @@ comes in the input. It also sets the stop_gradient to be True.</p>
...
@@ -980,7 +1005,38 @@ comes in the input. It also sets the stop_gradient to be True.</p>
<dl
class=
"function"
>
<dl
class=
"function"
>
<dt>
<dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant_batch_size_like
</code><span
class=
"sig-paren"
>
(
</span><em>
input
</em>
,
<em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
input_dim_idx=0
</em>
,
<em>
output_dim_idx=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<code
class=
"descclassname"
>
paddle.v2.fluid.layers.
</code><code
class=
"descname"
>
fill_constant_batch_size_like
</code><span
class=
"sig-paren"
>
(
</span><em>
input
</em>
,
<em>
shape
</em>
,
<em>
dtype
</em>
,
<em>
value
</em>
,
<em>
input_dim_idx=0
</em>
,
<em>
output_dim_idx=0
</em><span
class=
"sig-paren"
>
)
</span></dt>
<dd></dd></dl>
<dd><p><strong>
fill_constant_batch_size_like
</strong></p>
<p>
This function creates a tensor of specified
<em>
shape
</em>
,
<em>
dtype
</em>
and batch size,
and initializes this with a constant supplied in
<em>
value
</em>
. The batch size is
obtained from the
<cite>
input
</cite>
tensor.
</p>
<p>
It also sets
<em>
stop_gradient
</em>
to True.
</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>
input
</strong>
(
<em>
Variable
</em>
)
–
Tensor whose dimensions will be used to get batch size
</li>
<li><strong>
shape
</strong>
(
<em>
tuple|list|None
</em>
)
–
Shape of output tensor
</li>
<li><strong>
dtype
</strong>
(
<em>
np.dtype|core.DataType|str
</em>
)
–
Data type of output tensor
</li>
<li><strong>
value
</strong>
(
<em>
float
</em>
)
–
Constant value to initialize the output tensor
</li>
<li><strong>
input_dim_idx
</strong>
(
<em>
int
</em>
)
–
Index of input
’
s batch size dimension
</li>
<li><strong>
output_dim_idx
</strong>
(
<em>
int
</em>
)
–
Index of output
’
s batch size dimension
</li>
</ul>
</td>
</tr>
<tr
class=
"field-even field"
><th
class=
"field-name"
>
返回:
</th><td
class=
"field-body"
><p
class=
"first"
>
The tensor variable storing the output
</p>
</td>
</tr>
<tr
class=
"field-odd field"
><th
class=
"field-name"
>
返回类型:
</th><td
class=
"field-body"
><p
class=
"first last"
>
Variable
</p>
</td>
</tr>
</tbody>
</table>
<p
class=
"rubric"
>
Examples
</p>
<div
class=
"highlight-python"
><div
class=
"highlight"
><pre><span></span><span
class=
"n"
>
data
</span>
<span
class=
"o"
>
=
</span>
<span
class=
"n"
>
fluid
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
layers
</span><span
class=
"o"
>
.
</span><span
class=
"n"
>
fill_constant
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
shape
</span><span
class=
"o"
>
=
</span><span
class=
"p"
>
[
</span><span
class=
"mi"
>
1
</span><span
class=
"p"
>
],
</span>
<span
class=
"n"
>
value
</span><span
class=
"o"
>
=
</span><span
class=
"mi"
>
0
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
dtype
</span><span
class=
"o"
>
=
</span><span
class=
"s1"
>
'
int64
'
</span><span
class=
"p"
>
)
</span>
</pre></div>
</div>
</dd></dl>
</div>
</div>
<div
class=
"section"
id=
"ones"
>
<div
class=
"section"
id=
"ones"
>
...
...
develop/doc_cn/searchindex.js
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