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+ <div class="section" id="train-char-rnn-over-plain-text">
+<span id="train-char-rnn-over-plain-text"></span><h1>Train Char-RNN over plain text<a class="headerlink" href="#train-char-rnn-over-plain-text" title="Permalink to this headline">¶</a></h1>
+<p>Recurrent neural networks (RNN) are widely used for modelling sequential data,
+e.g., natural language sentences. This example describes how to implement a RNN
+application (or model) using SINGA’s RNN layers.
+We will use the <a class="reference external" href="https://github.com/karpathy/char-rnn">char-rnn</a> model as an
+example, which trains over sentences or
+source code, with each character as an input unit. Particularly, we will train
+a RNN using GRU over Linux kernel source code. After training, we expect to
+generate meaningful code from the model.</p>
+<div class="section" id="instructions">
+<span id="instructions"></span><h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2>
+<ul>
+<li><p class="first">Compile and install SINGA. Currently the RNN implementation depends on Cudnn with version >= 5.05.</p>
+</li>
+<li><p class="first">Prepare the dataset. Download the <a class="reference external" href="http://cs.stanford.edu/people/karpathy/char-rnn/">kernel source code</a>.
+Other plain text files can also be used.</p>
+</li>
+<li><p class="first">Start the training,</p>
+<div class="highlight-python"><div class="highlight"><pre> python train.py linux_input.txt
+</pre></div>
+</div>
+<p>Some hyper-parameters could be set through command line,</p>
+<div class="highlight-python"><div class="highlight"><pre> python train.py -h
+</pre></div>
+</div>
+</li>
+<li><p class="first">Sample characters from the model by providing the number of characters to sample and the seed string.</p>
+<div class="highlight-python"><div class="highlight"><pre> python sample.py 'model.bin' 100 --seed '#include <std'
+</pre></div>
+</div>
+<p>Please replace ‘model.bin’ with the path to one of the checkpoint paths.</p>
+</li>
+</ul>
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+ <div class="section" id="train-cnn-over-cifar-10">
+<span id="train-cnn-over-cifar-10"></span><h1>Train CNN over Cifar-10<a class="headerlink" href="#train-cnn-over-cifar-10" title="Permalink to this headline">¶</a></h1>
+<p>Convolution neural network (CNN) is a type of feed-forward artificial neural
+network widely used for image and video classification. In this example, we
+will train three deep CNN models to do image classification for the CIFAR-10 dataset,</p>
+<ol class="simple">
+<li><a class="reference external" href="https://code.google.com/p/cuda-convnet/source/browse/trunk/example-layers/layers-18pct.cfg">AlexNet</a>
+the best validation accuracy (without data augmentation) we achieved was about 82%.</li>
+<li><a class="reference external" href="http://torch.ch/blog/2015/07/30/cifar.html">VGGNet</a>, the best validation accuracy (without data augmentation) we achieved was about 89%.</li>
+<li><a class="reference external" href="https://github.com/facebook/fb.resnet.torch">ResNet</a>, the best validation accuracy (without data augmentation) we achieved was about 83%.</li>
+<li><a class="reference external" href="https://github.com/BVLC/caffe/tree/master/examples/cifar10">Alexnet from Caffe</a>, SINGA is able to convert model from Caffe seamlessly.</li>
+</ol>
+<div class="section" id="instructions">
+<span id="instructions"></span><h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2>
+<div class="section" id="singa-installation">
+<span id="singa-installation"></span><h3>SINGA installation<a class="headerlink" href="#singa-installation" title="Permalink to this headline">¶</a></h3>
+<p>Users can compile and install SINGA from source or install the Python version.
