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<div class="section" id="executor-and-executor-manager">
<span id="executor-and-executor-manager"></span><h1>Executor and Executor Manager<a class="headerlink" href="#executor-and-executor-manager" title="Permalink to this headline"></a></h1>
<p>The executor and executor manager are internal classes for managing symbolic
graph execution. This document is only intended for reference for advanced users.</p>
<div class="section" id="executor">
<span id="executor"></span><h2>Executor<a class="headerlink" href="#executor" title="Permalink to this headline"></a></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%"/>
<col width="90%"/>
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#mxnet.executor.Executor" title="mxnet.executor.Executor"><code class="xref py py-obj docutils literal"><span class="pre">Executor</span></code></a></td>
<td>Executor is the object providing efficient symbolic graph execution and optimization.</td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="executor-manager">
<span id="executor-manager"></span><h2>Executor Manager<a class="headerlink" href="#executor-manager" title="Permalink to this headline"></a></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%"/>
<col width="90%"/>
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<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#mxnet.executor_manager.DataParallelExecutorGroup" title="mxnet.executor_manager.DataParallelExecutorGroup"><code class="xref py py-obj docutils literal"><span class="pre">DataParallelExecutorGroup</span></code></a></td>
<td>A group of executors living on different devices, for data parallelization.</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#mxnet.executor_manager.DataParallelExecutorManager" title="mxnet.executor_manager.DataParallelExecutorManager"><code class="xref py py-obj docutils literal"><span class="pre">DataParallelExecutorManager</span></code></a></td>
<td>Helper class to manage multiple executors for data parallelism.</td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="api-reference">
<span id="api-reference"></span><h2>API Reference<a class="headerlink" href="#api-reference" title="Permalink to this headline"></a></h2>
<script src="../../_static/js/auto_module_index.js" type="text/javascript"></script><span class="target" id="module-mxnet.executor"></span><p>Symbolic Executor component of MXNet.</p>
<dl class="class">
<dt id="mxnet.executor.Executor">
<em class="property">class </em><code class="descclassname">mxnet.executor.</code><code class="descname">Executor</code><span class="sig-paren">(</span><em>handle</em>, <em>symbol</em>, <em>ctx</em>, <em>grad_req</em>, <em>group2ctx</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor.html#Executor"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor.Executor" title="Permalink to this definition"></a></dt>
<dd><p>Executor is the object providing efficient symbolic graph execution and optimization.</p>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># typical approach to create an executor is to bind symbol</span>
<span class="gp">>>> </span><span class="n">a</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'a'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">b</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'b'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">c</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
<span class="gp">>>> </span><span class="n">texec</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">bind</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(),</span> <span class="p">{</span><span class="s1">'a'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">]),</span> <span class="s1">'b'</span><span class="p">:</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">])})</span>
</pre></div>
</div>
<dl class="method">
<dt id="mxnet.executor.Executor.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>is_train=False</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor.html#Executor.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor.Executor.forward" title="Permalink to this definition"></a></dt>
<dd><p>Calculate the outputs specified by the bound symbol.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>is_train</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether this forward is for evaluation purpose. If True,
a backward call is expected to follow.</li>
<li><strong>**kwargs</strong> – Additional specification of input arguments.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># doing forward by specifying data</span>
<span class="gp">>>> </span><span class="n">texec</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">mydata</span><span class="p">)</span>
<span class="gp">>>> </span><span class="c1"># doing forward by not specifying things, but copy to the executor before hand</span>
<span class="gp">>>> </span><span class="n">mydata</span><span class="o">.</span><span class="n">copyto</span><span class="p">(</span><span class="n">texec</span><span class="o">.</span><span class="n">arg_dict</span><span class="p">[</span><span class="s1">'data'</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">texec</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="gp">>>> </span><span class="c1"># doing forward by specifying data and get outputs</span>
<span class="gp">>>> </span><span class="n">outputs</span> <span class="o">=</span> <span class="n">texec</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">mydata</span><span class="p">)</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">outputs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">())</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor.Executor.backward">
<code class="descname">backward</code><span class="sig-paren">(</span><em>out_grads=None</em>, <em>is_train=True</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor.html#Executor.backward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor.Executor.backward" title="Permalink to this definition"></a></dt>
<dd><p>Do backward pass to get the gradient of arguments.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>out_grads</strong> (<a class="reference internal" href="../ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em> or </em><em>list of NDArray</em><em> or </em><em>dict of str to NDArray</em><em>, </em><em>optional</em>) – Gradient on the outputs to be propagated back.
