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Added: incubator/singa/site/trunk/docs/model_zoo/imagenet/resnet/README.html
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--- incubator/singa/site/trunk/docs/model_zoo/imagenet/resnet/README.html (added)
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+SINGA version: 1.1.1
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+<li class="toctree-l3 current"><a class="current reference internal" href="#">name: Resnets on ImageNet
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+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="#image-classification-using-residual-networks">Image Classification using Residual Networks</a><ul>
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+      <li>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
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+<div class="section" id="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">
+<h1>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 class="headerlink" href="#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" title="Permalink to this headline">¶</a></h1>
+</div>
+<div class="section" id="image-classification-using-residual-networks">
+<h1>Image Classification using Residual Networks<a class="headerlink" href="#image-classification-using-residual-networks" title="Permalink to this headline">¶</a></h1>
+<p>In this example, we convert Residual Networks trained on <a class="reference external" href="https://github.com/facebook/fb.resnet.torch">Torch</a> to SINGA for image classification.</p>
+<div class="section" id="instructions">
+<h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2>
+<ul>
+<li><p class="first">Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz
+  $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt
+  $ tar xvf resnet-18.tar.gz
+</pre></div>
+</div>
+</li>
+<li><p class="first">Usage</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  $ python serve.py -h
+</pre></div>
+</div>
+</li>
+<li><p class="first">Example</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  # use cpu
+  $ python serve.py --use_cpu --parameter_file resnet-18.pickle --model resnet --depth 18 &amp;
+  # use gpu
+  $ python serve.py --parameter_file resnet-18.pickle --model resnet --depth 18 &amp;
+</pre></div>
+</div>
+<p>The parameter files for the following model and depth configuration pairs are provided:</p>
+<ul class="simple">
+<li>resnet (original resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz">18</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-34.tar.gz">34</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-101.tar.gz">101</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-152.tar.gz">152</a></li>
+<li>addbn (resnet with a batch normalization layer after the addition), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-50.tar.gz">50</a></li>
+<li>wrn (wide resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/wrn-50-2.tar.gz">50</a></li>
+<li>preact (resnet with pre-activation) <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-200.tar.gz">200</a></li>
+</ul>
+</li>
+<li><p class="first">Submit images for classification</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  $ curl -i -F image=@image1.jpg http://localhost:9999/api
+  $ curl -i -F image=@image2.jpg http://localhost:9999/api
+  $ curl -i -F image=@image3.jpg http://localhost:9999/api
+</pre></div>
+</div>
+</li>
+</ul>
+<p>image1.jpg, image2.jpg and image3.jpg should be downloaded before executing the above commands.</p>
+</div>
+<div class="section" id="details">
+<h2>Details<a class="headerlink" href="#details" title="Permalink to this headline">¶</a></h2>
+<p>The parameter files were extracted from the original <a class="reference external" href="https://github.com/facebook/fb.resnet.torch/tree/master/pretrained">torch files</a> via
+the convert.py program.</p>
+<p>Usage:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ python convert.py -h
+</pre></div>
+</div>
+</div>
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Added: incubator/singa/site/trunk/docs/model_zoo/imagenet/vgg/README.html
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--- incubator/singa/site/trunk/docs/model_zoo/imagenet/vgg/README.html (added)
+++ incubator/singa/site/trunk/docs/model_zoo/imagenet/vgg/README.html Sun Apr 21 22:05:49 2019
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+SINGA version: 1.0.1
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+SINGA version: 1.1.1
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+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="../resnet/README.html#image-classification-using-residual-networks">Image Classification using Residual Networks</a></li>
+<li class="toctree-l3 current"><a class="current reference internal" href="#">name: VGG models on ImageNet
+SINGA version: 1.1.1
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+<li class="toctree-l3"><a class="reference internal" href="#image-classification-using-vgg">Image Classification using VGG</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="#instructions">Instructions</a></li>
+<li class="toctree-l4"><a class="reference internal" href="#details">Details</a></li>
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+      <li>name: VGG models on ImageNet
+SINGA version: 1.1.1
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+license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py</li>
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+<div class="section" id="name-vgg-models-on-imagenet-singa-version-1-1-1-singa-commit-license-https-github-com-pytorch-vision-blob-master-torchvision-models-vgg-py">
+<h1>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 class="headerlink" href="#name-vgg-models-on-imagenet-singa-version-1-1-1-singa-commit-license-https-github-com-pytorch-vision-blob-master-torchvision-models-vgg-py" title="Permalink to this headline">¶</a></h1>
+</div>
+<div class="section" id="image-classification-using-vgg">
+<h1>Image Classification using VGG<a class="headerlink" href="#image-classification-using-vgg" title="Permalink to this headline">¶</a></h1>
+<p>In this example, we convert VGG on <a class="reference external" href="https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py">PyTorch</a>
+to SINGA for image classification.</p>
+<div class="section" id="instructions">
+<h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2>
+<ul>
+<li><p class="first">Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz
+  $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt
+  $ tar xvf vgg11.tar.gz
+</pre></div>
+</div>
+</li>
+<li><p class="first">Usage</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  $ python serve.py -h
+</pre></div>
+</div>
+</li>
+<li><p class="first">Example</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  # use cpu
+  $ python serve.py --use_cpu --parameter_file vgg11.pickle --depth 11 &amp;
+  # use gpu
+  $ python serve.py --parameter_file vgg11.pickle --depth 11 &amp;
+</pre></div>
+</div>
+<p>The parameter files for the following model and depth configuration pairs are provided:</p>
+<ul class="simple">
+<li>Without batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz">11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13.tar.gz">13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16.tar.gz">16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19.tar.gz">19</a></li>
+<li>With batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11_bn.tar.gz">11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13_bn.tar.gz">13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16_bn.tar.gz">16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19_bn.tar.gz">19</a></li>
