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<div class="section" id="mxnet-scala-symbolic-api">
<span id="mxnet-scala-symbolic-api"></span><h1>MXNet Scala Symbolic API<a class="headerlink" href="#mxnet-scala-symbolic-api" title="Permalink to this headline"></a></h1>
<p>Topics:</p>
<ul class="simple">
<li><a class="reference external" href="#overloaded-operators">How to Compose Symbols</a> introduces operator overloading of symbols.</li>
<li><a class="reference external" href="#symbol-attributes">Symbol Attributes</a> describes how to attach attributes to symbols.</li>
<li><a class="reference external" href="#serialization">Serialization</a> explains how to save and load symbols.</li>
<li><a class="reference external" href="#executing-symbols">Executing Symbols</a> explains how to evaluate the symbols with data.</li>
<li><a class="reference external" href="/versions/1.1.0/api/scala/docs/index.html#ml.dmlc.mxnet.Executor">Execution API Reference</a> documents the execution APIs.</li>
<li><a class="reference external" href="#multiple-outputs">Multiple Outputs</a> explains how to configure multiple outputs.</li>
<li><a class="reference external" href="/versions/1.1.0/api/scala/docs/index.html#ml.dmlc.mxnet.Symbol">Symbol Creation API Reference</a> documents functions.</li>
</ul>
<p>We also highly encourage you to read <a class="reference internal" href="symbol_in_pictures.html"><span class="doc">Symbolic Configuration and Execution in Pictures</span></a>.</p>
<div class="section" id="how-to-compose-symbols">
<span id="how-to-compose-symbols"></span><h2>How to Compose Symbols<a class="headerlink" href="#how-to-compose-symbols" title="Permalink to this headline"></a></h2>
<p>The symbolic API provides a way to configure computation graphs.
You can configure the graphs either at the level of neural network layer operations or as fine-grained operations.</p>
<p>The following example configures a two-layer neural network.</p>
<div class="highlight-scala"><div class="highlight"><pre><span></span> <span class="n">scala</span><span class="o">></span> <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">data</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"data"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">fc1</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">FullyConnected</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"fc1"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">data</span><span class="o">,</span> <span class="s">"num_hidden"</span> <span class="o">-></span> <span class="mi">128</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">act1</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Activation</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"relu1"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">fc1</span><span class="o">,</span> <span class="s">"act_type"</span> <span class="o">-></span> <span class="s">"relu"</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">fc2</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">FullyConnected</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"fc2"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">act1</span><span class="o">,</span> <span class="s">"num_hidden"</span> <span class="o">-></span> <span class="mi">64</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">net</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">SoftmaxOutput</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"out"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">fc2</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">:type</span> <span class="kt">net</span>
<span class="n">ml</span><span class="o">.</span><span class="n">dmlc</span><span class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span class="nc">Symbol</span>
</pre></div>
</div>
<p>The basic arithmetic operators (plus, minus, div, multiplication) are overloaded for
<em>element-wise operations</em> of symbols.</p>
<p>The following example creates a computation graph that adds two inputs together.</p>
<div class="highlight-scala"><div class="highlight"><pre><span></span> <span class="n">scala</span><span class="o">></span> <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">a</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"a"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">b</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"b"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">c</span> <span class="k">=</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
</pre></div>
</div>
</div>
<div class="section" id="symbol-attributes">
<span id="symbol-attributes"></span><h2>Symbol Attributes<a class="headerlink" href="#symbol-attributes" title="Permalink to this headline"></a></h2>
<p>You can add an attribute to a symbol by providing an attribute dictionary when you create a symbol.</p>
<div class="highlight-scala"><div class="highlight"><pre><span></span> <span class="k">val</span> <span class="n">data</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"data"</span><span class="o">,</span> <span class="nc">Map</span><span class="o">(</span><span class="s">"mood"</span><span class="o">-></span> <span class="s">"angry"</span><span class="o">))</span>
<span class="k">val</span> <span class="n">op</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Convolution</span><span class="o">()()(</span>
<span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">data</span><span class="o">,</span> <span class="s">"kernel"</span> <span class="o">-></span> <span class="s">"(1, 1)"</span><span class="o">,</span> <span class="s">"num_filter"</span> <span class="o">-></span> <span class="mi">1</span><span class="o">,</span> <span class="s">"mood"</span><span class="o">-></span> <span class="s">"so so"</span><span class="o">))</span>
</pre></div>
</div>
<p>For proper communication with the C++ backend, both the key and values of the attribute dictionary should be strings. To retrieve the attributes, use <code class="docutils literal"><span class="pre">attr(key)</span></code>:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span> <span class="n">data</span><span class="o">.</span><span class="n">attr</span><span class="p">(</span><span class="s2">"mood"</span><span class="p">)</span>
