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href="../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="../vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a></li> +</ul> +</li> +<li class="toctree-l2"><a class="reference internal" href="../../../security.html">Security</a></li> +</ul> +</li> +<li class="toctree-l1"><a class="reference internal" href="../../../../downloads.html">Download SINGA</a></li> +</ul> +<p class="caption"><span class="caption-text">Development</span></p> +<ul> +<li class="toctree-l1"><a class="reference internal" href="../../../../develop/schedule.html">Development Schedule</a></li> +<li class="toctree-l1"><a class="reference internal" href="../../../../develop/how-contribute.html">How to Contribute to SINGA</a></li> +<li class="toctree-l1"><a class="reference internal" 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Tracking</a></li> +<li class="toctree-l1"><a class="reference internal" href="../../../../community/team-list.html">The SINGA Team</a></li> +</ul> + + + + </div> + </div> + </nav> + + <section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"> + + + <nav class="wy-nav-top" aria-label="top navigation"> + + <i data-toggle="wy-nav-top" class="fa fa-bars"></i> + <a href="../../../../index.html">incubator-singa</a> + + </nav> + + + <div class="wy-nav-content"> + + <div class="rst-content"> + + + + + + + + + + + + + + + + + +<div role="navigation" aria-label="breadcrumbs navigation"> + + <ul class="wy-breadcrumbs"> + + <li><a href="../../../../index.html">Docs</a> »</li> + + <li><a href="../../../index.html">Documentation</a> »</li> + + <li><a href="../../index.html">Model Zoo</a> »</li> + + <li>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</li> + + + <li class="wy-breadcrumbs-aside"> + + + + </li> + + </ul> + + + <hr/> +</div> + <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> + <div itemprop="articleBody"> + + <!-- + Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + 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 + + 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. +--><hr class="docutils" /> +<div class="section" id="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"> +<h1>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 class="headerlink" href="#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" title="Permalink to this headline">¶</a></h1> +</div> +<div class="section" id="image-classification-using-googlenet"> +<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"> +<h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2> +<ul> +<li><p>Download the parameter checkpoint file into this folder</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ 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>Run the program</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu + $ python serve.py -C & + # use gpu + $ python serve.py & +</pre></div> +</div> +</li> +<li><p>Submit images for classification</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api + $ curl -i -F [email protected] http://localhost:9999/api + $ curl -i -F [email protected] 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>We first extract the parameter values from <a class="reference external" href="http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel";>Caffeâs checkpoint file</a> into a pickle version +After downloading the checkpoint file into <code class="docutils literal notranslate"><span class="pre">caffe_root/python</span></code> folder, run the following script</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><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="k">as</span> <span class="nn">np</span> +<span class="kn">import</span> <span class="nn">cPickle</span> <span class="k">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="nb">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 SINGAâs 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> +</div> + + + </div> + + </div> + <footer> + + <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> + + <a href="../inception/README.html" class="btn btn-neutral float-right" title="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"; accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a> + + + <a 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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="../vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a></li> +</ul> +</li> +<li class="toctree-l2"><a class="reference internal" href="../../../security.html">Security</a></li> +</ul> +</li> +<li class="toctree-l1"><a class="reference internal" href="../../../../downloads.html">Download SINGA</a></li> +</ul> +<p class="caption"><span class="caption-text">Development</span></p> +<ul> +<li class="toctree-l1"><a class="reference internal" href="../../../../develop/schedule.html">Development Schedule</a></li> +<li class="toctree-l1"><a class="reference internal" href="../../../../develop/how-contribute.html">How to Contribute to SINGA</a></li> +<li class="toctree-l1"><a class="reference internal" 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5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56 +license: https://github.com/tensorflow/models/tree/master/slim</li> + + + <li class="wy-breadcrumbs-aside"> + + + + </li> + + </ul> + + + <hr/> +</div> + <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> + <div itemprop="articleBody"> + + <!-- + Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + 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 + + 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. +--><hr class="docutils" /> +<div class="section" id="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"> +<h1>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 class="headerlink" href="#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" title="Permalink to this headline">¶</a></h1> +</div> +<div class="section" id="image-classification-using-inception-v4"> +<h1>Image Classification using Inception V4<a class="headerlink" href="#image-classification-using-inception-v4" title="Permalink to this headline">¶</a></h1> +<p>In this example, we convert Inception V4 trained on Tensorflow 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>Download the parameter checkpoint file</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ wget + $ tar xvf inception_v4.tar.gz +</pre></div> +</div> +</li> +<li><p>Download <a class="reference external" href="https://github.com/BVLC/caffe/blob/master/data/ilsvrc12/get_ilsvrc_aux.sh";>synset_word.txt</a> file.</p></li> +<li><p>Run the program</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu + $ python serve.py -C & + # use gpu + $ python serve.py & +</pre></div> +</div> +</li> +<li><p>Submit images for classification</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api + $ curl -i -F [email protected] http://localhost:9999/api + $ curl -i -F [email protected] 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>We first extract the parameter values from <a class="reference external" href="http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz";>Tensorflowâs checkpoint file</a> into a pickle version. +After downloading and decompressing the checkpoint file, run the following script</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ python convert.py --file_name=inception_v4.ckpt +</pre></div> +</div> +</div> +</div> + + + </div> + + </div> + <footer> + + <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> + + <a href="../resnet/README.html" class="btn btn-neutral float-right" title="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"; accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a> + + + <a href="../googlenet/README.html" class="btn btn-neutral float-left" title="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"; accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a> + + </div> + + + <hr/> + + <div role="contentinfo"> + <p> + © Copyright 2019 The Apache Software Foundation. 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itemscope="itemscope" itemtype="http://schema.org/Article";> + <div itemprop="articleBody"> + + <!-- + Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + 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 + + 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. +--><hr class="docutils" /> +<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>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>Usage</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ python serve.py -h +</pre></div> +</div> +</li> +<li><p>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 & + # use gpu + $ python serve.py --parameter_file resnet-18.pickle --model resnet --depth 18 & +</pre></div> +</div> +<p>The parameter files for the following model and depth configuration pairs are provided:</p> +<ul class="simple"> +<li><p>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></p></li> +<li><p>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></p></li> +<li><p>wrn (wide resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/wrn-50-2.tar.gz";>50</a></p></li> +<li><p>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></p></li> +</ul> +</li> +<li><p>Submit images for classification</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api + $ curl -i -F [email protected] http://localhost:9999/api + $ curl -i -F [email protected] 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> +</div> + + + </div> + + </div> + <footer> + + <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> + + <a href="../vgg/README.html" class="btn btn-neutral float-right" title="name: VGG models on ImageNet SINGA version: 1.1.1 SINGA commit: license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py"; 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