You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@singa.apache.org by wa...@apache.org on 2019/04/21 13:56:45 UTC
svn commit: r1857911 [11/27] - in /incubator/singa/site/trunk: en/
en/_static/ en/_static/css/ en/_static/fonts/ en/_static/fonts/Lato/
en/_static/fonts/RobotoSlab/ en/_static/js/ en/community/ en/develop/
en/docs/ en/docs/model_zoo/ en/docs/model_zoo/...
Modified: incubator/singa/site/trunk/en/docs/model_zoo/mnist/README.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/model_zoo/mnist/README.html?rev=1857911&r1=1857910&r2=1857911&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/model_zoo/mnist/README.html (original)
+++ incubator/singa/site/trunk/en/docs/model_zoo/mnist/README.html Sun Apr 21 13:56:42 2019
@@ -18,15 +18,21 @@
-
-
+ <script type="text/javascript" src="../../../_static/js/modernizr.min.js"></script>
+ <script type="text/javascript" id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
+ <script type="text/javascript" src="../../../_static/jquery.js"></script>
+ <script type="text/javascript" src="../../../_static/underscore.js"></script>
+ <script type="text/javascript" src="../../../_static/doctools.js"></script>
+ <script type="text/javascript" src="../../../_static/language_data.js"></script>
+
+ <script type="text/javascript" src="../../../_static/js/theme.js"></script>
-
+
- <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
+ <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<link rel="index" title="Index" href="../../../genindex.html" />
<link rel="search" title="Search" href="../../../search.html" />
@@ -44,21 +50,16 @@
}
</style>
-
-
- <script src="../../../_static/js/modernizr.min.js"></script>
-
</head>
<body class="wy-body-for-nav">
<div class="wy-grid-for-nav">
-
<nav data-toggle="wy-nav-shift" class="wy-nav-side">
<div class="wy-side-scroll">
- <div class="wy-side-nav-search">
+ <div class="wy-side-nav-search" >
@@ -125,15 +126,35 @@
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="../imagenet/alexnet/README.html">Train AlexNet over ImageNet</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../imagenet/densenet/README.html">â></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../imagenet/densenet/README.html">name: DenseNet models on ImageNet
+SINGA version: 1.1.1
+SINGA commit:
+license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py</a></li>
<li class="toctree-l3"><a class="reference internal" href="../imagenet/densenet/README.html#image-classification-using-densenet">Image Classification using DenseNet</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../imagenet/googlenet/README.html">â></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../imagenet/googlenet/README.html">name: GoogleNet on ImageNet
+SINGA version: 1.0.1
+SINGA commit: 8c990f7da2de220e8a012c6a8ecc897dc7532744
+parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz
+parameter_sha1: 0a88e8948b1abca3badfd8d090d6be03f8d7655d
+license: unrestricted https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet</a></li>
<li class="toctree-l3"><a class="reference internal" href="../imagenet/googlenet/README.html#image-classification-using-googlenet">Image Classification using GoogleNet</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../imagenet/inception/README.html">â></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../imagenet/inception/README.html">name: Inception V4 on ImageNet
+SINGA version: 1.1.1
+SINGA commit:
+parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz
+parameter_sha1: 5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56
+license: https://github.com/tensorflow/models/tree/master/slim</a></li>
<li class="toctree-l3"><a class="reference internal" href="../imagenet/inception/README.html#image-classification-using-inception-v4">Image Classification using Inception V4</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../imagenet/resnet/README.html">â></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../imagenet/resnet/README.html">name: Resnets on ImageNet
+SINGA version: 1.1
+SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f
+parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz
+license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE</a></li>
<li class="toctree-l3"><a class="reference internal" href="../imagenet/resnet/README.html#image-classification-using-residual-networks">Image Classification using Residual Networks</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../imagenet/vgg/README.html">â></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../imagenet/vgg/README.html">name: VGG models on ImageNet
+SINGA version: 1.1.1
+SINGA commit:
+license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py</a></li>
<li class="toctree-l3"><a class="reference internal" href="../imagenet/vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a></li>
</ul>
</li>
@@ -230,28 +251,26 @@
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
- with the License. You may obtain a copy of the License at<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">http</span><span class="p">:</span><span class="o">//</span><span class="n">www</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">org</span><span class="o">/</span><span class="n">licenses</span><span class="o">/</span><span class="n">LICENSE</span><span class="o">-</span><span class="mf">2.0</span>
+ with the License. You may obtain a copy of the License at
-<span class="n">Unless</span> <span class="n">required</span> <span class="n">by</span> <span class="n">applicable</span> <span class="n">law</span> <span class="ow">or</span> <span class="n">agreed</span> <span class="n">to</span> <span class="ow">in</span> <span class="n">writing</span><span class="p">,</span>
-<span class="n">software</span> <span class="n">distributed</span> <span class="n">under</span> <span class="n">the</span> <span class="n">License</span> <span class="ow">is</span> <span class="n">distributed</span> <span class="n">on</span> <span class="n">an</span>
-<span class="s2">"AS IS"</span> <span class="n">BASIS</span><span class="p">,</span> <span class="n">WITHOUT</span> <span class="n">WARRANTIES</span> <span class="n">OR</span> <span class="n">CONDITIONS</span> <span class="n">OF</span> <span class="n">ANY</span>
-<span class="n">KIND</span><span class="p">,</span> <span class="n">either</span> <span class="n">express</span> <span class="ow">or</span> <span class="n">implied</span><span class="o">.</span> <span class="n">See</span> <span class="n">the</span> <span class="n">License</span> <span class="k">for</span> <span class="n">the</span>