+The code can ran on both CPU and GPU. For GPU training, CUDA and CUDNN (V4 or V5)
+are required. Please refer to the installation page for detailed instructions.</p>
+</div>
+<div class="section" id="data-preparation">
+<span id="data-preparation"></span><h3>Data preparation<a class="headerlink" href="#data-preparation" title="Permalink to this headline">¶</a></h3>
+<p>The binary Cifar-10 dataset could be downloaded by</p>
+<div class="highlight-python"><div class="highlight"><pre>python download_data.py bin
+</pre></div>
+</div>
+<p>The Python version could be downloaded by</p>
+<div class="highlight-python"><div class="highlight"><pre>python download_data.py py
+</pre></div>
+</div>
+</div>
+<div class="section" id="training">
+<span id="training"></span><h3>Training<a class="headerlink" href="#training" title="Permalink to this headline">¶</a></h3>
+<p>There are four training programs</p>
+<ol>
+<li><p class="first">train.py. The following command would train the VGG model using the python
+version of the Cifar-10 dataset in ‘cifar-10-batches-py’ folder.</p>
+<div class="highlight-python"><div class="highlight"><pre> python train.py vgg cifar-10-batches-py
+</pre></div>
+</div>
+<p>To train other models, please replace ‘vgg’ to ‘alexnet’, ‘resnet’ or ‘caffe’,
+where ‘caffe’ refers to the alexnet model converted from Caffe. By default
+the training would run on a CudaGPU device, to run it on CppCPU, add an additional
+argument</p>
+<div class="highlight-python"><div class="highlight"><pre> python train.py vgg cifar-10-batches-py --use_cpu
+</pre></div>
+</div>
+</li>
+<li><p class="first">alexnet.cc. It trains the AlexNet model using the CPP APIs on a CudaGPU,</p>
+<div class="highlight-python"><div class="highlight"><pre> ./run.sh
+</pre></div>
+</div>
+</li>
+<li><p class="first">alexnet-parallel.cc. It trains the AlexNet model using the CPP APIs on two CudaGPU devices.
+The two devices run synchronously to compute the gradients of the mode parameters, which are
+averaged on the host CPU device and then be applied to update the parameters.</p>
+<div class="highlight-python"><div class="highlight"><pre> ./run-parallel.sh
+</pre></div>
+</div>
+</li>
+<li><p class="first">vgg-parallel.cc. It trains the VGG model using the CPP APIs on two CudaGPU devices similar to alexnet-parallel.cc.</p>
+</li>
+</ol>
+</div>
+<div class="section" id="prediction">
+<span id="prediction"></span><h3>Prediction<a class="headerlink" href="#prediction" title="Permalink to this headline">¶</a></h3>
+<p>predict.py includes the prediction function</p>
+<div class="highlight-python"><div class="highlight"><pre> def predict(net, images, dev, topk=5)
+</pre></div>
+</div>
+<p>The net is created by loading the previously trained model; Images consist of
+a numpy array of images (one row per image); dev is the training device, e.g.,
+a CudaGPU device or the host CppCPU device; It returns the topk labels for each instance.</p>
+<p>The predict.py file’s main function provides an example of using the pre-trained alexnet model to do prediction for new images.
