.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gyexamples/plot_benchmark_onnx_serialize.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_gyexamples_plot_benchmark_onnx_serialize.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_gyexamples_plot_benchmark_onnx_serialize.py:


.. _l-benchmark-onnx-serialize:

SerializeToString and ParseFromString
=====================================


.. contents::
    :local:

Startup
+++++++

This section creates an ONNX graph if there is not one.

.. GENERATED FROM PYTHON SOURCE LINES 17-34

.. code-block:: default

    import numpy
    import onnx
    from pyquickhelper.pycode.profiling import profile, profile2graph
    from cpyquickhelper.numbers.speed_measure import measure_time
    import matplotlib.pyplot as plt
    import pandas
    from tqdm import tqdm
    from onnx.checker import check_model
    from mlprodict.testing.experimental_c_impl.experimental_c import code_optimisation
    from mlprodict.plotting.text_plot import onnx_simple_text_plot
    from mlprodict.npy.xop import loadop
    try:
        from mlprodict.onnx_tools._onnx_check_model import check_model as check_model_py
    except ImportError:
        check_model_py = None









.. GENERATED FROM PYTHON SOURCE LINES 35-36

Available optimisation on this machine.

.. GENERATED FROM PYTHON SOURCE LINES 36-40

.. code-block:: default


    print(code_optimisation())






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    AVX-omp=8




.. GENERATED FROM PYTHON SOURCE LINES 41-43

Build an ONNX graph of different size
+++++++++++++++++++++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 43-59

.. code-block:: default


    def build_model(n_nodes, size, opv=15):
        OnnxAdd, OnnxIdentity = loadop('Add', 'Identity')
        x = 'X'
        for n in range(n_nodes):
            y = OnnxAdd(x, numpy.random.randn(size).astype(numpy.float32),
                        op_version=opv)
            x = y
        final = OnnxIdentity(x, op_version=opv, output_names=['Y'])
        x = numpy.zeros((10, 10), dtype=numpy.float32)
        return final.to_onnx({'X': x}, {'Y': x}, target_opset=opv)


    model = build_model(2, 5)
    print(onnx_simple_text_plot(model))





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    opset: domain='' version=15
    input: name='X' type=dtype('float32') shape=[10, 10]
    init: name='init' type=dtype('float32') shape=(5,)
    init: name='init_1' type=dtype('float32') shape=(5,)
    Add(X, init) -> out_add_0
      Add(out_add_0, init_1) -> Y
    output: name='Y' type=dtype('float32') shape=[10, 10]




.. GENERATED FROM PYTHON SOURCE LINES 60-62

Measure the time of serialization functions
+++++++++++++++++++++++++++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 62-114

.. code-block:: default



    def parse(buffer):
        proto = onnx.ModelProto()
        proto.ParseFromString(buffer)
        return proto


    data = []
    nodes = [5, 10, 20]
    for size in tqdm([10, 100, 1000, 10000, 100000, 200000, 300000]):
        for n_nodes in nodes:
            repeat = 20 if size < 100000 else 5
            onx = build_model(n_nodes, size)
            serialized = onx.SerializeToString()
            onnx_size = len(serialized)
            obs = measure_time(lambda: onx.SerializeToString(),
                               div_by_number=True, repeat=repeat)
            obs['size'] = size
            obs['n_nodes'] = n_nodes
            obs['onnx_size'] = onnx_size
            obs['task'] = "SerializeToString"
            data.append(obs)

            parsed = parse(serialized)
            obs = measure_time(lambda: parse(serialized),
                               div_by_number=True, repeat=repeat)
            obs['size'] = size
            obs['n_nodes'] = n_nodes
            obs['onnx_size'] = onnx_size
            obs['task'] = "ParseFromString"
            data.append(obs)

            obs = measure_time(lambda: check_model(onx, full_check=False),
                               div_by_number=True, repeat=repeat)
            obs['size'] = size
            obs['n_nodes'] = n_nodes
            obs['onnx_size'] = onnx_size
            obs['task'] = "check_model"
            data.append(obs)

            if check_model_py is None:
                continue

            obs = measure_time(lambda: check_model_py(onx),
                               div_by_number=True, repeat=repeat)
            obs['size'] = size
            obs['n_nodes'] = n_nodes
            obs['onnx_size'] = onnx_size
            obs['task'] = "check_model_py"
            data.append(obs)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none