-<span class="n">specific</span> <span class="n">language</span> <span class="n">governing</span> <span class="n">permissions</span> <span class="ow">and</span> <span class="n">limitations</span>
-<span class="n">under</span> <span class="n">the</span> <span class="n">License</span><span class="o">.</span>
-</pre></div>
-</div>
-<p>â></p>
-<div class="section" id="train-a-rbm-model-against-mnist-dataset">
-<span id="train-a-rbm-model-against-mnist-dataset"></span><h1>Train a RBM model against MNIST dataset<a class="headerlink" href="#train-a-rbm-model-against-mnist-dataset" title="Permalink to this headline">¶</a></h1>
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+--><div class="section" id="train-a-rbm-model-against-mnist-dataset">
+<h1>Train a RBM model against MNIST dataset<a class="headerlink" href="#train-a-rbm-model-against-mnist-dataset" title="Permalink to this headline">¶</a></h1>
<p>This example is to train an RBM model using the
MNIST dataset. The RBM model and its hyper-parameters are set following
-<a class="reference external" href="http://www.cs.toronto.edu/~hinton/science.pdf">Hintonâs paper</a></p>
+<a class="reference external" href="http://www.cs.toronto.edu/%7Ehinton/science.pdf">Hintonâs paper</a></p>
<div class="section" id="running-instructions">
-<span id="running-instructions"></span><h2>Running instructions<a class="headerlink" href="#running-instructions" title="Permalink to this headline">¶</a></h2>
+<h2>Running instructions<a class="headerlink" href="#running-instructions" title="Permalink to this headline">¶</a></h2>
<ol>
-<li><p class="first">Download the pre-processed <a class="reference external" href="https://github.com/mnielsen/neural-networks-and-deep-learning/raw/master/data/mnist.pkl.gz">MNIST dataset</a></p>
-</li>
-<li><p class="first">Start the training</p>
+<li><p>Download the pre-processed <a class="reference external" href="https://github.com/mnielsen/neural-networks-and-deep-learning/raw/master/data/mnist.pkl.gz">MNIST dataset</a></p></li>
+<li><p>Start the training</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">python</span> <span class="n">train</span><span class="o">.</span><span class="n">py</span> <span class="n">mnist</span><span class="o">.</span><span class="n">pkl</span><span class="o">.</span><span class="n">gz</span>
</pre></div>
</div>
@@ -276,7 +295,7 @@ the program with an additional argument<
<a href="../imagenet/alexnet/README.html" class="btn btn-neutral float-right" title="Train AlexNet over ImageNet" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a>
- <a href="../char-rnn/README.html" class="btn btn-neutral" title="Train Char-RNN over plain text" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a>
+ <a href="../char-rnn/README.html" class="btn btn-neutral float-left" title="Train Char-RNN over plain text" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a>
</div>
@@ -285,7 +304,7 @@ the program with an additional argument<
<div role="contentinfo">
<p>
- © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners..
+ © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners.
</p>
</div>
@@ -302,36 +321,17 @@ the program with an additional argument<
-
-
- <script type="text/javascript">
- var DOCUMENTATION_OPTIONS = {
- URL_ROOT:'../../../',
- VERSION:'1.1.0',
- LANGUAGE:'None',
- COLLAPSE_INDEX:false,
- FILE_SUFFIX:'.html',
- HAS_SOURCE: true,
- SOURCELINK_SUFFIX: '.txt'
- };
- </script>
- <script type="text/javascript" src="../../../_static/jquery.js"></script>
- <script type="text/javascript" src="../../../_static/underscore.js"></script>
- <script type="text/javascript" src="../../../_static/doctools.js"></script>
-
-
-
-
-
- <script type="text/javascript" src="../../../_static/js/theme.js"></script>
-
-
<script type="text/javascript">
jQuery(function () {
SphinxRtdTheme.Navigation.enable(true);
});
</script>
+
+
+
+
+
<div class="rst-versions" data-toggle="rst-versions" role="note" aria-label="versions">
<span class="rst-current-version" data-toggle="rst-current-version">
<span class="fa fa-book"> incubator-singa </span>
Modified: incubator/singa/site/trunk/en/docs/net.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/net.html?rev=1857911&r1=1857910&r2=1857911&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/net.html (original)
+++ incubator/singa/site/trunk/en/docs/net.html Sun Apr 21 13:56:42 2019
@@ -18,15 +18,21 @@
-
-
+ <script type="text/javascript" src="../_static/js/modernizr.min.js"></script>
+ <script type="text/javascript" id="documentation_options" data-url_root="../" src="../_static/documentation_options.js"></script>
+ <script type="text/javascript" src="../_static/jquery.js"></script>
+ <script type="text/javascript" src="../_static/underscore.js"></script>
+ <script type="text/javascript" src="../_static/doctools.js"></script>
+ <script type="text/javascript" src="../_static/language_data.js"></script>
+
+ <script type="text/javascript" src="../_static/js/theme.js"></script>
-
+
- <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
+ <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
<link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
<link rel="index" title="Index" href="../genindex.html" />
<link rel="search" title="Search" href="../search.html" />
@@ -44,21 +50,16 @@
}
</style>
-
-
- <script src="../_static/js/modernizr.min.js"></script>
-
</head>
<body class="wy-body-for-nav">
<div class="wy-grid-for-nav">
-
<nav data-toggle="wy-nav-shift" class="wy-nav-side">
<div class="wy-side-scroll">
- <div class="wy-side-nav-search">
+ <div class="wy-side-nav-search" >
@@ -261,18 +262,14 @@ newly added layer. For the first layer,
function should ensure the correctness of the layer order. If src is
None, the last layer is the src layer. If there are multiple src layers,
the src is a list of the src layers.</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 last simple">
-<li><strong>lyr</strong> (<a class="reference internal" href="layer.html#singa.layer.Layer" title="singa.layer.Layer"><em>Layer</em></a>) â the layer to be added</li>
-<li><strong>src</strong> (<a class="reference internal" href="layer.html#singa.layer.Layer" title="singa.layer.Layer"><em>Layer</em></a>) â the source layer of lyr</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>lyr</strong> (<a class="reference internal" href="layer.html#singa.layer.Layer" title="singa.layer.Layer"><em>Layer</em></a>) â the layer to be added</p></li>
+<li><p><strong>src</strong> (<a class="reference internal" href="layer.html#singa.layer.Layer" title="singa.layer.Layer"><em>Layer</em></a>) â the source layer of lyr</p></li>
+</ul>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
@@ -312,21 +309,17 @@ loss objective and metric.