<span class="n">res6</span><span class="p">:</span> <span class="n">Option</span><span class="p">[</span><span class="n">String</span><span class="p">]</span> <span class="o">=</span> <span class="n">Some</span><span class="p">(</span><span class="n">angry</span><span class="p">)</span>
</pre></div>
</div>
<p>To attach attributes, you can use <code class="docutils literal"><span class="pre">AttrScope</span></code>. <code class="docutils literal"><span class="pre">AttrScope</span></code> automatically adds the specified attributes to all of the symbols created within that scope. The user can also inherit this object to change naming behavior. For example:</p>
<div class="highlight-scala"><div class="highlight"><pre><span></span> <span class="k">val</span> <span class="o">(</span><span class="n">data</span><span class="o">,</span> <span class="n">gdata</span><span class="o">)</span> <span class="k">=</span>
<span class="nc">AttrScope</span><span class="o">(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"group"</span> <span class="o">-></span> <span class="s">"4"</span><span class="o">,</span> <span class="s">"data"</span> <span class="o">-></span> <span class="s">"great"</span><span class="o">)).</span><span class="n">withScope</span> <span class="o">{</span>
<span class="k">val</span> <span class="n">data</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"data"</span><span class="o">,</span> <span class="n">attr</span> <span class="k">=</span> <span class="nc">Map</span><span class="o">(</span><span class="s">"dtype"</span> <span class="o">-></span> <span class="s">"data"</span><span class="o">,</span> <span class="s">"group"</span> <span class="o">-></span> <span class="s">"1"</span><span class="o">))</span>
<span class="k">val</span> <span class="n">gdata</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"data2"</span><span class="o">)</span>
<span class="o">(</span><span class="n">data</span><span class="o">,</span> <span class="n">gdata</span><span class="o">)</span>
<span class="o">}</span>
<span class="n">assert</span><span class="o">(</span><span class="n">gdata</span><span class="o">.</span><span class="n">attr</span><span class="o">(</span><span class="s">"group"</span><span class="o">).</span><span class="n">get</span> <span class="o">===</span> <span class="s">"4"</span><span class="o">)</span>
<span class="n">assert</span><span class="o">(</span><span class="n">data</span><span class="o">.</span><span class="n">attr</span><span class="o">(</span><span class="s">"group"</span><span class="o">).</span><span class="n">get</span> <span class="o">===</span> <span class="s">"1"</span><span class="o">)</span>
<span class="k">val</span> <span class="n">exceedScopeData</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"data3"</span><span class="o">)</span>
<span class="n">assert</span><span class="o">(</span><span class="n">exceedScopeData</span><span class="o">.</span><span class="n">attr</span><span class="o">(</span><span class="s">"group"</span><span class="o">)</span> <span class="o">===</span> <span class="nc">None</span><span class="o">,</span> <span class="s">"No group attr in global attr scope"</span><span class="o">)</span>
</pre></div>
</div>
</div>
<div class="section" id="serialization">
<span id="serialization"></span><h2>Serialization<a class="headerlink" href="#serialization" title="Permalink to this headline"></a></h2>
<p>There are two ways to save and load the symbols. You can use the <code class="docutils literal"><span class="pre">mxnet.Symbol.save</span></code> and <code class="docutils literal"><span class="pre">mxnet.Symbol.load</span></code> functions to serialize the <code class="docutils literal"><span class="pre">Symbol</span></code> objects.
The advantage of using <code class="docutils literal"><span class="pre">save</span></code> and <code class="docutils literal"><span class="pre">load</span></code> functions is that it is language agnostic and cloud friendly.
The symbol is saved in JSON format. You can also get a JSON string directly using <code class="docutils literal"><span class="pre">mxnet.Symbol.toJson</span></code>.
Refer to <a class="reference external" href="/versions/1.1.0/api/scala/docs/index.html#ml.dmlc.mxnet.Symbol">API documentation</a> for more details.</p>
<p>The following example shows how to save a symbol to an S3 bucket, load it back, and compare two symbols using a JSON string.</p>
<div class="highlight-scala"><div class="highlight"><pre><span></span> <span class="n">scala</span><span class="o">></span> <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">a</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"a"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">b</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"b"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">c</span> <span class="k">=</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
<span class="n">scala</span><span class="o">></span> <span class="n">c</span><span class="o">.</span><span class="n">save</span><span class="o">(</span><span class="s">"s3://my-bucket/symbol-c.json"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">c2</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="n">load</span><span class="o">(</span><span class="s">"s3://my-bucket/symbol-c.json"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="n">c</span><span class="o">.</span><span class="n">toJson</span> <span class="o">==</span> <span class="n">c2</span><span class="o">.</span><span class="n">toJson</span>
<span class="nc">Boolean</span> <span class="k">=</span> <span class="kc">true</span>
</pre></div>
</div>
</div>
<div class="section" id="executing-symbols">
<span id="executing-symbols"></span><h2>Executing Symbols<a class="headerlink" href="#executing-symbols" title="Permalink to this headline"></a></h2>
<p>After you have assembled a set of symbols into a computation graph, the MXNet engine can evaluate them.