This parameter is only needed when bind is called
on outputs that are not a loss function.</li>
<li><strong>is_train</strong> (<em>bool</em><em>, </em><em>default True</em>) – Whether this backward is for training or inference. Note that in rare
cases you want to call backward with is_train=False to get gradient
during inference.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># Example for binding on loss function symbol, which gives the loss value of the model.</span>
<span class="gp">>>> </span><span class="c1"># Equivalently it gives the head gradient for backward pass.</span>
<span class="gp">>>> </span><span class="c1"># In this example the built-in SoftmaxOutput is used as loss function.</span>
<span class="gp">>>> </span><span class="c1"># MakeLoss can be used to define customized loss function symbol.</span>
<span class="gp">>>> </span><span class="n">net</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'data'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">net</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">FullyConnected</span><span class="p">(</span><span class="n">net</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'fc'</span><span class="p">,</span> <span class="n">num_hidden</span><span class="o">=</span><span class="mi">6</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">net</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Activation</span><span class="p">(</span><span class="n">net</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'relu'</span><span class="p">,</span> <span class="n">act_type</span><span class="o">=</span><span class="s2">"relu"</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">net</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">SoftmaxOutput</span><span class="p">(</span><span class="n">net</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'softmax'</span><span class="p">)</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">args</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'data'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">)),</span> <span class="s1">'fc_weight'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">6</span><span class="p">,</span> <span class="mi">4</span><span class="p">)),</span>
<span class="gp">>>> </span> <span class="s1">'fc_bias'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">)),</span> <span class="s1">'softmax_label'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">1</span><span class="p">))}</span>
<span class="gp">>>> </span><span class="n">args_grad</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'fc_weight'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">6</span><span class="p">,</span> <span class="mi">4</span><span class="p">)),</span> <span class="s1">'fc_bias'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">6</span><span class="p">))}</span>
<span class="gp">>>> </span><span class="n">texec</span> <span class="o">=</span> <span class="n">net</span><span class="o">.</span><span class="n">bind</span><span class="p">(</span><span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(),</span> <span class="n">args</span><span class="o">=</span><span class="n">args</span><span class="p">,</span> <span class="n">args_grad</span><span class="o">=</span><span class="n">args_grad</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">out</span> <span class="o">=</span> <span class="n">texec</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="gp">>>> </span><span class="nb">print</span> <span class="n">out</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span>
<span class="go">[[ 0.00378404 0.07600445 0.07600445 0.07600445 0.20660152 0.5616011 ]]</span>
<span class="gp">>>> </span><span class="n">texec</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">texec</span><span class="o">.</span><span class="n">grad_arrays</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">())</span>
<span class="go">[[ 0.00378404 0.00378404 0.00378404 0.00378404]</span>
<span class="go"> [-0.92399555 -0.92399555 -0.92399555 -0.92399555]</span>
<span class="go"> [ 0.07600445 0.07600445 0.07600445 0.07600445]</span>
<span class="go"> [ 0.07600445 0.07600445 0.07600445 0.07600445]</span>
<span class="go"> [ 0.20660152 0.20660152 0.20660152 0.20660152]</span>
<span class="go"> [ 0.5616011 0.5616011 0.5616011 0.5616011 ]]</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="c1"># Example for binding on non-loss function symbol.</span>
<span class="gp">>>> </span><span class="c1"># Here the binding symbol is neither built-in loss function</span>
<span class="gp">>>> </span><span class="c1"># nor customized loss created by MakeLoss.</span>
<span class="gp">>>> </span><span class="c1"># As a result the head gradient is not automatically provided.</span>
<span class="gp">>>> </span><span class="n">a</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'a'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">b</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'b'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="c1"># c is not a loss function symbol</span>
<span class="gp">>>> </span><span class="n">c</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
<span class="gp">>>> </span><span class="n">args</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'a'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">]),</span> <span class="s1">'b'</span><span class="p">:</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">])}</span>
<span class="gp">>>> </span><span class="n">args_grad</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'a'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">)),</span> <span class="s1">'b'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">))}</span>