For multiple outputs (with multiple loss/metric), please manually
call forward, compute loss/metric and call backward. backward() is also
more memory efficient than this function.</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>x</strong> â input data, a single input Tensor or a dict: layer name -> Tensor</li>
-<li><strong>y</strong> â label data, a single input Tensor.</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">gradients of parameters and the loss and metric values.</p>
-</td>
-</tr>
-</tbody>
-</table>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>x</strong> â input data, a single input Tensor or a dict: layer name -> Tensor</p></li>
+<li><p><strong>y</strong> â label data, a single input Tensor.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p>gradients of parameters and the loss and metric values.</p>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
@@ -336,18 +329,14 @@ more memory efficient than this function
<p>Currently only support nets with a single output layer, and a single
loss objective and metric.
TODO(wangwei) consider multiple loss objectives and metrics.</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 last simple">
-<li><strong>x</strong> â input data, a single input Tensor or a dict: layer name -> Tensor</li>
-<li><strong>y</strong> â label data, a single input Tensor.</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>x</strong> â input data, a single input Tensor or a dict: layer name -> Tensor</p></li>
+<li><p><strong>y</strong> â label data, a single input Tensor.</p></li>
+</ul>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
@@ -356,16 +345,14 @@ TODO(wangwei) consider multiple loss obj
<dd><p>Forward the input data through each layer to get the values of the
output layers.</p>
<p>Currently only support nets with a single output layer</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>x</strong> â input data, a single input Tensor or a dict: layer name -> Tensor</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">a single output tensor as the prediction result.</td>
-</tr>
-</tbody>
-</table>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><p><strong>x</strong> â input data, a single input Tensor or a dict: layer name -> Tensor</p>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p>a single output tensor as the prediction result.</p>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
@@ -373,116 +360,99 @@ output layers.</p>
<code class="descname">topo_sort</code><span class="sig-paren">(</span><em>layers</em>, <em>src_of_layer</em><span class="sig-paren">)</span><a class="headerlink" href="#singa.net.FeedForwardNet.topo_sort" title="Permalink to this definition">¶</a></dt>
<dd><p>Topology sort of layers.</p>
<p>It would try to preserve the orders of the input layers.</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>layers</strong> â a list of layers; the layers from the output of the same
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>layers</strong> â a list of layers; the layers from the output of the same
layer (e.g., slice layer) should be added by users in correct
-order; This function would not change their order.</li>
-<li><strong>src_of_layer</strong> â a dictionary: src layer name -> a list of src layers</li>
+order; This function would not change their order.</p></li>
+<li><p><strong>src_of_layer</strong> â a dictionary: src layer name -> a list of src layers</p></li>
</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">A list of ordered layer</p>
-</td>
-</tr>
-</tbody>
-</table>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p>A list of ordered layer</p>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
<dt id="singa.net.FeedForwardNet.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>flag</em>, <em>x</em>, <em>output=[]</em>, <em>freeze=None</em><span class="sig-paren">)</span><a class="headerlink" href="#singa.net.FeedForwardNet.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Forward the input(s) through every layer.</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>flag</strong> â True for training; False for evaluation; could also be
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>flag</strong> â True for training; False for evaluation; could also be
model_pb2.kTrain or model_pb2.kEval, or other values for future
-use.</li>
-<li><strong>x</strong> â a single SINGA tensor if there is a single input; otherwise, a
+use.</p></li>
+<li><p><strong>x</strong> â a single SINGA tensor if there is a single input; otherwise, a
dictionary: layer name-> singa tensor, for each layer accepting
input data. Do not associate a layer with input tensor if it is
connected from another layer. For such case, use a Dummy() layer
to accept the input data and connect the dummy layer to this
-layer.</li>
-<li><strong>output</strong> (<em>list</em>) â a list of layer names whose output would be returned
-in addition to the default output.</li>
-<li><strong>freeze</strong> (<em>str</em>) â layer name, freeze all layers before this layer; flag
-is set to false for these layers.</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><dl class="docutils">
-<dt>if there is only one output layer and output arg is empty, return</dt>
-<dd><p class="first last">the result from the single output layer; otherwise, return a
+layer.</p></li>
+<li><p><strong>output</strong> (<em>list</em>) â a list of layer names whose output would be returned
+in addition to the default output.</p></li>
+<li><p><strong>freeze</strong> (<em>str</em>) â layer name, freeze all layers before this layer; flag
+is set to false for these layers.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p><dl class="simple">
+<dt>if there is only one output layer and output arg is empty, return</dt><dd><p>the result from the single output layer; otherwise, return a
dictionary: layer name -> output tensor(s)</p>
</dd>
</dl>
</p>
-</td>
-</tr>
-</tbody>
-</table>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
<dt id="singa.net.FeedForwardNet.backward">
<code class="descname">backward</code><span class="sig-paren">(</span><em>dy</em>, <em>output=[]</em>, <em>freeze=None</em><span class="sig-paren">)</span><a class="headerlink" href="#singa.net.FeedForwardNet.backward" title="Permalink to this definition">¶</a></dt>
<dd><p>Run back-propagation after forward-propagation.</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>dy</strong> â a single tensor if there is a single loss function; otherwise,
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>dy</strong> â a single tensor if there is a single loss function; otherwise,
a dictionary maps the name of the layer connecting to the loss
function -> gradient from the loss function. Do not associate a
layer with gradient tensor if it is connecting to another layer.
