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 <div class="section" id="mxnet-perl-symbolic-api">
 <span id="mxnet-perl-symbolic-api"></span><h1>MXNet Perl Symbolic API<a class="headerlink" href="#mxnet-perl-symbolic-api" title="Permalink to this headline">¶</a></h1>
 <p>Topics:</p>
 <ul class="simple">
 <li><a class="reference external" href="#how-to-compose-symbols">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="#multiple-outputs">Multiple Outputs</a> explains how to configure multiple outputs.</li>
 </ul>
 <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-perl"><div class="highlight"><pre><span></span>pdl> use AI::MXNet qw(mx)
 pdl> $data = mx->symbold->Variable("data")
 pdl> $fc1  = mx->symbol->FullyConnected(data => $data, name => "fc1", num_hidden" -> 128)
 pdl> $act1 = mx->symbol->Activation(data => $fc1, name => "relu1", act_type => "relu")
 pdl> $fc2 =  mx->symbol->FullyConnected(data => $act1, name => "fc2", num_hidden => 64)
 pdl> $net =  mx->symbol->SoftmaxOutput(data => $fc2, name => "out")
 </pre></div>
 </div>
 <p>The basic arithmetic operators (plus, minus, div, multiplication) are overloaded for
 <em>element-wise operations</em> of symbols.</p>
 <p>The following example creates a computation graph that adds two inputs together.</p>
 <div class="highlight-perl"><div class="highlight"><pre><span></span><span class="n">pdl</span><span class="o">></span> <span class="k">use</span> <span class="nn">AI::MXNet</span> <span class="sx">qw(mx)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$a</span> <span class="o">=</span>  <span class="nn">mx</span><span class="o">-></span><span class="nn">symbol</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"a"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$b</span> <span class="o">=</span>  <span class="nn">mx</span><span class="o">-></span><span class="nn">symbol</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"b"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$c</span> <span class="o">=</span> <span class="nv">$a</span> <span class="o">+</span> <span class="nv">$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 hash when you create a symbol.</p>
 <div class="highlight-perl"><div class="highlight"><pre><span></span><span class="nv">$data</span> <span class="o">=</span>  <span class="nn">mx</span><span class="o">-></span><span class="nn">symbol</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"data"</span><span class="p">,</span> <span class="n">attr</span> <span class="o">=></span> <span class="p">{</span> <span class="n">mood</span> <span class="o">=></span> <span class="s">"angry"</span> <span class="p">})</span>
 <span class="nv">$op</span>   <span class="o">=</span>  <span class="nn">mx</span><span class="o">-></span><span class="nn">symbol</span><span class="o">-></span><span class="n">Convolution</span><span class="p">(</span><span class="n">data</span> <span class="o">=></span> <span class="nv">$data</span><span class="p">,</span> <span class="n">kernel</span> <span class="o">=></span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">num_filter</span> <span class="o">=></span> <span class="mi">1</span><span class="p">,</span> <span class="n">attr</span> <span class="o">=></span> <span class="p">{</span> <span class="n">mood</span> <span class="o">=></span> <span class="s">"so so"</span> <span class="p">})</span>
 </pre></div>
 </div>
 <p>For proper communication with the C++ backend, both the key and values of the attribute dictionary should be strings. To retrieve the attributes, use <code class="docutils literal"><span class="pre">->attr($key)</span></code>:</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span>    $data->attr("mood")
 </pre></div>
 </div>
 <p>To attach attributes, you can use <code class="docutils literal"><span class="pre">AI::MXNet::AttrScope</span></code>. <code class="docutils literal"><span class="pre">AI::MXNet::AttrScopeAttrScope</span></code> automatically adds
 the specified attributes to all of the symbols created within that scope.