+The ‘model.bin’ file generated by the training program should be placed at the cifar10 folder to run</p>
+<div class="highlight-python"><div class="highlight"><pre> python predict.py
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+
+
+ </div>
+ </div>
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+
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+ <p>
+ © Copyright 2017 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>
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+ <div class="section" id="train-alexnet-over-imagenet">
+<span id="train-alexnet-over-imagenet"></span><h1>Train AlexNet over ImageNet<a class="headerlink" href="#train-alexnet-over-imagenet" title="Permalink to this headline">¶</a></h1>
+<p>Convolution neural network (CNN) is a type of feed-forward neural
+network widely used for image and video classification. In this example, we will
+use a <a class="reference external" href="http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks">deep CNN model</a>
+to do image classification against the ImageNet dataset.</p>
+<div class="section" id="instructions">
+<span id="instructions"></span><h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2>
+<div class="section" id="compile-singa">
+<span id="compile-singa"></span><h3>Compile SINGA<a class="headerlink" href="#compile-singa" title="Permalink to this headline">¶</a></h3>
+<p>Please compile SINGA with CUDA, CUDNN and OpenCV. You can manually turn on the
+options in CMakeLists.txt or run <code class="docutils literal"><span class="pre">ccmake</span> <span class="pre">..</span></code> in build/ folder.</p>
+<p>We have tested CUDNN V4 and V5 (V5 requires CUDA 7.5)</p>
+</div>
+<div class="section" id="data-download">
+<span id="data-download"></span><h3>Data download<a class="headerlink" href="#data-download" title="Permalink to this headline">¶</a></h3>
+<ul class="simple">
+<li>Please refer to step1-3 on <a class="reference external" href="https://github.com/amd/OpenCL-caffe/wiki/Instructions-to-create-ImageNet-2012-data">Instructions to create ImageNet 2012 data</a>
+to download and decompress the data.</li>
+<li>You can download the training and validation list by
+<a class="reference external" href="https://github.com/BVLC/caffe/blob/master/data/ilsvrc12/get_ilsvrc_aux.sh">get_ilsvrc_aux.sh</a>
+or from <a class="reference external" href="http://www.image-net.org/download-images">Imagenet</a>.</li>
+</ul>
+</div>
+<div class="section" id="data-preprocessing">
+<span id="data-preprocessing"></span><h3>Data preprocessing<a class="headerlink" href="#data-preprocessing" title="Permalink to this headline">¶</a></h3>
+<ul>
+<li><p class="first">Assuming you have downloaded the data and the list.
+Now we should transform the data into binary files. You can run:</p>
+<div class="highlight-python"><div class="highlight"><pre> sh create_data.sh
+</pre></div>
+</div>
+<p>The script will generate a test file(<code class="docutils literal"><span class="pre">test.bin</span></code>), a mean file(<code class="docutils literal"><span class="pre">mean.bin</span></code>) and
+several training files(<code class="docutils literal"><span class="pre">trainX.bin</span></code>) in the specified output folder.</p>
+</li>
+<li><p class="first">You can also change the parameters in <code class="docutils literal"><span class="pre">create_data.sh</span></code>.</p>
+<ul class="simple">
+<li><code class="docutils literal"><span class="pre">-trainlist</span> <span class="pre"><file></span></code>: the file of training list;</li>
+<li><code class="docutils literal"><span class="pre">-trainfolder</span> <span class="pre"><folder></span></code>: the folder of training images;</li>
+<li><code class="docutils literal"><span class="pre">-testlist</span> <span class="pre"><file></span></code>: the file of test list;</li>
+<li><code class="docutils literal"><span class="pre">-testfolder</span> <span class="pre"><floder></span></code>: the folder of test images;</li>
+<li><code class="docutils literal"><span class="pre">-outdata</span> <span class="pre"><folder></span></code>: the folder to save output files, including mean, training and test files.