For such case, connect this layer to a Dummy() layer and use the
-dummy layer to accept the gradient.</li>
-<li><strong>output</strong> (<em>list</em>) â a list of layer names whose output gradient would be
-returned in addition to the param gradient</li>
-<li><strong>freeze</strong> (<em>str</em>) â layer name, stop backward after this layer.</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a geneartor iterator that generates
+dummy layer to accept the gradient.</p></li>
+<li><p><strong>output</strong> (<em>list</em>) â a list of layer names whose output gradient would be
+returned in addition to the param gradient</p></li>
+<li><p><strong>freeze</strong> (<em>str</em>) â layer name, stop backward after this layer.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p>a geneartor iterator that generates
(param_names, param_values, param_grads, layer_grads) after
processing each layer h, where the first three lists are for h
and the last item is a dictionary which maps
layer name -> its output gradient tensor(s). At the end of this
function, the key set includes all layers in the output arg.</p>
-</td>
-</tr>
-</tbody>
-</table>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
<dt id="singa.net.FeedForwardNet.save">
<code class="descname">save</code><span class="sig-paren">(</span><em>f</em>, <em>buffer_size=10</em>, <em>use_pickle=False</em><span class="sig-paren">)</span><a class="headerlink" href="#singa.net.FeedForwardNet.save" title="Permalink to this definition">¶</a></dt>
<dd><p>Save model parameters using io/snapshot.</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 last simple">
-<li><strong>f</strong> â file name</li>
-<li><strong>buffer_size</strong> â size (MB) of the IO, default setting is 10MB; Please
-make sure it is larger than any single parameter object.</li>
-<li><strong>use_pickle</strong> (<em>Boolean</em>) â if true, it would use pickle for dumping;
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>f</strong> â file name</p></li>
+<li><p><strong>buffer_size</strong> â size (MB) of the IO, default setting is 10MB; Please
+make sure it is larger than any single parameter object.</p></li>
+<li><p><strong>use_pickle</strong> (<em>Boolean</em>) â if true, it would use pickle for dumping;
otherwise, it would use protobuf for serialization, which uses
-less space.</li>
+less space.</p></li>
</ul>
-</td>
-</tr>
-</tbody>
-</table>
+</dd>
+</dl>
</dd></dl>
<dl class="method">
@@ -507,7 +477,7 @@ less space.</li>
<a href="initializer.html" class="btn btn-neutral float-right" title="Initializer" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a>
- <a href="layer.html" class="btn btn-neutral" title="Layer" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a>
+ <a href="layer.html" class="btn btn-neutral float-left" title="Layer" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a>
</div>
@@ -516,7 +486,7 @@ less space.</li>
<div role="contentinfo">
<p>
- © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners..
+ © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners.
</p>
</div>
@@ -533,36 +503,17 @@ less space.</li>
-
-
- <script type="text/javascript">
- var DOCUMENTATION_OPTIONS = {
- URL_ROOT:'../',
- VERSION:'1.1.0',
- LANGUAGE:'None',
- COLLAPSE_INDEX:false,
- FILE_SUFFIX:'.html',
- HAS_SOURCE: true,
- SOURCELINK_SUFFIX: '.txt'
- };
- </script>
- <script type="text/javascript" src="../_static/jquery.js"></script>
- <script type="text/javascript" src="../_static/underscore.js"></script>
- <script type="text/javascript" src="../_static/doctools.js"></script>
-
-
-
-
-
- <script type="text/javascript" src="../_static/js/theme.js"></script>
-
-
<script type="text/javascript">
jQuery(function () {
SphinxRtdTheme.Navigation.enable(true);
});
</script>
+
+
+
+
+
<div class="rst-versions" data-toggle="rst-versions" role="note" aria-label="versions">
<span class="rst-current-version" data-toggle="rst-current-version">
<span class="fa fa-book"> incubator-singa </span>
Modified: incubator/singa/site/trunk/en/docs/neural-net.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/neural-net.html?rev=1857911&r1=1857910&r2=1857911&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/neural-net.html (original)
+++ incubator/singa/site/trunk/en/docs/neural-net.html Sun Apr 21 13:56:42 2019
@@ -18,15 +18,21 @@
-
-
+ <script type="text/javascript" src="../_static/js/modernizr.min.js"></script>
+ <script type="text/javascript" id="documentation_options" data-url_root="../" src="../_static/documentation_options.js"></script>
+ <script type="text/javascript" src="../_static/jquery.js"></script>
+ <script type="text/javascript" src="../_static/underscore.js"></script>
+ <script type="text/javascript" src="../_static/doctools.js"></script>
+ <script type="text/javascript" src="../_static/language_data.js"></script>
+
+ <script type="text/javascript" src="../_static/js/theme.js"></script>
-
+
- <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
+ <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
<link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
<link rel="index" title="Index" href="../genindex.html" />
<link rel="search" title="Search" href="../search.html" />
@@ -42,21 +48,16 @@
}
</style>
-
-
- <script src="../_static/js/modernizr.min.js"></script>
-
</head>
<body class="wy-body-for-nav">
<div class="wy-grid-for-nav">
-
<nav data-toggle="wy-nav-shift" class="wy-nav-side">