<span class="gp">>>> </span><span class="n">texec</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">bind</span><span class="p">(</span><span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(),</span> <span class="n">args</span><span class="o">=</span><span class="n">args</span><span class="p">,</span> <span class="n">args_grad</span><span class="o">=</span><span class="n">args_grad</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">out</span> <span class="o">=</span> <span class="n">texec</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">())</span>
<span class="go">[ 4. 7.]</span>
<span class="gp">>>> </span><span class="c1"># out_grads is the head gradient in backward pass.</span>
<span class="gp">>>> </span><span class="c1"># Here we define 'c' as loss function.</span>
<span class="gp">>>> </span><span class="c1"># Then 'out' is passed as head gradient of backward pass.</span>
<span class="gp">>>> </span><span class="n">texec</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">texec</span><span class="o">.</span><span class="n">grad_arrays</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">())</span>
<span class="go">[ 8. 14.]</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">texec</span><span class="o">.</span><span class="n">grad_arrays</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">())</span>
<span class="go">[ 4. 7.]</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor.Executor.set_monitor_callback">
<code class="descname">set_monitor_callback</code><span class="sig-paren">(</span><em>callback</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor.html#Executor.set_monitor_callback"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor.Executor.set_monitor_callback" title="Permalink to this definition"></a></dt>
<dd><p>Install callback for monitor.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>callback</strong> (<em>function</em>) – Takes a string and an NDArrayHandle.</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">def</span> <span class="nf">mon_callback</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="gp">>>> </span> <span class="nb">print</span><span class="p">(</span><span class="s2">"Do your stuff here."</span><span class="p">)</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="n">texe</span><span class="o">.</span><span class="n">set_monitor_callback</span><span class="p">(</span><span class="n">mon_callback</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="attribute">
<dt id="mxnet.executor.Executor.arg_dict">
<code class="descname">arg_dict</code><a class="headerlink" href="#mxnet.executor.Executor.arg_dict" title="Permalink to this definition"></a></dt>
<dd><p>Get dictionary representation of argument arrrays.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>arg_dict</strong> – The dictionary that maps the names of arguments to NDArrays.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">dict of str to NDArray</td>
</tr>
<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body">ValueError : if there are duplicated names in the arguments.</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="attribute">
<dt id="mxnet.executor.Executor.grad_dict">
<code class="descname">grad_dict</code><a class="headerlink" href="#mxnet.executor.Executor.grad_dict" title="Permalink to this definition"></a></dt>
<dd><p>Get dictionary representation of gradient arrays.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>grad_dict</strong> – The dictionary that maps name of arguments to gradient arrays.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">dict of str to NDArray</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="attribute">
<dt id="mxnet.executor.Executor.aux_dict">
<code class="descname">aux_dict</code><a class="headerlink" href="#mxnet.executor.Executor.aux_dict" title="Permalink to this definition"></a></dt>
<dd><p>Get dictionary representation of auxiliary states arrays.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>aux_dict</strong> – The dictionary that maps name of auxiliary states to NDArrays.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">dict of str to NDArray</td>
</tr>
<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body">ValueError : if there are duplicated names in the auxiliary states.</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="attribute">
<dt id="mxnet.executor.Executor.output_dict">
<code class="descname">output_dict</code><a class="headerlink" href="#mxnet.executor.Executor.output_dict" title="Permalink to this definition"></a></dt>
<dd><p>Get dictionary representation of output arrays.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>output_dict</strong> – The dictionary that maps name of output names to NDArrays.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">dict of str to NDArray</td>
</tr>
<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body">ValueError : if there are duplicated names in the outputs.</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor.Executor.copy_params_from">
<code class="descname">copy_params_from</code><span class="sig-paren">(</span><em>arg_params</em>, <em>aux_params=None</em>, <em>allow_extra_params=False</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor.html#Executor.copy_params_from"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor.Executor.copy_params_from" title="Permalink to this definition"></a></dt>
<dd><p>Copy parameters from arg_params, aux_params into executor’s internal array.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>arg_params</strong> (<em>dict of str to NDArray</em>) – Parameters, dict of name to NDArray of arguments.</li>
<li><strong>aux_params</strong> (<em>dict of str to NDArray</em><em>, </em><em>optional</em>) – Parameters, dict of name to NDArray of auxiliary states.</li>
<li><strong>allow_extra_params</strong> (<em>boolean</em><em>, </em><em>optional</em>) – Whether allow extra parameters that are not needed by symbol.
