deploy: 5b50ffda54ac45ad481bbfd525f4c07880779eb8

_sources/model-export/export-onnx.rst.txt

@@ -3,6 +3,15 @@ Export to ONNX
 
 In this section, we describe how to export models to `ONNX`_.
 
+.. hint::
+
+   Before you continue, please run:
+
+    .. code-block:: bash
+
+        pip install onnx
+
+
 In each recipe, there is a file called ``export-onnx.py``, which is used
 to export trained models to `ONNX`_.
 

model-export/export-onnx.html

@@ -98,6 +98,15 @@
   <section id="export-to-onnx">
 <h1>Export to ONNX<a class="headerlink" href="#export-to-onnx" title="Permalink to this heading"></a></h1>
 <p>In this section, we describe how to export models to <a class="reference external" href="https://github.com/onnx/onnx">ONNX</a>.</p>
+<div class="admonition hint">
+<p class="admonition-title">Hint</p>
+<p>Before you continue, please run:</p>
+<blockquote>
+<div><div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>onnx
+</pre></div>
+</div>
+</div></blockquote>
+</div>
 <p>In each recipe, there is a file called <code class="docutils literal notranslate"><span class="pre">export-onnx.py</span></code>, which is used
 to export trained models to <a class="reference external" href="https://github.com/onnx/onnx">ONNX</a>.</p>
 <p>There is also a file named <code class="docutils literal notranslate"><span class="pre">onnx_pretrained.py</span></code>, which you can use