      0%|          | 0/7 [00:00<?, ?it/s]
     14%|#4        | 1/7 [00:13<01:18, 13.14s/it]
     29%|##8       | 2/7 [00:26<01:05, 13.19s/it]
     43%|####2     | 3/7 [00:39<00:53, 13.36s/it]
     57%|#####7    | 4/7 [00:56<00:44, 14.73s/it]
     71%|#######1  | 5/7 [01:10<00:28, 14.33s/it]
     86%|########5 | 6/7 [01:33<00:17, 17.43s/it]
    100%|##########| 7/7 [02:07<00:00, 22.63s/it]
    100%|##########| 7/7 [02:07<00:00, 18.17s/it]




.. GENERATED FROM PYTHON SOURCE LINES 115-116

time

.. GENERATED FROM PYTHON SOURCE LINES 116-120

.. code-block:: default

    df = pandas.DataFrame(data).sort_values(
        ['task', 'onnx_size', 'size', 'n_nodes'])
    df[['task', 'onnx_size', 'size', 'n_nodes', 'average']]






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>task</th>
          <th>onnx_size</th>
          <th>size</th>
          <th>n_nodes</th>
          <th>average</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>1</th>
          <td>ParseFromString</td>
          <td>573</td>
          <td>10</td>
          <td>5</td>
          <td>0.000071</td>
        </tr>
        <tr>
          <th>5</th>
          <td>ParseFromString</td>
          <td>1108</td>
          <td>10</td>
          <td>10</td>
          <td>0.000106</td>
        </tr>
        <tr>
          <th>9</th>
          <td>ParseFromString</td>
          <td>2274</td>
          <td>10</td>
          <td>20</td>
          <td>0.000171</td>
        </tr>
        <tr>
          <th>13</th>
          <td>ParseFromString</td>
          <td>2383</td>
          <td>100</td>
          <td>5</td>
          <td>0.000075</td>
        </tr>
        <tr>
          <th>17</th>
          <td>ParseFromString</td>
          <td>4728</td>
          <td>100</td>
          <td>10</td>
          <td>0.000108</td>
        </tr>
        <tr>
          <th>...</th>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
        </tr>
        <tr>
          <th>67</th>
          <td>check_model_py</td>
          <td>8000770</td>
          <td>200000</td>
          <td>10</td>
          <td>0.016459</td>
        </tr>
        <tr>
          <th>59</th>
          <td>check_model_py</td>
          <td>8001596</td>
          <td>100000</td>
          <td>20</td>
          <td>0.015613</td>
        </tr>
        <tr>
          <th>79</th>
          <td>check_model_py</td>
          <td>12000770</td>
          <td>300000</td>
          <td>10</td>
          <td>0.022685</td>
        </tr>
        <tr>
          <th>71</th>
          <td>check_model_py</td>
          <td>16001596</td>
          <td>200000</td>
          <td>20</td>
          <td>0.032270</td>
        </tr>
        <tr>
          <th>83</th>
          <td>check_model_py</td>
          <td>24001596</td>
          <td>300000</td>
          <td>20</td>
          <td>0.046195</td>
        </tr>
      </tbody>
    </table>
    <p>84 rows × 5 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 121-123

Summary
+++++++

.. GENERATED FROM PYTHON SOURCE LINES 123-128

.. code-block:: default


    df.to_excel("time.xlsx", index=False)
    piv = df.pivot(index='onnx_size', columns='task', values='average')
    piv