If this is True, no error will be thrown when arg_params or aux_params
contain extra parameters that is not needed by the executor.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Raises:</th><td class="field-body"><p class="first last"><code class="xref py py-exc docutils literal"><span class="pre">ValueError</span></code> – If there is additional parameters in the dict but <code class="docutils literal"><span class="pre">allow_extra_params=False</span></code>.</p>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># set parameters with existing model checkpoint</span>
<span class="gp">>>> </span><span class="n">model_prefix</span> <span class="o">=</span> <span class="s1">'mx_mlp'</span>
<span class="gp">>>> </span><span class="n">sym</span><span class="p">,</span> <span class="n">arg_params</span><span class="p">,</span> <span class="n">aux_params</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">load_checkpoint</span><span class="p">(</span><span class="n">model_prefix</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">texec</span><span class="o">.</span><span class="n">copy_params_from</span><span class="p">(</span><span class="n">arg_params</span><span class="p">,</span> <span class="n">aux_params</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor.Executor.reshape">
<code class="descname">reshape</code><span class="sig-paren">(</span><em>partial_shaping=False</em>, <em>allow_up_sizing=False</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor.html#Executor.reshape"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor.Executor.reshape" title="Permalink to this definition"></a></dt>
<dd><p>Return a new executor with the same symbol and shared memory,
but different input/output shapes.
For runtime reshaping, variable length sequences, etc.
The returned executor shares state with the current one,
and cannot be used in parallel with it.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>partial_shaping</strong> (<em>bool</em>) – Whether to allow changing the shape of unspecified arguments.</li>
<li><strong>allow_up_sizing</strong> (<em>bool</em>) – Whether to allow allocating new ndarrays that’s larger than the original.</li>
<li><strong>kwargs</strong> (<em>dict of string to tuple of int</em>) – New shape for arguments.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>exec</strong> – A new executor that shares memory with self.</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.executor.Executor" title="mxnet.executor.Executor">Executor</a></p>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">a</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'a'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">b</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'b'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">c</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
<span class="gp">>>> </span><span class="n">texec</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">bind</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(),</span> <span class="p">{</span><span class="s1">'a'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">)),</span> <span class="s1">'b'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">))})</span>
<span class="gp">>>> </span><span class="n">new_shape</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'a'</span><span class="p">:</span> <span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="s1">'b'</span><span class="p">:</span> <span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">)}</span>
<span class="gp">>>> </span><span class="n">texec</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">allow_up_sizing</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="n">new_shape</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor.Executor.debug_str">
<code class="descname">debug_str</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor.html#Executor.debug_str"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor.Executor.debug_str" title="Permalink to this definition"></a></dt>
<dd><p>Get a debug string about internal execution plan.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>debug_str</strong> – Debug string of the executor.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">string</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">a</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'a'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">b</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">c</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
<span class="gp">>>> </span><span class="n">texec</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">bind</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(),</span> <span class="p">{</span><span class="s1">'a'</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">]),</span> <span class="s1">'b'</span><span class="p">:</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">])})</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">texec</span><span class="o">.</span><span class="n">debug_str</span><span class="p">())</span>
<span class="go">Symbol Outputs:</span>
<span class="go"> output[0]=_plus0(0)</span>
<span class="go">Variable:a</span>
<span class="go">--------------------</span>
<span class="go">Op:_mul_scalar, Name=_mulscalar0</span>
<span class="go">Inputs:</span>
<span class="go"> arg[0]=a(0) version=0</span>
<span class="go">Attrs:</span>
<span class="go"> scalar=2</span>