+The script will generate these files in the specified folder;</li>
+<li><code class="docutils literal"><span class="pre">-filesize</span> <span class="pre"><int></span></code>: number of training images that stores in each binary file.</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="section" id="training">
+<span id="training"></span><h3>Training<a class="headerlink" href="#training" title="Permalink to this headline">¶</a></h3>
+<ul>
+<li><p class="first">After preparing data, you can run the following command to train the Alexnet model.</p>
+<div class="highlight-python"><div class="highlight"><pre> sh run.sh
+</pre></div>
+</div>
+</li>
+<li><p class="first">You may change the parameters in <code class="docutils literal"><span class="pre">run.sh</span></code>.</p>
+<ul class="simple">
+<li><code class="docutils literal"><span class="pre">-epoch</span> <span class="pre"><int></span></code>: number of epoch to be trained, default is 90;</li>
+<li><code class="docutils literal"><span class="pre">-lr</span> <span class="pre"><float></span></code>: base learning rate, the learning rate will decrease each 20 epochs,
+more specifically, <code class="docutils literal"><span class="pre">lr</span> <span class="pre">=</span> <span class="pre">lr</span> <span class="pre">*</span> <span class="pre">exp(0.1</span> <span class="pre">*</span> <span class="pre">(epoch</span> <span class="pre">/</span> <span class="pre">20))</span></code>;</li>
+<li><code class="docutils literal"><span class="pre">-batchsize</span> <span class="pre"><int></span></code>: batchsize, it should be changed regarding to your memory;</li>
+<li><code class="docutils literal"><span class="pre">-filesize</span> <span class="pre"><int></span></code>: number of training images that stores in each binary file, it is the
+same as the <code class="docutils literal"><span class="pre">filesize</span></code> in data preprocessing;</li>
+<li><code class="docutils literal"><span class="pre">-ntrain</span> <span class="pre"><int></span></code>: number of training images;</li>
+<li><code class="docutils literal"><span class="pre">-ntest</span> <span class="pre"><int></span></code>: number of test images;</li>
+<li><code class="docutils literal"><span class="pre">-data</span> <span class="pre"><folder></span></code>: the folder which stores the binary files, it is exactly the output
+folder in data preprocessing step;</li>
+<li><code class="docutils literal"><span class="pre">-pfreq</span> <span class="pre"><int></span></code>: the frequency(in batch) of printing current model status(loss and accuracy);</li>
+<li><code class="docutils literal"><span class="pre">-nthreads</span> <span class="pre"><int></span></code>: the number of threads to load data which feed to the model.</li>
+</ul>
+</li>
+</ul>
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+<p>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</p>
+<hr class="docutils" />
+<div class="section" id="image-classification-using-googlenet">
+<span id="image-classification-using-googlenet"></span><h1>Image Classification using GoogleNet<a class="headerlink" href="#image-classification-using-googlenet" title="Permalink to this headline">¶</a></h1>
+<p>In this example, we convert GoogleNet trained on Caffe to SINGA for image classification.</p>
+<div class="section" id="instructions">
+<span id="instructions"></span><h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2>
+<ul>
+<li><p class="first">Download the parameter checkpoint file into this folder</p>
+<div class="highlight-python"><div class="highlight"><pre> $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz
+ $ tar xvf bvlc_googlenet.tar.gz
+</pre></div>
+</div>
+</li>
+<li><p class="first">Run the program</p>
+<div class="highlight-python"><div class="highlight"><pre> # use cpu
+ $ python serve.py -C &
+ # use gpu
+ $ python serve.py &
+</pre></div>
+</div>
+</li>
+<li><p class="first">Submit images for classification</p>
+<div class="highlight-python"><div class="highlight"><pre> $ 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">
+<span id="details"></span><h2>Details<a class="headerlink" href="#details" title="Permalink to this headline">¶</a></h2>
+<p>We first extract the parameter values from <a class="reference external" href="http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel">Caffe’s checkpoint file</a> into a pickle version
+After downloading the checkpoint file into <code class="docutils literal"><span class="pre">caffe_root/python</span></code> folder, run the following script</p>
+<div class="highlight-python"><div class="highlight"><pre><span class="c1"># to be executed within caffe_root/python folder</span>
+<span class="kn">import</span> <span class="nn">caffe</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">cPickle</span> <span class="kn">as</span> <span class="nn">pickle</span>
+
+<span class="n">model_def</span> <span class="o">=</span> <span class="s1">'../models/bvlc_googlenet/deploy.prototxt'</span>
+<span class="n">weight</span> <span class="o">=</span> <span class="s1">'bvlc_googlenet.caffemodel'</span> <span class="c1"># must be downloaded at first</span>
+<span class="n">net</span> <span class="o">=</span> <span class="n">caffe</span><span class="o">.</span><span class="n">Net</span><span class="p">(</span><span class="n">model_def</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">caffe</span><span class="o">.</span><span class="n">TEST</span><span class="p">)</span>