+</ul>
+</li>
+<li><p class="first">Submit images for classification</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>  $ curl -i -F image=@image1.jpg http://localhost:9999/api
+  $ curl -i -F image=@image2.jpg http://localhost:9999/api
+  $ curl -i -F image=@image3.jpg http://localhost:9999/api
+</pre></div>
+</div>
+</li>
+</ul>
+<p>image1.jpg, image2.jpg and image3.jpg should be downloaded before executing the above commands.</p>
+</div>
+<div class="section" id="details">
+<h2>Details<a class="headerlink" href="#details" title="Permalink to this headline">¶</a></h2>
+<p>The parameter files were converted from the pytorch via the convert.py program.</p>
+<p>Usage:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ python convert.py -h
+</pre></div>
+</div>
+</div>
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Added: incubator/singa/site/trunk/docs/model_zoo/index.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/index.html?rev=1857927&view=auto
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--- incubator/singa/site/trunk/docs/model_zoo/index.html (added)
+++ incubator/singa/site/trunk/docs/model_zoo/index.html Sun Apr 21 22:05:49 2019
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+<li class="toctree-l2"><a class="reference internal" href="../net.html">FeedForward Net</a></li>
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+<li class="toctree-l2 current"><a class="current reference internal" href="#">Model Zoo</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="cifar10/README.html">Train CNN over Cifar-10</a></li>
+<li class="toctree-l3"><a class="reference internal" href="char-rnn/README.html">Train Char-RNN over plain text</a></li>
+<li class="toctree-l3"><a class="reference internal" href="mnist/README.html">Train a RBM model against MNIST dataset</a></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">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">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">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">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">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>
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+</ul>
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+<li class="toctree-l1"><a class="reference internal" href="../../downloads.html">Download SINGA</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../develop/how-to-release.html">How to prepare a release</a></li>
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+<p class="caption"><span class="caption-text">Community</span></p>
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+           <div itemprop="articleBody">
+            
+  <div class="section" id="model-zoo">
+<h1>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this headline">¶</a></h1>
+<div class="toctree-wrapper compound">
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="cifar10/README.html">Train CNN over Cifar-10</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="cifar10/README.html#instructions">Instructions</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="cifar10/README.html#singa-installation">SINGA installation</a></li>
+<li class="toctree-l3"><a class="reference internal" href="cifar10/README.html#data-preparation">Data preparation</a></li>
+<li class="toctree-l3"><a class="reference internal" href="cifar10/README.html#training">Training</a></li>
+<li class="toctree-l3"><a class="reference internal" href="cifar10/README.html#prediction">Prediction</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="char-rnn/README.html">Train Char-RNN over plain text</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="char-rnn/README.html#instructions">Instructions</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="mnist/README.html">Train a RBM model against MNIST dataset</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="mnist/README.html#running-instructions">Running instructions</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="imagenet/alexnet/README.html">Train AlexNet over ImageNet</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/alexnet/README.html#instructions">Instructions</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="imagenet/alexnet/README.html#compile-singa">Compile SINGA</a></li>
+<li class="toctree-l3"><a class="reference internal" href="imagenet/alexnet/README.html#data-download">Data download</a></li>
+<li class="toctree-l3"><a class="reference internal" href="imagenet/alexnet/README.html#data-preprocessing">Data preprocessing</a></li>
+<li class="toctree-l3"><a class="reference internal" href="imagenet/alexnet/README.html#training">Training</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l1"><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-l1"><a class="reference internal" href="imagenet/densenet/README.html#image-classification-using-densenet">Image Classification using DenseNet</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/densenet/README.html#instructions">Instructions</a></li>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/densenet/README.html#details">Details</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><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-l1"><a class="reference internal" href="imagenet/googlenet/README.html#image-classification-using-googlenet">Image Classification using GoogleNet</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/googlenet/README.html#instructions">Instructions</a></li>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/googlenet/README.html#details">Details</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><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-l1"><a class="reference internal" href="imagenet/inception/README.html#image-classification-using-inception-v4">Image Classification using Inception V4</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/inception/README.html#instructions">Instructions</a></li>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/inception/README.html#details">Details</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><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-l1"><a class="reference internal" href="imagenet/resnet/README.html#image-classification-using-residual-networks">Image Classification using Residual Networks</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/resnet/README.html#instructions">Instructions</a></li>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/resnet/README.html#details">Details</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><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-l1"><a class="reference internal" href="imagenet/vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/vgg/README.html#instructions">Instructions</a></li>
+<li class="toctree-l2"><a class="reference internal" href="imagenet/vgg/README.html#details">Details</a></li>
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+    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">Hinton’s paper</a></p>
+<div class="section" id="running-instructions">
+<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>
+<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>
+</li>
+</ol>
+<p>By default the training code would run on CPU. To run it on a GPU card, please start
+the program with an additional argument</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> <span class="o">--</span><span class="n">use_gpu</span>
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