<span class="go">--------------------</span>
<span class="go">Op:sin, Name=sin0</span>
<span class="go">Inputs:</span>
<span class="go"> arg[0]=a(0) version=0</span>
<span class="go">--------------------</span>
<span class="go">Op:elemwise_add, Name=_plus0</span>
<span class="go">Inputs:</span>
<span class="go"> arg[0]=_mulscalar0(0)</span>
<span class="go"> arg[1]=sin0(0)</span>
<span class="go">Total 0 MB allocated</span>
<span class="go">Total 11 TempSpace resource requested</span>
</pre></div>
</div>
</dd></dl>
</dd></dl>
<span class="target" id="module-mxnet.executor_manager"></span><p>Executor manager.</p>
<dl class="class">
<dt id="mxnet.executor_manager.DataParallelExecutorGroup">
<em class="property">class </em><code class="descclassname">mxnet.executor_manager.</code><code class="descname">DataParallelExecutorGroup</code><span class="sig-paren">(</span><em>sym</em>, <em>arg_names</em>, <em>param_names</em>, <em>ctx</em>, <em>slices</em>, <em>train_data</em>, <em>shared_group=None</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorGroup"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorGroup" title="Permalink to this definition"></a></dt>
<dd><p>A group of executors living on different devices, for data parallelization.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>sym</strong> (<a class="reference internal" href="../symbol/symbol.html#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The network configuration.</li>
<li><strong>arg_names</strong> (<em>list of str</em>) – Equals <cite>sym.list_arguments()</cite></li>
<li><strong>param_names</strong> (<em>list of str</em>) – List of names of all trainable parameters.</li>
<li><strong>ctx</strong> (<em>list of Context</em>) – List of devices for training (data parallelization).</li>
<li><strong>slices</strong> (<em>list of int</em>) – Describes how the data parallelization splits data into different devices.</li>
<li><strong>train_data</strong> (<a class="reference internal" href="../io/io.html#mxnet.io.DataIter" title="mxnet.io.DataIter"><em>DataIter</em></a><em> (or </em><a class="reference internal" href="../io/io.html#mxnet.io.DataBatch" title="mxnet.io.DataBatch"><em>DataBatch</em></a><em>)</em>) – The dataset for training. It could be any object with <cite>provide_data</cite> and
<cite>provide_label</cite> properties. Loading of actual data is not necessarily needed
at this stage.</li>
<li><strong>shared_grop</strong> (<a class="reference internal" href="#mxnet.executor_manager.DataParallelExecutorGroup" title="mxnet.executor_manager.DataParallelExecutorGroup"><em>DataParallelExecutorGroup</em></a>) – An existing executor group, if to share parameters with it.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorGroup.load_data_batch">
<code class="descname">load_data_batch</code><span class="sig-paren">(</span><em>data_batch</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorGroup.load_data_batch"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorGroup.load_data_batch" title="Permalink to this definition"></a></dt>
<dd><p>Load data and labels into arrays.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorGroup.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>is_train=False</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorGroup.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorGroup.forward" title="Permalink to this definition"></a></dt>
<dd><p>Perform a forward pass on each executor.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorGroup.backward">
<code class="descname">backward</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorGroup.backward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorGroup.backward" title="Permalink to this definition"></a></dt>
<dd><p>Perform a backward pass on each executor.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorGroup.update_metric">
<code class="descname">update_metric</code><span class="sig-paren">(</span><em>metric</em>, <em>labels</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorGroup.update_metric"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorGroup.update_metric" title="Permalink to this definition"></a></dt>
<dd><p>Update evaluation metric with label and current outputs.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="mxnet.executor_manager.DataParallelExecutorManager">
<em class="property">class </em><code class="descclassname">mxnet.executor_manager.</code><code class="descname">DataParallelExecutorManager</code><span class="sig-paren">(</span><em>symbol</em>, <em>ctx</em>, <em>train_data</em>, <em>arg_names</em>, <em>param_names</em>, <em>aux_names</em>, <em>work_load_list=None</em>, <em>logger=None</em>, <em>sym_gen=None</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager" title="Permalink to this definition"></a></dt>
<dd><p>Helper class to manage multiple executors for data parallelism.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>symbol</strong> (<a class="reference internal" href="../symbol/symbol.html#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Output symbol.</li>
<li><strong>ctx</strong> (<em>list of Context</em>) – Devices to run on.</li>
<li><strong>param_names</strong> (<em>list of str</em>) – Name of all trainable parameters of the network.</li>
<li><strong>arg_names</strong> (<em>list of str</em>) – Name of all arguments of the network.</li>
<li><strong>aux_names</strong> (<em>list of str</em>) – Name of all auxiliary states of the network.</li>