If you are training a neural network, this is typically
handled by the high-level <a class="reference internal" href="model.html"><span class="doc">Model class</span></a> and the [<code class="docutils literal"><span class="pre">fit()</span></code>] function.</p>
<p>For neural networks used in “feed-forward”, “prediction”, or “inference” mode (all terms for the same
thing: running a trained network), the input arguments are the
input data, and the weights of the neural network that were learned during training.</p>
<p>To manually execute a set of symbols, you need to create an [<code class="docutils literal"><span class="pre">Executor</span></code>] object,
which is typically constructed by calling the [<code class="docutils literal"><span class="pre">simpleBind(<parameters>)</span></code>] method on a symbol.</p>
</div>
<div class="section" id="multiple-outputs">
<span id="multiple-outputs"></span><h2>Multiple Outputs<a class="headerlink" href="#multiple-outputs" title="Permalink to this headline"></a></h2>
<p>To group the symbols together, use the <a class="reference external" href="#mxnet.symbol.Group">mxnet.symbol.Group</a> function.</p>
<div class="highlight-scala"><div class="highlight"><pre><span></span> <span class="n">scala</span><span class="o">></span> <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">data</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Variable</span><span class="o">(</span><span class="s">"data"</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">fc1</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">FullyConnected</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"fc1"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">data</span><span class="o">,</span> <span class="s">"num_hidden"</span> <span class="o">-></span> <span class="mi">128</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">act1</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Activation</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"relu1"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">fc1</span><span class="o">,</span> <span class="s">"act_type"</span> <span class="o">-></span> <span class="s">"relu"</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">fc2</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">FullyConnected</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"fc2"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">act1</span><span class="o">,</span> <span class="s">"num_hidden"</span> <span class="o">-></span> <span class="mi">64</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">net</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">SoftmaxOutput</span><span class="o">(</span><span class="n">name</span> <span class="k">=</span> <span class="s">"out"</span><span class="o">)()(</span><span class="nc">Map</span><span class="o">(</span><span class="s">"data"</span> <span class="o">-></span> <span class="n">fc2</span><span class="o">))</span>
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">group</span> <span class="k">=</span> <span class="nc">Symbol</span><span class="o">.</span><span class="nc">Group</span><span class="o">(</span><span class="n">fc1</span><span class="o">,</span> <span class="n">net</span><span class="o">)</span>
<span class="n">scala</span><span class="o">></span> <span class="n">group</span><span class="o">.</span><span class="n">listOutputs</span><span class="o">()</span>
<span class="nc">IndexedSeq</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span> <span class="k">=</span> <span class="nc">ArrayBuffer</span><span class="o">(</span><span class="n">fc1_output</span><span class="o">,</span> <span class="n">out_output</span><span class="o">)</span>
</pre></div>
</div>
<p>After you get the <code class="docutils literal"><span class="pre">group</span></code>, you can bind on <code class="docutils literal"><span class="pre">group</span></code> instead.
The resulting executor will have two outputs, one for fc1_output and one for softmax_output.</p>
</div>
<div class="section" id="next-steps">
<span id="next-steps"></span><h2>Next Steps<a class="headerlink" href="#next-steps" title="Permalink to this headline"></a></h2>
<ul class="simple">
<li>See <a class="reference internal" href="io.html"><span class="doc">IO Data Loading API</span></a> for parsing and loading data.</li>
<li>See <a class="reference internal" href="ndarray.html"><span class="doc">NDArray API</span></a> for vector/matrix/tensor operations.</li>
<li>See <a class="reference internal" href="kvstore.html"><span class="doc">KVStore API</span></a> for multi-GPU and multi-host distributed training.</li>
</ul>
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</div>
</div>
</div>
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<h3><a href="../../index.html">Table Of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">MXNet Scala Symbolic API</a><ul>
<li><a class="reference internal" href="#how-to-compose-symbols">How to Compose Symbols</a></li>
<li><a class="reference internal" href="#symbol-attributes">Symbol Attributes</a></li>
<li><a class="reference internal" href="#serialization">Serialization</a></li>
<li><a class="reference internal" href="#executing-symbols">Executing Symbols</a></li>
<li><a class="reference internal" href="#multiple-outputs">Multiple Outputs</a></li>
<li><a class="reference internal" href="#next-steps">Next Steps</a></li>
</ul>
</li>
</ul>
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Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), <strong>sponsored by the <i>Apache Incubator</i></strong>. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
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Apache MXNet, MXNet, Apache, the Apache feather, and the Apache MXNet project logo are either registered trademarks or trademarks of the Apache Software Foundation."
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