<div class="wy-side-scroll">
- <div class="wy-side-nav-search">
+ <div class="wy-side-nav-search" >
@@ -185,34 +186,32 @@
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
- with the License. You may obtain a copy of the License at<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">http</span><span class="p">:</span><span class="o">//</span><span class="n">www</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">org</span><span class="o">/</span><span class="n">licenses</span><span class="o">/</span><span class="n">LICENSE</span><span class="o">-</span><span class="mf">2.0</span>
+ with the License. You may obtain a copy of the License at
-<span class="n">Unless</span> <span class="n">required</span> <span class="n">by</span> <span class="n">applicable</span> <span class="n">law</span> <span class="ow">or</span> <span class="n">agreed</span> <span class="n">to</span> <span class="ow">in</span> <span class="n">writing</span><span class="p">,</span>
-<span class="n">software</span> <span class="n">distributed</span> <span class="n">under</span> <span class="n">the</span> <span class="n">License</span> <span class="ow">is</span> <span class="n">distributed</span> <span class="n">on</span> <span class="n">an</span>
-<span class="s2">"AS IS"</span> <span class="n">BASIS</span><span class="p">,</span> <span class="n">WITHOUT</span> <span class="n">WARRANTIES</span> <span class="n">OR</span> <span class="n">CONDITIONS</span> <span class="n">OF</span> <span class="n">ANY</span>
-<span class="n">KIND</span><span class="p">,</span> <span class="n">either</span> <span class="n">express</span> <span class="ow">or</span> <span class="n">implied</span><span class="o">.</span> <span class="n">See</span> <span class="n">the</span> <span class="n">License</span> <span class="k">for</span> <span class="n">the</span>
-<span class="n">specific</span> <span class="n">language</span> <span class="n">governing</span> <span class="n">permissions</span> <span class="ow">and</span> <span class="n">limitations</span>
-<span class="n">under</span> <span class="n">the</span> <span class="n">License</span><span class="o">.</span>
-</pre></div>
-</div>
-<p>â></p>
-<div class="section" id="neural-net">
-<span id="neural-net"></span><h1>Neural Net<a class="headerlink" href="#neural-net" title="Permalink to this headline">¶</a></h1>
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+--><div class="section" id="neural-net">
+<h1>Neural Net<a class="headerlink" href="#neural-net" title="Permalink to this headline">¶</a></h1>
<p><code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> in SINGA represents an instance of userâs neural net model. As the
neural net typically consists of a set of layers, <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> comprises
a set of unidirectionally connected <a class="reference external" href="layer.html">Layer</a>s.
This page describes how to convert an userâs neural net into
the configuration of <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code>.</p>
-<p><img src="../_static/images/model-category.png" align="center" width="200px"/>
-<span><strong>Figure 1 - Categorization of popular deep learning models.</strong></span></p>
-<div class="section" id="net-structure-configuration">
-<span id="net-structure-configuration"></span><h2>Net structure configuration<a class="headerlink" href="#net-structure-configuration" title="Permalink to this headline">¶</a></h2>
+<img src="../_static/images/model-category.png" align="center" width="200px"/>
+<span><strong>Figure 1 - Categorization of popular deep learning models.</strong></span><div class="section" id="net-structure-configuration">
+<h2>Net structure configuration<a class="headerlink" href="#net-structure-configuration" title="Permalink to this headline">¶</a></h2>
<p>Users configure the <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> by listing all layers of the neural net and
specifying each layerâs source layer names. Popular deep learning models can be
categorized as Figure 1. The subsequent sections give details for each
category.</p>
<div class="section" id="feed-forward-models">
-<span id="feed-forward-models"></span><h3>Feed-forward models<a class="headerlink" href="#feed-forward-models" title="Permalink to this headline">¶</a></h3>
+<h3>Feed-forward models<a class="headerlink" href="#feed-forward-models" title="Permalink to this headline">¶</a></h3>
<div align = "left">
<img src="../_static/images/mlp-net.png" align="center" width="200px"/>
<span><strong>Figure 2 - Net structure of a MLP model.</strong></span>
@@ -250,10 +249,9 @@ configuration for the MLP model shown in
</div>
</div>
<div class="section" id="energy-models">
-<span id="energy-models"></span><h3>Energy models<a class="headerlink" href="#energy-models" title="Permalink to this headline">¶</a></h3>
-<p><img src="../_static/images/rbm-rnn.png" align="center" width="500px"/>
-<span><strong>Figure 3 - Convert connections in RBM and RNN.</strong></span></p>
-<p>For energy models including RBM, DBM,
+<h3>Energy models<a class="headerlink" href="#energy-models" title="Permalink to this headline">¶</a></h3>
+<img src="../_static/images/rbm-rnn.png" align="center" width="500px"/>
+<span><strong>Figure 3 - Convert connections in RBM and RNN.</strong></span><p>For energy models including RBM, DBM,