<li><strong>train_data</strong> (<a class="reference internal" href="../io/io.html#mxnet.io.DataIter" title="mxnet.io.DataIter"><em>DataIter</em></a>) – Training data iterator.</li>
<li><strong>work_load_list</strong> (<em>list of float</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – The list of work load for different devices,
in the same order as ctx.</li>
<li><strong>logger</strong> (<em>logging logger</em>) – When not specified, default logger will be used.</li>
<li><strong>sym_gen</strong> (<em>A function that generate new Symbols depending on different</em>) – input shapes. Used only for bucketing.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.install_monitor">
<code class="descname">install_monitor</code><span class="sig-paren">(</span><em>monitor</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager.install_monitor"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.install_monitor" title="Permalink to this definition"></a></dt>
<dd><p>Install monitor on all executors.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.set_params">
<code class="descname">set_params</code><span class="sig-paren">(</span><em>arg_params</em>, <em>aux_params</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager.set_params"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.set_params" title="Permalink to this definition"></a></dt>
<dd><p>Set parameter and aux values.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>arg_params</strong> (<em>list of NDArray</em>) – Source parameter arrays</li>
<li><strong>aux_params</strong> (<em>list of NDArray</em>) – Source aux arrays.</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.copy_to">
<code class="descname">copy_to</code><span class="sig-paren">(</span><em>arg_params</em>, <em>aux_params</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager.copy_to"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.copy_to" title="Permalink to this definition"></a></dt>
<dd><p>Copy data from each executor to <code class="docutils literal"><span class="pre">`arg_params</span></code> and <code class="docutils literal"><span class="pre">aux_params</span></code>.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>arg_params</strong> (<em>list of NDArray</em>) – Target parameter arrays.</li>
<li><strong>aux_params</strong> (<em>list of NDArray</em>) – Target aux arrays.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Notes</p>
<ul class="simple">
<li>This function will inplace update the NDArrays in arg_params and aux_params.</li>
</ul>
</dd></dl>
<dl class="attribute">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.param_arrays">
<code class="descname">param_arrays</code><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.param_arrays" title="Permalink to this definition"></a></dt>
<dd><p>Shared parameter arrays.</p>
</dd></dl>
<dl class="attribute">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.grad_arrays">
<code class="descname">grad_arrays</code><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.grad_arrays" title="Permalink to this definition"></a></dt>
<dd><p>Shared gradient arrays.</p>
</dd></dl>
<dl class="attribute">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.aux_arrays">
<code class="descname">aux_arrays</code><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.aux_arrays" title="Permalink to this definition"></a></dt>
<dd><p>Shared aux states.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.load_data_batch">
<code class="descname">load_data_batch</code><span class="sig-paren">(</span><em>data_batch</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager.load_data_batch"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.load_data_batch" title="Permalink to this definition"></a></dt>
<dd><p>Load data and labels into arrays.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>is_train=False</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.forward" title="Permalink to this definition"></a></dt>
<dd><p>Run forward on the current executor.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.backward">
<code class="descname">backward</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager.backward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.backward" title="Permalink to this definition"></a></dt>
<dd><p>Run backward on the current executor.</p>
</dd></dl>
<dl class="method">
<dt id="mxnet.executor_manager.DataParallelExecutorManager.update_metric">
<code class="descname">update_metric</code><span class="sig-paren">(</span><em>metric</em>, <em>labels</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/executor_manager.html#DataParallelExecutorManager.update_metric"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.executor_manager.DataParallelExecutorManager.update_metric" title="Permalink to this definition"></a></dt>
<dd><p>Update metric with the current executor.</p>
</dd></dl>
</dd></dl>
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<li><a class="reference internal" href="#executor">Executor</a></li>
<li><a class="reference internal" href="#executor-manager">Executor Manager</a></li>
<li><a class="reference internal" href="#api-reference">API Reference</a></li>
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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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"Copyright © 2017-2018, The Apache Software Foundation
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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