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* initial setup and rename "how to" to "setup" * move API to main nav * move api to main nav * add get starated, rework nav order * rename to install move mds out of install section * update api nav and home page * add install docs and python qs updates * python get started work * remove c and obj c for now * move java, python, and obj-c docs under api folder * move java api html to iframe (ugh) * remove api docs w/o details, move api text getstar * remove api docs wo detail updates get started * remvoe iframes * move eco system to main nav * fix api buttons * added more examples moved intro to ORT * fix links * fix get started titles * fix get started titles * fix more links * fix more links * more link fixes * fix nav remove inferencing and training subnav * fix top nav remove inference and training nav * fix title * fix tutorials nav hierarchy * fix python api button * add tenorflow keras example * fix quickstart toc * add imports fix spacing * fix links * update nav and python get started page * move ort training example, add coming soon for iot * update C# get started * fix spacing on quantization * Add some js get started content * fix formatting * fix typo * removed onnx-pytorch and onnx-tf * updated pip install torch and added links iot page * added pytorch tutorial heirarchy * updated web to docs soon added release blog link * add web link
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<meta charset="utf-8" />
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<title>Metadata — ONNX Runtime 1.7.0 documentation</title>
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<link rel="index" title="Index" href="../genindex.html" />
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<link rel="next" title="Profile the execution of a simple model" href="plot_profiling.html" />
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<div class="body" role="main">
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<div class="sphx-glr-download-link-note admonition note">
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<p class="admonition-title">Note</p>
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<p>Click <a class="reference internal" href="#sphx-glr-download-auto-examples-plot-metadata-py"><span class="std std-ref">here</span></a>
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to download the full example code</p>
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</div>
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<div class="sphx-glr-example-title section" id="metadata">
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<span id="sphx-glr-auto-examples-plot-metadata-py"></span><h1>Metadata<a class="headerlink" href="#metadata" title="Permalink to this headline">¶</a></h1>
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<p>ONNX format contains metadata related to how the
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model was produced. It is useful when the model
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is deployed to production to keep track of which
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instance was used at a specific time.
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Let’s see how to do that with a simple
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logistic regression model trained with
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<em>scikit-learn</em> and converted with <em>sklearn-onnx</em>.</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">onnxruntime.datasets</span> <span class="kn">import</span> <span class="n">get_example</span>
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<span class="n">example</span> <span class="o">=</span> <span class="n">get_example</span><span class="p">(</span><span class="s2">"logreg_iris.onnx"</span><span class="p">)</span>
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<span class="kn">import</span> <span class="nn">onnx</span>
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<span class="n">model</span> <span class="o">=</span> <span class="n">onnx</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">example</span><span class="p">)</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"doc_string=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">doc_string</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"domain=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">domain</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"ir_version=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">ir_version</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"metadata_props=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">metadata_props</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"model_version=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">model_version</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"producer_name=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">producer_name</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"producer_version=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">producer_version</span><span class="p">))</span>
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</pre></div>
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</div>
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<p class="sphx-glr-script-out">Out:</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>doc_string=
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domain=onnxml
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ir_version=3
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metadata_props=[]
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model_version=0
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producer_name=OnnxMLTools
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producer_version=1.2.0.0116
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</pre></div>
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</div>
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<p>With <em>ONNX Runtime</em>:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">onnxruntime</span> <span class="kn">import</span> <span class="n">InferenceSession</span>
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<span class="n">sess</span> <span class="o">=</span> <span class="n">InferenceSession</span><span class="p">(</span><span class="n">example</span><span class="p">)</span>
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<span class="n">meta</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">get_modelmeta</span><span class="p">()</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"custom_metadata_map=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">meta</span><span class="o">.</span><span class="n">custom_metadata_map</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"description=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">meta</span><span class="o">.</span><span class="n">description</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"domain=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">meta</span><span class="o">.</span><span class="n">domain</span><span class="p">,</span> <span class="n">meta</span><span class="o">.</span><span class="n">domain</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"graph_name=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">meta</span><span class="o">.</span><span class="n">graph_name</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"producer_name=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">meta</span><span class="o">.</span><span class="n">producer_name</span><span class="p">))</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"version=</span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">meta</span><span class="o">.</span><span class="n">version</span><span class="p">))</span>
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</pre></div>
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</div>
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<p class="sphx-glr-script-out">Out:</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>custom_metadata_map={}
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description=
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domain=onnxml
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graph_name=3c59201b940f410fa29dc71ea9d5767d
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producer_name=OnnxMLTools
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version=0
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</pre></div>
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<p><a class="reference download internal" download="" href="../downloads/932fe1ee7f48f55a6155d2f378bc85a0/plot_metadata.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_metadata.py</span></code></a></p>
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