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  <div class="section" id="executor">
<h1>executor<a class="headerlink" href="#executor" title="Permalink to this headline">¶</a></h1>
<div class="section" id="id1">
<h2>Executor<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.fluid.executor.</code><code class="descname">Executor</code><span class="sig-paren">(</span><em>places</em><span class="sig-paren">)</span></dt>
<dd><dl class="method">
<dt>
<code class="descname">run</code><span class="sig-paren">(</span><em>program=None</em>, <em>feed=None</em>, <em>fetch_list=None</em>, <em>feed_var_name='feed'</em>, <em>fetch_var_name='fetch'</em>, <em>scope=None</em>, <em>return_numpy=True</em>, <em>use_program_cache=False</em><span class="sig-paren">)</span></dt>
<dd><p>Run program by this Executor. Feed data by feed map, fetch result by fetch_list.</p>
<p>Python executor takes a program, add feed operators and fetch operators to this program according
to feed map and fetch_list. Feed map provides input data for the program. fetch_list provides
the variables(or names) that user want to get after program run. Note: the executor will run all
operators in the program but not only the operators dependent by the fetch_list</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>program</strong> &#8211; the program that need to run, if not provied, then default_main_program will be used.</li>
<li><strong>feed</strong> &#8211; feed variable map, e.g. {&#8220;image&#8221;: ImageData, &#8220;label&#8221;: LableData}</li>
<li><strong>fetch_list</strong> &#8211; a list of variable or variable names that user want to get, run will return them according</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p>to this list.
:param feed_var_name: the name for the input variable of feed Operator.
:param fetch_var_name: the name for the output variable of feed Operator.
:param scope: the scope used to run this program, you can switch it to different scope. default is global_scope
:param return_numpy: if convert the fetched tensor to numpy
:param use_program_cache: set use_program_cache to true if program not changed compare to the last step.
:return: result according to fetch_list.</p>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="global-scope">
<h2>global_scope<a class="headerlink" href="#global-scope" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.fluid.executor.</code><code class="descname">global_scope</code><span class="sig-paren">(</span><span class="sig-paren">)</span></dt>
<dd></dd></dl>

</div>
<div class="section" id="scope-guard">
<h2>scope_guard<a class="headerlink" href="#scope-guard" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.fluid.executor.</code><code class="descname">scope_guard</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwds</em><span class="sig-paren">)</span></dt>
<dd></dd></dl>

</div>
<div class="section" id="switch-scope">
<h2>switch_scope<a class="headerlink" href="#switch-scope" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.fluid.executor.</code><code class="descname">switch_scope</code><span class="sig-paren">(</span><em>scope</em><span class="sig-paren">)</span></dt>
<dd></dd></dl>

</div>
</div>


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