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<p>In this example, we convert DenseNet on <a href="https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py">PyTorch</a> to SINGA for image classification.</p>
<h2><a class="anchor" aria-hidden="true" id="instructions"></a><a href="#instructions" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Instructions</h2>
<blockquote>
<p>Please <code>cd</code> to <code>singa/examples/imagenet/densenet/</code> for the following commands</p>
</blockquote>
<h3><a class="anchor" aria-hidden="true" id="download-one-parameter-checkpoint-file"></a><a href="#download-one-parameter-checkpoint-file" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Download one parameter checkpoint file</h3>
<p>Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> wget https://s3-ap-southeast-1.amazonaws.com/dlfile/densenet/densenet-121.tar.gz</span>
<span class="hljs-meta">$</span><span class="bash"> wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt</span>
<span class="hljs-meta">$</span><span class="bash"> tar xvf densenet-121.tar.gz</span>
</code></pre>
<h3><a class="anchor" aria-hidden="true" id="usage"></a><a href="#usage" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Usage</h3>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> python serve.py -h</span>
</code></pre>
<h3><a class="anchor" aria-hidden="true" id="example"></a><a href="#example" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Example</h3>
<pre><code class="hljs css language-shell"><span class="hljs-meta">#</span><span class="bash"> use cpu</span>
<span class="hljs-meta">$</span><span class="bash"> python serve.py --use_cpu --parameter_file densenet-121.pickle --depth 121 &amp;</span>
<span class="hljs-meta">#</span><span class="bash"> use gpu</span>
<span class="hljs-meta">$</span><span class="bash"> python serve.py --parameter_file densenet-121.pickle --depth 121 &amp;</span>
</code></pre>
<p>The parameter files for the following model and depth configuration pairs are provided: <a href="https://s3-ap-southeast-1.amazonaws.com/dlfile/densenet/densenet-121.tar.gz">121</a>, <a href="https://s3-ap-southeast-1.amazonaws.com/dlfile/densenet/densenet-169.tar.gz">169</a>, <a href="https://s3-ap-southeast-1.amazonaws.com/dlfile/densenet/densenet-201.tar.gz">201</a>, <a href="https://s3-ap-southeast-1.amazonaws.com/dlfile/densenet/densenet-161.tar.gz">161</a></p>
<h3><a class="anchor" aria-hidden="true" id="submit"></a><a href="#submit" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Submit</h3>
<p>Submit images for classification</p>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> curl -i -F image=@image1.jpg http://localhost:9999/api</span>
<span class="hljs-meta">$</span><span class="bash"> curl -i -F image=@image2.jpg http://localhost:9999/api</span>
<span class="hljs-meta">$</span><span class="bash"> curl -i -F image=@image3.jpg http://localhost:9999/api</span>
</code></pre>
<p>image1.jpg, image2.jpg and image3.jpg should be downloaded before executing the above commands.</p>
<h2><a class="anchor" aria-hidden="true" id="details"></a><a href="#details" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Details</h2>
<p>The parameter files were converted from the pytorch via the convert.py program.</p>
<p>Usage:</p>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> python convert.py -h</span>
</code></pre>
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