 The user can also inherit this object to change naming behavior. For example:</p>
 <div class="highlight-perl"><div class="highlight"><pre><span></span><span class="k">use</span> <span class="nn">AI::MXNet</span> <span class="sx">qw(mx)</span><span class="p">;</span>
 <span class="k">use</span> <span class="nn">Test::More</span> <span class="n">tests</span> <span class="o">=></span> <span class="mi">3</span><span class="p">;</span>
 <span class="k">my</span> <span class="p">(</span><span class="nv">$data</span><span class="p">,</span> <span class="nv">$gdata</span><span class="p">);</span>
 <span class="p">{</span>
     <span class="nb">local</span><span class="p">(</span><span class="nv">$</span><span class="nn">mx::</span><span class="nv">AttrScope</span><span class="p">)</span> <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="n">AttrScope</span><span class="p">(</span><span class="n">group</span><span class="o">=></span><span class="mi">4</span><span class="p">,</span> <span class="n">data</span><span class="o">=></span><span class="s">'great'</span><span class="p">);</span>
     <span class="nv">$data</span> <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"data"</span><span class="p">,</span> <span class="n">attr</span> <span class="o">=></span> <span class="p">{</span> <span class="n">dtype</span> <span class="o">=></span> <span class="s">"data"</span><span class="p">,</span> <span class="n">group</span> <span class="o">=></span> <span class="s">"1"</span> <span class="p">});</span>
     <span class="nv">$gdata</span> <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"data2"</span><span class="p">);</span>
 <span class="p">}</span>
 <span class="n">ok</span><span class="p">(</span><span class="nv">$gdata</span><span class="o">-></span><span class="n">attr</span><span class="p">(</span><span class="s">"group"</span><span class="p">)</span> <span class="o">==</span> <span class="mi">4</span><span class="p">);</span>
 <span class="n">ok</span><span class="p">(</span><span class="nv">$data</span><span class="o">-></span><span class="n">attr</span><span class="p">(</span><span class="s">"group"</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">);</span>

 <span class="k">my</span> <span class="nv">$exceedScopeData</span> <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"data3"</span><span class="p">);</span>
 <span class="n">ok</span><span class="p">((</span><span class="ow">not</span> <span class="nb">defined</span> <span class="nv">$exceedScopeData</span><span class="o">-></span><span class="n">attr</span><span class="p">(</span><span class="s">"group"</span><span class="p">)),</span> <span class="s">"No group attr in global attr scope"</span><span class="p">);</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">mx->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">AI::MXNet::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">$symbol->tojson</span></code>.</p>
 <p>The following example shows how to save a symbol to an S3 bucket, load it back, and compare two symbols using a JSON string.</p>
 <div class="highlight-perl"><div class="highlight"><pre><span></span><span class="n">pdl</span><span class="o">></span> <span class="k">use</span> <span class="nn">AI::MXNet</span> <span class="sx">qw(mx)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$a</span> <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"a"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$b</span> <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"b"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$c</span> <span class="o">=</span> <span class="nv">$a</span> <span class="o">+</span> <span class="nv">$b</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$c</span><span class="o">-></span><span class="n">save</span><span class="p">(</span><span class="s">"s3://my-bucket/symbol-c.json"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$c2</span> <span class="o">=</span> <span class="nv">$c</span><span class="o">-></span><span class="n">load</span><span class="p">(</span><span class="s">"s3://my-bucket/symbol-c.json"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="n">ok</span><span class="p">(</span><span class="nv">$c</span><span class="o">-></span><span class="n">tojson</span> <span class="ow">eq</span> <span class="nv">$c2</span><span class="o">-></span><span class="n">tojson</span><span class="p">)</span>
 <span class="n">ok</span> <span class="mi">1</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="module.html"><em>AI::MXNet::Module package</em></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">AI::MXNet::Executor</span></code>] object,
 which is typically constructed by calling the [<code class="docutils literal"><span class="pre">simple_bind(<parameters>)</span></code>] method on a AI::MXNet::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">AI::MXNet::Symbol->Group</a> function.</p>
 <div class="highlight-perl"><div class="highlight"><pre><span></span><span class="n">pdl</span><span class="o">></span> <span class="k">use</span> <span class="nn">AI::MXNet</span> <span class="sx">qw(mx)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="k">use</span> <span class="nn">Data::Dumper</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$data</span>  <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Variable</span><span class="p">(</span><span class="s">"data"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$fc1</span>   <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">FullyConnected</span><span class="p">(</span><span class="nv">$data</span><span class="p">,</span> <span class="n">name</span> <span class="o">=></span> <span class="s">"fc1"</span><span class="p">,</span> <span class="n">num_hidden</span> <span class="o">=></span> <span class="mi">128</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$act1</span>  <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Activation</span><span class="p">(</span><span class="nv">$fc1</span><span class="p">,</span> <span class="n">name</span> <span class="o">=></span> <span class="s">"relu1"</span><span class="p">,</span> <span class="n">act_type</span> <span class="o">=></span> <span class="s">"relu"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$fc2</span>   <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">FullyConnected</span><span class="p">(</span><span class="nv">$act1</span><span class="p">,</span> <span class="n">name</span> <span class="o">=></span> <span class="s">"fc2"</span><span class="p">,</span> <span class="n">num_hidden</span> <span class="o">=></span> <span class="mi">64</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$net</span>   <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">SoftmaxOutput</span><span class="p">(</span><span class="nv">$fc2</span><span class="p">,</span> <span class="n">name</span> <span class="o">=></span> <span class="s">"softmax"</span><span class="p">)</span>
 <span class="n">pdl</span><span class="o">></span> <span class="nv">$group</span> <span class="o">=</span> <span class="nn">mx</span><span class="o">-></span><span class="nn">sym</span><span class="o">-></span><span class="n">Group</span><span class="p">([</span><span class="nv">$fc1</span><span class="p">,</span> <span class="nv">$net</span><span class="p">])</span>
 <span class="n">pdl</span><span class="o">></span> <span class="k">print</span> <span class="n">Dumper</span><span class="p">(</span><span class="nv">$group</span><span class="o">-></span><span class="n">list_outputs</span><span class="p">())</span>
 <span class="nv">$VAR1</span> <span class="o">=</span> <span class="p">[</span>
     <span class="s">'fc1_output'</span><span class="p">,</span>
     <span class="s">'softmax_output'</span>
 <span class="p">];</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>
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 <h3><a href="../../index.html">Table Of Contents</a></h3>
 <ul>
 <li><a class="reference internal" href="#">MXNet Perl 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>
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