etc., their connections are undirected (i.e., Category B). To represent these models using
<code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code>, users can simply replace each connection with two directed
connections, as shown in Figure 3a. In other words, for each pair of connected layers, their source
@@ -283,7 +281,7 @@ detailed neural net configuration for a
</div>
</div>
<div class="section" id="rnn-models">
-<span id="rnn-models"></span><h3>RNN models<a class="headerlink" href="#rnn-models" title="Permalink to this headline">¶</a></h3>
+<h3>RNN models<a class="headerlink" href="#rnn-models" title="Permalink to this headline">¶</a></h3>
<p>For recurrent neural networks (RNN), users can remove the recurrent connections
by unrolling the recurrent layer. For example, in Figure 3b, the original
layer is unrolled into a new layer with 4 internal layers. In this way, the
@@ -293,7 +291,7 @@ configuration for a RNN model.</p>
</div>
</div>
<div class="section" id="configuration-for-multiple-nets">
-<span id="configuration-for-multiple-nets"></span><h2>Configuration for multiple nets<a class="headerlink" href="#configuration-for-multiple-nets" title="Permalink to this headline">¶</a></h2>
+<h2>Configuration for multiple nets<a class="headerlink" href="#configuration-for-multiple-nets" title="Permalink to this headline">¶</a></h2>
<p>Typically, a training job includes three neural nets for
training, validation and test phase respectively. The three neural nets share most
layers except the data layer, loss layer or output layer, etc.. To avoid
@@ -308,14 +306,13 @@ filtered when creating the testing <code
</div>
</div>
<div class="section" id="neural-net-partitioning">
-<span id="neural-net-partitioning"></span><h2>Neural net partitioning<a class="headerlink" href="#neural-net-partitioning" title="Permalink to this headline">¶</a></h2>
+<h2>Neural net partitioning<a class="headerlink" href="#neural-net-partitioning" title="Permalink to this headline">¶</a></h2>
<p>A neural net can be partitioned in different ways to distribute the training
over multiple workers.</p>
<div class="section" id="batch-and-feature-dimension">
-<span id="batch-and-feature-dimension"></span><h3>Batch and feature dimension<a class="headerlink" href="#batch-and-feature-dimension" title="Permalink to this headline">¶</a></h3>
-<p><img src="../_static/images/partition_fc.png" align="center" width="400px"/>
-<span><strong>Figure 4 - Partitioning of a fully connected layer.</strong></span></p>
-<p>Every layerâs feature blob is considered a matrix whose rows are feature
+<h3>Batch and feature dimension<a class="headerlink" href="#batch-and-feature-dimension" title="Permalink to this headline">¶</a></h3>
+<img src="../_static/images/partition_fc.png" align="center" width="400px"/>
+<span><strong>Figure 4 - Partitioning of a fully connected layer.</strong></span><p>Every layerâs feature blob is considered a matrix whose rows are feature
vectors. Thus, one layer can be split on two dimensions. Partitioning on
dimension 0 (also called batch dimension) slices the feature matrix by rows.
For instance, if the mini-batch size is 256 and the layer is partitioned into 2
@@ -330,10 +327,10 @@ Figure 4. Both the bias vector and weigh
partitioned into two sub-layers.</p>
</div>
<div class="section" id="partitioning-configuration">
-<span id="partitioning-configuration"></span><h3>Partitioning configuration<a class="headerlink" href="#partitioning-configuration" title="Permalink to this headline">¶</a></h3>
+<h3>Partitioning configuration<a class="headerlink" href="#partitioning-configuration" title="Permalink to this headline">¶</a></h3>
<p>There are 4 partitioning schemes, whose configurations are give below,</p>
<ol>
-<li><p class="first">Partitioning each singe layer into sub-layers on batch dimension (see
+<li><p>Partitioning each singe layer into sub-layers on batch dimension (see
below). It is enabled by configuring the partition dimension of the layer to
0, e.g.,</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="c1"># with other fields omitted</span>
@@ -343,7 +340,7 @@ below). It is enabled by configuring the
</pre></div>
</div>
</li>
-<li><p class="first">Partitioning each singe layer into sub-layers on feature dimension (see
+<li><p>Partitioning each singe layer into sub-layers on feature dimension (see
below). It is enabled by configuring the partition dimension of the layer to
1, e.g.,</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="c1"># with other fields omitted</span>
@@ -353,7 +350,7 @@ below). It is enabled by configuring th
</pre></div>
</div>
</li>
-<li><p class="first">Partitioning all layers into different subsets. It is enabled by
+<li><p>Partitioning all layers into different subsets. It is enabled by
configuring the location ID of a layer, e.g.,</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="c1"># with other fields omitted</span>
<span class="n">layer</span> <span class="p">{</span>
@@ -365,9 +362,7 @@ configuring the location ID of a layer,
</pre></div>
</div>
</li>
-</ol>
-<ol>
-<li><p class="first">Hybrid partitioning of strategy 1, 2 and 3. The hybrid partitioning is
+<li><p>Hybrid partitioning of strategy 1, 2 and 3. The hybrid partitioning is
useful for large models. An example application is to implement the
<a class="reference external" href="http://arxiv.org/abs/1404.5997">idea proposed by Alex</a>.