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th>task</th>
          <th>ParseFromString</th>
          <th>SerializeToString</th>
          <th>check_model</th>
          <th>check_model_py</th>
        </tr>
        <tr>
          <th>onnx_size</th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>573</th>
          <td>0.000071</td>
          <td>0.000088</td>
          <td>0.000144</td>
          <td>0.001822</td>
        </tr>
        <tr>
          <th>1108</th>
          <td>0.000106</td>
          <td>0.000134</td>
          <td>0.000236</td>
          <td>0.003213</td>
        </tr>
        <tr>
          <th>2274</th>
          <td>0.000171</td>
          <td>0.000219</td>
          <td>0.000393</td>
          <td>0.006007</td>
        </tr>
        <tr>
          <th>2383</th>
          <td>0.000075</td>
          <td>0.000091</td>
          <td>0.000157</td>
          <td>0.001828</td>
        </tr>
        <tr>
          <th>4728</th>
          <td>0.000108</td>
          <td>0.000135</td>
          <td>0.000240</td>
          <td>0.003226</td>
        </tr>
        <tr>
          <th>9514</th>
          <td>0.000177</td>
          <td>0.000221</td>
          <td>0.000398</td>
          <td>0.006025</td>
        </tr>
        <tr>
          <th>20389</th>
          <td>0.000081</td>
          <td>0.000093</td>
          <td>0.000166</td>
          <td>0.001858</td>
        </tr>
        <tr>
          <th>40739</th>
          <td>0.000122</td>
          <td>0.000140</td>
          <td>0.000254</td>
          <td>0.003278</td>
        </tr>
        <tr>
          <th>81535</th>
          <td>0.000205</td>
          <td>0.000232</td>
          <td>0.000430</td>
          <td>0.006164</td>
        </tr>
        <tr>
          <th>200399</th>
          <td>0.000110</td>
          <td>0.000115</td>
          <td>0.000250</td>
          <td>0.001993</td>
        </tr>
        <tr>
          <th>400759</th>
          <td>0.000268</td>
          <td>0.000240</td>
          <td>0.000643</td>
          <td>0.003585</td>
        </tr>
        <tr>
          <th>801575</th>
          <td>0.000618</td>
          <td>0.000569</td>
          <td>0.001207</td>
          <td>0.006630</td>
        </tr>
        <tr>
          <th>2000404</th>
          <td>0.000977</td>
          <td>0.000903</td>
          <td>0.001863</td>
          <td>0.004334</td>
        </tr>
        <tr>
          <th>4000405</th>
          <td>0.001263</td>
          <td>0.001242</td>
          <td>0.002445</td>
          <td>0.008527</td>
        </tr>
        <tr>
          <th>4000770</th>
          <td>0.001826</td>
          <td>0.001700</td>
          <td>0.003561</td>
          <td>0.008047</td>
        </tr>
        <tr>
          <th>6000405</th>
          <td>0.001762</td>
          <td>0.001706</td>
          <td>0.003448</td>
          <td>0.011656</td>
        </tr>
        <tr>
          <th>8000770</th>
          <td>0.002345</td>
          <td>0.002294</td>
          <td>0.004584</td>
          <td>0.016459</td>
        </tr>
        <tr>
          <th>8001596</th>
          <td>0.003417</td>
          <td>0.003161</td>
          <td>0.006496</td>
          <td>0.015613</td>
        </tr>
        <tr>
          <th>12000770</th>
          <td>0.003430</td>
          <td>0.003452</td>
          <td>0.006722</td>
          <td>0.022685</td>
        </tr>
        <tr>
          <th>16001596</th>
          <td>0.004550</td>
          <td>0.004430</td>
          <td>0.009106</td>
          <td>0.032270</td>
        </tr>
        <tr>
          <th>24001596</th>
          <td>0.006657</td>
          <td>0.006511</td>
          <td>0.012976</td>
          <td>0.046195</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 129-131

Graph
+++++

.. GENERATED FROM PYTHON SOURCE LINES 131-138

.. code-block:: default


    fig, ax = plt.subplots(1, 1)
    piv.plot(title="Time processing of serialization functions\n"
                   "lower better", ax=ax)
    ax.set_xlabel("onnx size")
    ax.set_ylabel("s")




.. image-sg:: /gyexamples/images/sphx_glr_plot_benchmark_onnx_serialize_001.png
   :alt: Time processing of serialization functions lower better
   :srcset: /gyexamples/images/sphx_glr_plot_benchmark_onnx_serialize_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    Text(33.972222222222214, 0.5, 's')



.. GENERATED FROM PYTHON SOURCE LINES 139-149

Conclusion
++++++++++

This graph shows that implementing check_model in python is much slower
than the C++ version. However, protobuf prevents from sharing
ModelProto from Python to C++ (see `Python Updates
<https://developers.google.com/protocol-buffers/docs/news/2022-05-06>`_)
unless the python package is compiled with a specific setting
(problably slower). A profiling shows that the code spends quite some time
in function :func:`getattr`.

