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< li class = "toctree-l2" > < a class = "reference internal" href = "../tutorial.html#step-1-train-a-model-using-your-favorite-framework" > Step 1: Train a model using your favorite framework< / a > < / li >
< li class = "toctree-l2" > < a class = "reference internal" href = "../tutorial.html#step-2-convert-or-export-the-model-into-onnx-format" > Step 2: Convert or export the model into ONNX format< / a > < / li >
< li class = "toctree-l2" > < a class = "reference internal" href = "../tutorial.html#step-3-load-and-run-the-model-using-onnx-runtime" > Step 3: Load and run the model using ONNX Runtime< / a > < / li >
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< li class = "toctree-l2" > < a class = "reference internal" href = "plot_load_and_predict.html" > Load and predict with ONNX Runtime and a very simple model< / a > < / li >
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< li class = "toctree-l2 current" > < a class = "current reference internal" href = "#" > Metadata< / a > < / li >
< li class = "toctree-l2" > < a class = "reference internal" href = "plot_dl_keras.html" > ONNX Runtime for Keras< / a > < / li >
< li class = "toctree-l2" > < a class = "reference internal" href = "plot_convert_pipeline_vectorizer.html" > Train, convert and predict with ONNX Runtime< / a > < / li >
< li class = "toctree-l2" > < a class = "reference internal" href = "plot_common_errors.html" > Common errors with onnxruntime< / a > < / li >
< li class = "toctree-l2" > < a class = "reference internal" href = "plot_train_convert_predict.html" > Train, convert and predict with ONNX Runtime< / a > < / li >
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< div class = "sphx-glr-download-link-note admonition note" >
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< p class = "admonition-title" > Note< / p >
< p > Click < a class = "reference internal" href = "#sphx-glr-download-auto-examples-plot-metadata-py" > < span class = "std std-ref" > here< / span > < / a > to download the full example code< / p >
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< div class = "sphx-glr-example-title section" id = "metadata" >
< span id = "sphx-glr-auto-examples-plot-metadata-py" > < / span > < h1 > Metadata< a class = "headerlink" href = "#metadata" title = "Permalink to this headline" > ¶< / a > < / h1 >
< p > ONNX format contains metadata related to how the
model was produced. It is useful when the model
is deployed to production to keep track of which
instance was used at a specific time.
Let’
logistic regression model trained with
< 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 = "k" > 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 >
< span class = "kn" > import< / span > < span class = "nn" > onnx< / span >
< 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 >
< 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 >
< 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 >
< 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 >
< 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 >
< 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 >
< 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 >
< / div >
< p class = "sphx-glr-script-out" > Out:< / p >
< div class = "sphx-glr-script-out highlight-none notranslate" > < div class = "highlight" > < pre > < span > < / span > doc_string=
domain=onnxml
ir_version=3
metadata_props=[]
model_version=0
producer_name=OnnxMLTools
producer_version=1.2.0.0116
< / pre > < / div >
< / div >
< 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 = "k" > 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 >
< 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 >
< 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 >
< 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 >
< 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 >
< 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 >
< 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 >
< / div >
< p class = "sphx-glr-script-out" > Out:< / p >
< div class = "sphx-glr-script-out highlight-none notranslate" > < div class = "highlight" > < pre > < span > < / span > custom_metadata_map={}
description=
domain=onnxml
graph_name=3c59201b940f410fa29dc71ea9d5767d
producer_name=OnnxMLTools
version=0
< / pre > < / div >
< / div >
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< p > < a class = "reference download internal" download = "" href = "../_downloads/b0937520019fa7a27c06534937db5360/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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< p > < a class = "reference download internal" download = "" href = "../_downloads/887b1b90bedbc47a6865747b3085ad9f/plot_metadata.ipynb" > < code class = "xref download docutils literal notranslate" > < span class = "pre" > Download< / span > < span class = "pre" > Jupyter< / span > < span class = "pre" > notebook:< / span > < span class = "pre" > plot_metadata.ipynb< / span > < / code > < / a > < / p >
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