Hybrid partitioning is configured like,</p>
@@ -395,19 +390,19 @@ are under test and will be released in l
</div>
</div>
<div class="section" id="parameter-sharing">
-<span id="parameter-sharing"></span><h2>Parameter sharing<a class="headerlink" href="#parameter-sharing" title="Permalink to this headline">¶</a></h2>
+<h2>Parameter sharing<a class="headerlink" href="#parameter-sharing" title="Permalink to this headline">¶</a></h2>
<p>Parameters can be shared in two cases,</p>
<ul class="simple">
-<li>sharing parameters among layers via user configuration. For example, the
+<li><p>sharing parameters among layers via user configuration. For example, the
visible layer and hidden layer of a RBM shares the weight matrix, which is configured through
the <code class="docutils literal notranslate"><span class="pre">share_from</span></code> field as shown in the above RBM configuration. The
-configurations must be the same (except name) for shared parameters.</li>
-<li>due to neural net partitioning, some <code class="docutils literal notranslate"><span class="pre">Param</span></code> objects are replicated into
+configurations must be the same (except name) for shared parameters.</p></li>
+<li><p>due to neural net partitioning, some <code class="docutils literal notranslate"><span class="pre">Param</span></code> objects are replicated into
different workers, e.g., partitioning one layer on batch dimension. These
workers share parameter values. SINGA controls this kind of parameter
-sharing automatically, users do not need to do any configuration.</li>
-<li>the <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> for training and testing (and validation) share most layers
-, thus share <code class="docutils literal notranslate"><span class="pre">Param</span></code> values.</li>
+sharing automatically, users do not need to do any configuration.</p></li>
+<li><p>the <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> for training and testing (and validation) share most layers
+, thus share <code class="docutils literal notranslate"><span class="pre">Param</span></code> values.</p></li>
</ul>
<p>If the shared <code class="docutils literal notranslate"><span class="pre">Param</span></code> instances resident in the same process (may in different
threads), they use the same chunk of memory space for their values. But they
@@ -415,9 +410,9 @@ would have different memory spaces for t
gradients will be averaged by the stub or server.</p>
</div>
<div class="section" id="advanced-user-guide">
-<span id="advanced-user-guide"></span><h2>Advanced user guide<a class="headerlink" href="#advanced-user-guide" title="Permalink to this headline">¶</a></h2>
+<h2>Advanced user guide<a class="headerlink" href="#advanced-user-guide" title="Permalink to this headline">¶</a></h2>
<div class="section" id="creation">
-<span id="creation"></span><h3>Creation<a class="headerlink" href="#creation" title="Permalink to this headline">¶</a></h3>
+<h3>Creation<a class="headerlink" href="#creation" title="Permalink to this headline">¶</a></h3>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">static</span> <span class="n">NeuralNet</span><span class="o">*</span> <span class="n">NeuralNet</span><span class="p">::</span><span class="n">Create</span><span class="p">(</span><span class="n">const</span> <span class="n">NetProto</span><span class="o">&</span> <span class="n">np</span><span class="p">,</span> <span class="n">Phase</span> <span class="n">phase</span><span class="p">,</span> <span class="nb">int</span> <span class="n">num</span><span class="p">);</span>
</pre></div>
</div>
@@ -453,8 +448,8 @@ connected.</p>
<p>Since the <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> instance may be shared among multiple workers, the
<code class="docutils literal notranslate"><span class="pre">Create</span></code> function returns a pointer to the <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> instance .</p>
</div>
-<div class="section" id="parameter-sharing">
-<span id="id1"></span><h3>Parameter sharing<a class="headerlink" href="#parameter-sharing" title="Permalink to this headline">¶</a></h3>
+<div class="section" id="id1">
+<h3>Parameter sharing<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h3>
<p><code class="docutils literal notranslate"><span class="pre">Param</span></code> sharing
is enabled by first sharing the Param configuration (in <code class="docutils literal notranslate"><span class="pre">NeuralNet::Create</span></code>)
to create two similar (e.g., the same shape) Param objects, and then calling
@@ -470,7 +465,7 @@ the training net and the test net,</p>
<p>It will call <code class="docutils literal notranslate"><span class="pre">Param::ShareFrom</span></code> for each Param object.</p>
</div>
<div class="section" id="access-functions">
-<span id="access-functions"></span><h3>Access functions<a class="headerlink" href="#access-functions" title="Permalink to this headline">¶</a></h3>
+<h3>Access functions<a class="headerlink" href="#access-functions" title="Permalink to this headline">¶</a></h3>
<p><code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> provides a couple of access function to get the layers and params
of the net:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">const</span> <span class="n">std</span><span class="p">::</span><span class="n">vector</span><span class="o"><</span><span class="n">Layer</span><span class="o">*>&</span> <span class="n">layers</span><span class="p">()</span> <span class="n">const</span><span class="p">;</span>
@@ -481,9 +476,9 @@ of the net:</p>
</div>
</div>
<div class="section" id="partitioning">
-<span id="partitioning"></span><h3>Partitioning<a class="headerlink" href="#partitioning" title="Permalink to this headline">¶</a></h3>
+<h3>Partitioning<a class="headerlink" href="#partitioning" title="Permalink to this headline">¶</a></h3>
<div class="section" id="implementation">
-<span id="implementation"></span><h4>Implementation<a class="headerlink" href="#implementation" title="Permalink to this headline">¶</a></h4>
+<h4>Implementation<a class="headerlink" href="#implementation" title="Permalink to this headline">¶</a></h4>
<p>SINGA partitions the neural net in <code class="docutils literal notranslate"><span class="pre">CreateGraph</span></code> function, which creates one
node for each (partitioned) layer. For example, if one layerâs partition
dimension is 0 or 1, then it creates <code class="docutils literal notranslate"><span class="pre">npartition</span></code> nodes for it; if the
@@ -501,7 +496,7 @@ inserted. These connection layers help m
synchronization transparent to the users.</p>
</div>
<div class="section" id="dispatching-partitions-to-workers">
-<span id="dispatching-partitions-to-workers"></span><h4>Dispatching partitions to workers<a class="headerlink" href="#dispatching-partitions-to-workers" title="Permalink to this headline">¶</a></h4>
+<h4>Dispatching partitions to workers<a class="headerlink" href="#dispatching-partitions-to-workers" title="Permalink to this headline">¶</a></h4>
<p>Each (partitioned) layer is assigned a location ID, based on which it is dispatched to one
worker. Particularly, the pointer to the <code class="docutils literal notranslate"><span class="pre">NeuralNet</span></code> instance is passed
to every worker within the same group, but each worker only computes over the
@@ -531,7 +526,7 @@ lower layers and <code class="docutils l
<div role="contentinfo">
<p>
- © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners..
+ © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners.
