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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-profiling-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 = "profile-the-execution-of-a-simple-model" >
< span id = "l-example-profiling" > < / span > < span id = "sphx-glr-auto-examples-plot-profiling-py" > < / span > < h1 > Profile the execution of a simple model< a class = "headerlink" href = "#profile-the-execution-of-a-simple-model" title = "Permalink to this headline" > ¶< / a > < / h1 >
< p > < em > ONNX Runtime< / em > can profile the execution of the model.
This example shows how to interpret the results.< / p >
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< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "kn" > import< / span > < span class = "nn" > onnxruntime< / span > < span class = "k" > as< / span > < span class = "nn" > rt< / span >
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< span class = "kn" > import< / span > < span class = "nn" > numpy< / span >
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< 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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< / pre > < / div >
< / div >
< p > Let’ < / p >
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< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > example1< / span > < span class = "o" > =< / span > < span class = "n" > get_example< / span > < span class = "p" > (< / span > < span class = "s2" > " mul_1.onnx" < / span > < span class = "p" > )< / span >
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< span class = "n" > sess< / span > < span class = "o" > =< / span > < span class = "n" > rt< / span > < span class = "o" > .< / span > < span class = "n" > InferenceSession< / span > < span class = "p" > (< / span > < span class = "n" > example1< / span > < span class = "p" > )< / span >
< span class = "n" > input_name< / span > < span class = "o" > =< / span > < span class = "n" > sess< / span > < span class = "o" > .< / span > < span class = "n" > get_inputs< / span > < span class = "p" > ()[< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > name< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "n" > numpy< / span > < span class = "o" > .< / span > < span class = "n" > array< / span > < span class = "p" > ([[< / span > < span class = "mf" > 1.0< / span > < span class = "p" > ,< / span > < span class = "mf" > 2.0< / span > < span class = "p" > ],< / span > < span class = "p" > [< / span > < span class = "mf" > 3.0< / span > < span class = "p" > ,< / span > < span class = "mf" > 4.0< / span > < span class = "p" > ],< / span > < span class = "p" > [< / span > < span class = "mf" > 5.0< / span > < span class = "p" > ,< / span > < span class = "mf" > 6.0< / span > < span class = "p" > ]],< / span > < span class = "n" > dtype< / span > < span class = "o" > =< / span > < span class = "n" > numpy< / span > < span class = "o" > .< / span > < span class = "n" > float32< / span > < span class = "p" > )< / span >
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< span class = "n" > res< / span > < span class = "o" > =< / span > < span class = "n" > sess< / span > < span class = "o" > .< / span > < span class = "n" > run< / span > < span class = "p" > (< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "p" > {< / span > < span class = "n" > input_name< / span > < span class = "p" > :< / span > < span class = "n" > x< / span > < span class = "p" > })< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > res< / 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 > [array([[ 1., 4.],
[ 9., 16.],
[25., 36.]], dtype=float32)]
< / pre > < / div >
< / div >
< p > We need to enable to profiling
before running the predictions.< / p >
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< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > options< / span > < span class = "o" > =< / span > < span class = "n" > rt< / span > < span class = "o" > .< / span > < span class = "n" > SessionOptions< / span > < span class = "p" > ()< / span >
< span class = "n" > options< / span > < span class = "o" > .< / span > < span class = "n" > enable_profiling< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span >
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< span class = "n" > sess_profile< / span > < span class = "o" > =< / span > < span class = "n" > rt< / span > < span class = "o" > .< / span > < span class = "n" > InferenceSession< / span > < span class = "p" > (< / span > < span class = "n" > example1< / span > < span class = "p" > ,< / span > < span class = "n" > options< / span > < span class = "p" > )< / span >
< span class = "n" > input_name< / span > < span class = "o" > =< / span > < span class = "n" > sess< / span > < span class = "o" > .< / span > < span class = "n" > get_inputs< / span > < span class = "p" > ()[< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > name< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "n" > numpy< / span > < span class = "o" > .< / span > < span class = "n" > array< / span > < span class = "p" > ([[< / span > < span class = "mf" > 1.0< / span > < span class = "p" > ,< / span > < span class = "mf" > 2.0< / span > < span class = "p" > ],< / span > < span class = "p" > [< / span > < span class = "mf" > 3.0< / span > < span class = "p" > ,< / span > < span class = "mf" > 4.0< / span > < span class = "p" > ],< / span > < span class = "p" > [< / span > < span class = "mf" > 5.0< / span > < span class = "p" > ,< / span > < span class = "mf" > 6.0< / span > < span class = "p" > ]],< / span > < span class = "n" > dtype< / span > < span class = "o" > =< / span > < span class = "n" > numpy< / span > < span class = "o" > .< / span > < span class = "n" > float32< / span > < span class = "p" > )< / span >
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< span class = "n" > sess< / span > < span class = "o" > .< / span > < span class = "n" > run< / span > < span class = "p" > (< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "p" > {< / span > < span class = "n" > input_name< / span > < span class = "p" > :< / span > < span class = "n" > x< / span > < span class = "p" > })< / span >
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< span class = "n" > prof_file< / span > < span class = "o" > =< / span > < span class = "n" > sess_profile< / span > < span class = "o" > .< / span > < span class = "n" > end_profiling< / span > < span class = "p" > ()< / span >
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< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > prof_file< / span > < span class = "p" > )< / span >
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< / pre > < / div >
< / div >
< 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 > onnxruntime_profile__2019-08-01_17-10-30.json
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< / pre > < / div >
< / div >
< p > The results are stored un a file in JSON format.
Let’ < / p >
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< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "kn" > import< / span > < span class = "nn" > json< / span >
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< span class = "k" > with< / span > < span class = "nb" > open< / span > < span class = "p" > (< / span > < span class = "n" > prof_file< / span > < span class = "p" > ,< / span > < span class = "s2" > " r" < / span > < span class = "p" > )< / span > < span class = "k" > as< / span > < span class = "n" > f< / span > < span class = "p" > :< / span >
< span class = "n" > sess_time< / span > < span class = "o" > =< / span > < span class = "n" > json< / span > < span class = "o" > .< / span > < span class = "n" > load< / span > < span class = "p" > (< / span > < span class = "n" > f< / span > < span class = "p" > )< / span >
< span class = "kn" > import< / span > < span class = "nn" > pprint< / span >
< span class = "n" > pprint< / span > < span class = "o" > .< / span > < span class = "n" > pprint< / span > < span class = "p" > (< / span > < span class = "n" > sess_time< / span > < span class = "p" > )< / span >
< / 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 > [{' args' : {},
' cat' : ' Session' ,
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' dur' : 236,
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' name' : ' model_loading_uri' ,
' ph' : ' X' ,
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' pid' : 5504,
' tid' : 26256,
' ts' : 14},
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{' args' : {},
' cat' : ' Session' ,
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' dur' : 116,
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' name' : ' session_initialization' ,
' ph' : ' X' ,
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' pid' : 5504,
' tid' : 26256,
' ts' : 254}]
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< / pre > < / div >
< / div >
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< p class = "sphx-glr-timing" > < strong > Total running time of the script:< / strong > ( 0 minutes 0.074 seconds)< / p >
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< p > < a class = "reference download internal" download = "" href = "../_downloads/f470b72fa11eb874a6b566633ea5940f/plot_profiling.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_profiling.py< / span > < / code > < / a > < / p >
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< p > < a class = "reference download internal" download = "" href = "../_downloads/e0ba4bfe8596bf9c4b37b81c2e570b71/plot_profiling.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_profiling.ipynb< / span > < / code > < / a > < / p >
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