+
+<span class="n">params</span> <span class="o">=</span> <span class="p">{}</span>
+<span class="k">for</span> <span class="n">layer_name</span> <span class="ow">in</span> <span class="n">net</span><span class="o">.</span><span class="n">params</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
+ <span class="n">weights</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">net</span><span class="o">.</span><span class="n">params</span><span class="p">[</span><span class="n">layer_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">data</span><span class="p">)</span>
+ <span class="n">bias</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">net</span><span class="o">.</span><span class="n">params</span><span class="p">[</span><span class="n">layer_name</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">data</span><span class="p">)</span>
+ <span class="n">params</span><span class="p">[</span><span class="n">layer_name</span><span class="o">+</span><span class="s1">'_weight'</span><span class="p">]</span><span class="o">=</span><span class="n">weights</span>
+ <span class="n">params</span><span class="p">[</span><span class="n">layer_name</span><span class="o">+</span><span class="s1">'_bias'</span><span class="p">]</span><span class="o">=</span><span class="n">bias</span>
+ <span class="k">print</span> <span class="n">layer_name</span><span class="p">,</span> <span class="n">weights</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">bias</span><span class="o">.</span><span class="n">shape</span>
+
+<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">'bvlc_googlenet.pickle'</span><span class="p">,</span> <span class="s1">'wb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">fd</span><span class="p">:</span>
+ <span class="n">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">fd</span><span class="p">)</span>
+</pre></div>
+</div>
+<p>Then we construct the GoogleNet using SINGA’s FeedForwardNet structure.
+Note that we added a EndPadding layer to resolve the issue from discrepancy
+of the rounding strategy of the pooling layer between Caffe (ceil) and cuDNN (floor).
+Only the MaxPooling layers outside inception blocks have this problem.
+Refer to <a class="reference external" href="http://joelouismarino.github.io/blog_posts/blog_googlenet_keras.html">this</a> for more detials.</p>
+</div>
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+ <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="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/googlenet/README.html">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>
+</ul>
+</div>
+</div>
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+
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+
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+
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+ <p>
+ © Copyright 2017 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>
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+ Built with <a href="http://sphinx-doc.org/">Sphinx</a> using a <a href="https://github.com/snide/sphinx_rtd_theme">theme</a> provided by <a href="https://readthedocs.org">Read the Docs</a>.
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+
+ <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>
+<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">
+<span id="running-instructions"></span><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-python"><div class="highlight"><pre> python train.py mnist.pkl.gz
+</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-python"><div class="highlight"><pre> python train.py mnist.pkl.gz --use_gpu
+</pre></div>
+</div>
+</div>
+</div>
+
+
+ </div>
+ </div>
+ <footer>
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+ <p>
+ © Copyright 2017 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..
+
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+ <div class="rst-other-versions">
+ <dl>
+ <dt>Languages</dt>
+ <dd><a href="../../../../../en/index.html">English</a></dd>
+ <dd><a href="../../../../../zh/index.html">中文</a></dd>
+ </dl>
+ <dl>
+ <dt>Versions</dt>
+ <dd><a href="http://singa.apache.org/v0.3.0/">0.3</a></dd>
+ </dl>
+
+ </div>
+</div>
+
+ <a href="https://github.com/apache/incubator-singa">
+ <img style="position: absolute; top: 0; right: 0; border: 0; z-index: 10000;"
+ src="https://s3.amazonaws.com/github/ribbons/forkme_right_orange_ff7600.png"
+ alt="Fork me on GitHub">
+</a>
+
+
+
+
+</body>
+</html>
\ No newline at end of file
Modified: incubator/singa/site/trunk/en/docs/model_zoo/imagenet/README.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/model_zoo/imagenet/README.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/model_zoo/imagenet/README.html (original)
+++ incubator/singa/site/trunk/en/docs/model_zoo/imagenet/README.html Tue Jan 24 09:25:48 2017
@@ -273,7 +273,7 @@ folder in data preprocessing step;</li>
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/docs/model_zoo/index.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/model_zoo/index.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/model_zoo/index.html (original)
+++ incubator/singa/site/trunk/en/docs/model_zoo/index.html Tue Jan 24 09:25:48 2017
@@ -223,7 +223,7 @@
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