</p>
</div>
@@ -548,36 +543,17 @@ lower layers and <code class="docutils l
-
-
- <script type="text/javascript">
- var DOCUMENTATION_OPTIONS = {
- URL_ROOT:'../',
- VERSION:'1.1.0',
- LANGUAGE:'None',
- COLLAPSE_INDEX:false,
- FILE_SUFFIX:'.html',
- HAS_SOURCE: true,
- SOURCELINK_SUFFIX: '.txt'
- };
- </script>
- <script type="text/javascript" src="../_static/jquery.js"></script>
- <script type="text/javascript" src="../_static/underscore.js"></script>
- <script type="text/javascript" src="../_static/doctools.js"></script>
-
-
-
-
-
- <script type="text/javascript" src="../_static/js/theme.js"></script>
-
-
<script type="text/javascript">
jQuery(function () {
SphinxRtdTheme.Navigation.enable(true);
});
</script>
+
+
+
+
+
<div class="rst-versions" data-toggle="rst-versions" role="note" aria-label="versions">
<span class="rst-current-version" data-toggle="rst-current-version">
<span class="fa fa-book"> incubator-singa </span>
Modified: incubator/singa/site/trunk/en/docs/notebook/README.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/notebook/README.html?rev=1857911&r1=1857910&r2=1857911&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/notebook/README.html (original)
+++ incubator/singa/site/trunk/en/docs/notebook/README.html Sun Apr 21 13:56:42 2019
@@ -18,15 +18,21 @@
-
-
+ <script type="text/javascript" src="../../_static/js/modernizr.min.js"></script>
+ <script type="text/javascript" id="documentation_options" data-url_root="../../" src="../../_static/documentation_options.js"></script>
+ <script type="text/javascript" src="../../_static/jquery.js"></script>
+ <script type="text/javascript" src="../../_static/underscore.js"></script>
+ <script type="text/javascript" src="../../_static/doctools.js"></script>
+ <script type="text/javascript" src="../../_static/language_data.js"></script>
+
+ <script type="text/javascript" src="../../_static/js/theme.js"></script>
-
+
- <link rel="stylesheet" href="../../_static/css/theme.css" type="text/css" />
+ <link rel="stylesheet" href="../../_static/css/theme.css" type="text/css" />
<link rel="stylesheet" href="../../_static/pygments.css" type="text/css" />
<link rel="index" title="Index" href="../../genindex.html" />
<link rel="search" title="Search" href="../../search.html" />
@@ -42,21 +48,16 @@
}
</style>
-
-
- <script src="../../_static/js/modernizr.min.js"></script>
-
</head>
<body class="wy-body-for-nav">
<div class="wy-grid-for-nav">
-
<nav data-toggle="wy-nav-shift" class="wy-nav-side">
<div class="wy-side-scroll">
- <div class="wy-side-nav-search">
+ <div class="wy-side-nav-search" >
@@ -185,18 +186,17 @@
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
- with the License. You may obtain a copy of the License at<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">http</span><span class="p">:</span><span class="o">//</span><span class="n">www</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">org</span><span class="o">/</span><span class="n">licenses</span><span class="o">/</span><span class="n">LICENSE</span><span class="o">-</span><span class="mf">2.0</span>
+ with the License. You may obtain a copy of the License at
-<span class="n">Unless</span> <span class="n">required</span> <span class="n">by</span> <span class="n">applicable</span> <span class="n">law</span> <span class="ow">or</span> <span class="n">agreed</span> <span class="n">to</span> <span class="ow">in</span> <span class="n">writing</span><span class="p">,</span>
-<span class="n">software</span> <span class="n">distributed</span> <span class="n">under</span> <span class="n">the</span> <span class="n">License</span> <span class="ow">is</span> <span class="n">distributed</span> <span class="n">on</span> <span class="n">an</span>
-<span class="s2">"AS IS"</span> <span class="n">BASIS</span><span class="p">,</span> <span class="n">WITHOUT</span> <span class="n">WARRANTIES</span> <span class="n">OR</span> <span class="n">CONDITIONS</span> <span class="n">OF</span> <span class="n">ANY</span>
-<span class="n">KIND</span><span class="p">,</span> <span class="n">either</span> <span class="n">express</span> <span class="ow">or</span> <span class="n">implied</span><span class="o">.</span> <span class="n">See</span> <span class="n">the</span> <span class="n">License</span> <span class="k">for</span> <span class="n">the</span>
-<span class="n">specific</span> <span class="n">language</span> <span class="n">governing</span> <span class="n">permissions</span> <span class="ow">and</span> <span class="n">limitations</span>
-<span class="n">under</span> <span class="n">the</span> <span class="n">License</span><span class="o">.</span>
-</pre></div>
-</div>
-<p>â>
-These are some examples in IPython notebooks.</p>
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+--><p>These are some examples in IPython notebooks.</p>
<p>You can open them in <a class="reference external" href="http://nbviewer.jupyter.org/github/apache/incubator-singa/blob/master/doc/en/docs/notebook/index.ipynb">notebook viewer</a>.</p>
@@ -210,7 +210,7 @@ These are some examples in IPython noteb
<div role="contentinfo">
<p>
- © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners..
+ © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners.
</p>
</div>
@@ -227,36 +227,17 @@ These are some examples in IPython noteb
-
-
- <script type="text/javascript">
- var DOCUMENTATION_OPTIONS = {
- URL_ROOT:'../../',
- VERSION:'1.1.0',
- LANGUAGE:'None',
- COLLAPSE_INDEX:false,
- FILE_SUFFIX:'.html',
- HAS_SOURCE: true,
- SOURCELINK_SUFFIX: '.txt'
- };
- </script>
- <script type="text/javascript" src="../../_static/jquery.js"></script>
- <script type="text/javascript" src="../../_static/underscore.js"></script>
- <script type="text/javascript" src="../../_static/doctools.js"></script>
-
-
-
-
-
- <script type="text/javascript" src="../../_static/js/theme.js"></script>
-
-
<script type="text/javascript">
jQuery(function () {
SphinxRtdTheme.Navigation.enable(true);
});
</script>
+
+
+
+
+
<div class="rst-versions" data-toggle="rst-versions" role="note" aria-label="versions">
<span class="rst-current-version" data-toggle="rst-current-version">
<span class="fa fa-book"> incubator-singa </span>