<spanid="sphx-glr-auto-examples"></span><h1>Gallery of examples<aclass="headerlink"href="#gallery-of-examples"title="Permalink to this headline">¶</a></h1>
<divclass="sphx-glr-thumbcontainer"tooltip="There is no other way to look into one model stored in ONNX format than looking into its node w..."><figureclass="align-default"id="id1">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_pipeline.html#sphx-glr-auto-examples-plot-pipeline-py"><spanclass="std std-ref">Draw a pipeline</span></a></span><aclass="headerlink"href="#id1"title="Permalink to this image">¶</a></p>
<divclass="sphx-glr-thumbcontainer"tooltip="This example demonstrates how to load a model and compute the output for an input vector. It al..."><figureclass="align-default"id="id2">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_load_and_predict.html#sphx-glr-auto-examples-plot-load-and-predict-py"><spanclass="std std-ref">Load and predict with ONNX Runtime and a very simple model</span></a></span><aclass="headerlink"href="#id2"title="Permalink to this image">¶</a></p>
<divclass="sphx-glr-thumbcontainer"tooltip="*ONNX Runtime* extends the `onnx backend API <https://github.com/onnx/onnx/blob/master/docs/Im..."><figureclass="align-default"id="id3">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_backend.html#sphx-glr-auto-examples-plot-backend-py"><spanclass="std std-ref">ONNX Runtime Backend for ONNX</span></a></span><aclass="headerlink"href="#id3"title="Permalink to this image">¶</a></p>
<divclass="sphx-glr-thumbcontainer"tooltip="ONNX format contains metadata related to how the model was produced. It is useful when the mode..."><figureclass="align-default"id="id4">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_metadata.html#sphx-glr-auto-examples-plot-metadata-py"><spanclass="std std-ref">Metadata</span></a></span><aclass="headerlink"href="#id4"title="Permalink to this image">¶</a></p>
<divclass="sphx-glr-thumbcontainer"tooltip="*ONNX Runtime* can profile the execution of the model. This example shows how to interpret the ..."><figureclass="align-default"id="id5">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_profiling.html#sphx-glr-auto-examples-plot-profiling-py"><spanclass="std std-ref">Profile the execution of a simple model</span></a></span><aclass="headerlink"href="#id5"title="Permalink to this image">¶</a></p>
<divclass="sphx-glr-thumbcontainer"tooltip="This example demonstrates an end to end scenario starting with the training of a scikit-learn p..."><figureclass="align-default"id="id6">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_convert_pipeline_vectorizer.html#sphx-glr-auto-examples-plot-convert-pipeline-vectorizer-py"><spanclass="std std-ref">Train, convert and predict with ONNX Runtime</span></a></span><aclass="headerlink"href="#id6"title="Permalink to this image">¶</a></p>
<divclass="sphx-glr-thumbcontainer"tooltip="This example looks into several common situations in which *onnxruntime* does not return the mo..."><figureclass="align-default"id="id7">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_common_errors.html#sphx-glr-auto-examples-plot-common-errors-py"><spanclass="std std-ref">Common errors with onnxruntime</span></a></span><aclass="headerlink"href="#id7"title="Permalink to this image">¶</a></p>
<divclass="sphx-glr-thumbcontainer"tooltip="This example demonstrates an end to end scenario starting with the training of a machine learne..."><figureclass="align-default"id="id8">
<p><spanclass="caption-text"><aclass="reference internal"href="plot_train_convert_predict.html#sphx-glr-auto-examples-plot-train-convert-predict-py"><spanclass="std std-ref">Train, convert and predict with ONNX Runtime</span></a></span><aclass="headerlink"href="#id8"title="Permalink to this image">¶</a></p>