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=1780040&r1=1780039&r2=1780040&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 Tue Jan 24 09:25:48 2017
@@ -178,7 +178,7 @@ the program with an additional argument<
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/docs/net.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/net.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/net.html (original)
+++ incubator/singa/site/trunk/en/docs/net.html Tue Jan 24 09:25:48 2017
@@ -388,7 +388,7 @@ less space.</li>
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
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=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/neural-net.html (original)
+++ incubator/singa/site/trunk/en/docs/neural-net.html Tue Jan 24 09:25:48 2017
@@ -478,7 +478,7 @@ lower layers and <code class="docutils l
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
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=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/notebook/README.html (original)
+++ incubator/singa/site/trunk/en/docs/notebook/README.html Tue Jan 24 09:25:48 2017
@@ -157,7 +157,7 @@
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/docs/optimizer.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/optimizer.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/optimizer.html (original)
+++ incubator/singa/site/trunk/en/docs/optimizer.html Tue Jan 24 09:25:48 2017
@@ -548,7 +548,7 @@ updating rules (including regularizer an
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/docs/snapshot.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/snapshot.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/snapshot.html (original)
+++ incubator/singa/site/trunk/en/docs/snapshot.html Tue Jan 24 09:25:48 2017
@@ -229,7 +229,7 @@
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/docs/software_stack.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/software_stack.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/software_stack.html (original)
+++ incubator/singa/site/trunk/en/docs/software_stack.html Tue Jan 24 09:25:48 2017
@@ -281,7 +281,7 @@ model parameter values using parameter g
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/docs/tensor.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/tensor.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/tensor.html (original)
+++ incubator/singa/site/trunk/en/docs/tensor.html Tue Jan 24 09:25:48 2017
@@ -1379,7 +1379,7 @@ must be on the default CppCPU device.</p
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/docs/utils.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/docs/utils.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/docs/utils.html (original)
+++ incubator/singa/site/trunk/en/docs/utils.html Tue Jan 24 09:25:48 2017
@@ -208,7 +208,7 @@
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/downloads.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/downloads.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/downloads.html (original)
+++ incubator/singa/site/trunk/en/downloads.html Tue Jan 24 09:25:48 2017
@@ -266,7 +266,7 @@ ASF.</p>
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/genindex.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/genindex.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/genindex.html (original)
+++ incubator/singa/site/trunk/en/genindex.html Tue Jan 24 09:25:48 2017
@@ -1239,7 +1239,7 @@
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/index.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/index.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/index.html (original)
+++ incubator/singa/site/trunk/en/index.html Tue Jan 24 09:25:48 2017
@@ -241,7 +241,7 @@
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/py-modindex.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/py-modindex.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/py-modindex.html (original)
+++ incubator/singa/site/trunk/en/py-modindex.html Tue Jan 24 09:25:48 2017
@@ -241,7 +241,7 @@
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.1.0.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.1.0.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.1.0.html (original)
+++ incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.1.0.html Tue Jan 24 09:25:48 2017
@@ -265,7 +265,7 @@ deep learning models.</p>
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.2.0.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.2.0.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.2.0.html (original)
+++ incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.2.0.html Tue Jan 24 09:25:48 2017
@@ -254,7 +254,7 @@ of popular deep learning models.</p>
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>
Modified: incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.3.0.html
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.3.0.html?rev=1780040&r1=1780039&r2=1780040&view=diff
==============================================================================
--- incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.3.0.html (original)
+++ incubator/singa/site/trunk/en/releases/RELEASE_NOTES_0.3.0.html Tue Jan 24 09:25:48 2017
@@ -194,7 +194,7 @@ of popular deep learning models.</p>
<div role="contentinfo">
<p>
- © Copyright 2016 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 2017 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>