.. GENERATED FROM PYTHON SOURCE LINES 149-156

.. code-block:: default


    ps = profile(lambda: check_model_py(onx))[0]
    root, nodes = profile2graph(ps, clean_text=lambda x: x.split('/')[-1])
    text = root.to_text()
    print(text)

    # plt.show()




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    __getattr__                                                  --  160  160 -- 0.00099 0.00280 -- _onnx_check_model.py:68:__getattr__ (__getattr__)
        <method 'endswith' of 'str' objects>                     --  160  160 -- 0.00020 0.00020 -- ~:0:<method 'endswith' of 'str' objects> (<method 'endswith' of 'str' objects>) +++
        <built-in method builtins.getattr>                       --  160  160 -- 0.00067 0.00067 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>) +++
        <built-in method builtins.hasattr>                       --  160  160 -- 0.00094 0.00094 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
    __init__                                                     --    2    2 -- 0.00002 0.00002 -- _onnx_check_model.py:312:__init__ (__init__)
    get_ir_version                                               --   21   21 -- 0.00004 0.00004 -- _onnx_check_model.py:326:get_ir_version (get_ir_version)
    get_opset_imports                                            --   21   21 -- 0.00001 0.00001 -- _onnx_check_model.py:334:get_opset_imports (get_opset_imports)
    set_opset_imports                                            --    2    2 -- 0.00000 0.00000 -- _onnx_check_model.py:338:set_opset_imports (set_opset_imports)
    __init__                                                     --    2    3 -- 0.00001 0.00001 -- _onnx_check_model.py:377:__init__ (__init__)
        copy                                                     --    1    1 -- 0.00000 0.00001 -- _onnx_check_model.py:398:copy (copy)
            __init__                                             --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:377:__init__ (__init__) +++
    this_graph_has                                               --   81   81 -- 0.00008 0.00008 -- _onnx_check_model.py:388:this_graph_has (this_graph_has)
    this_or_ancestor_graph_has                                   --   60   80 -- 0.00013 0.00021 -- _onnx_check_model.py:392:this_or_ancestor_graph_has (this_or_ancestor_graph_has)
        this_graph_has                                           --   80   80 -- 0.00008 0.00008 -- _onnx_check_model.py:388:this_graph_has (this_graph_has) +++
        this_or_ancestor_graph_has                               --   20   20 -- 0.00002 0.00003 -- _onnx_check_model.py:392:this_or_ancestor_graph_has (this_or_ancestor_graph_has) +++
    _enforce_has_field                                           --   46   46 -- 0.00007 0.00024 -- _onnx_check_model.py:405:_enforce_has_field (_enforce_has_field)
        <built-in method builtins.hasattr>                       --   46   46 -- 0.00018 0.00018 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
    _enforce_non_empty_field                                     --   23   23 -- 0.00003 0.00009 -- _onnx_check_model.py:417:_enforce_non_empty_field (_enforce_non_empty_field)
        <built-in method builtins.getattr>                       --   23   23 -- 0.00006 0.00006 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>) +++
    <lambda>                                                     --    1    1 -- 0.00000 0.04924 -- plot_benchmark_onnx_serialize.py:150:<lambda> (<lambda>)
        check_model                                              --    1    1 -- 0.00002 0.04923 -- _onnx_check_model.py:1266:check_model (check_model)
            __init__                                             --    1    1 -- 0.00001 0.00001 -- _onnx_check_model.py:312:__init__ (__init__) +++
            _check_model                                         --    1    1 -- 0.00008 0.04920 -- _onnx_check_model.py:1223:_check_model (_check_model)
                get_ir_version                                   --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:326:get_ir_version (get_ir_version) +++
                set_ir_version                                   --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:330:set_ir_version (set_ir_version)
                set_opset_imports                                --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:338:set_opset_imports (set_opset_imports) +++
                __init__                                         --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:377:__init__ (__init__) +++
                _check_graph                                     --    1    1 -- 0.00149 0.04907 -- _onnx_check_model.py:962:_check_graph (_check_graph)
                    get_ir_version                               --   20   20 -- 0.00004 0.00004 -- _onnx_check_model.py:326:get_ir_version (get_ir_version) +++
                    __init__                                     --    1    1 -- 0.00000 0.00001 -- _onnx_check_model.py:377:__init__ (__init__) +++
                    add                                          --   41   41 -- 0.00014 0.00018 -- _onnx_check_model.py:384:add (add)
                        <method 'add' of 'set' objects>          --   41   41 -- 0.00004 0.00004 -- ~:0:<method 'add' of 'set' objects> (<method 'add' of 'set' objects>) +++
                    this_graph_has                               --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:388:this_graph_has (this_graph_has) +++
                    this_or_ancestor_graph_has                   --   60   60 -- 0.00011 0.00021 -- _onnx_check_model.py:392:this_or_ancestor_graph_has (this_or_ancestor_graph_has) +++
                    _enforce_has_field                           --   20   20 -- 0.00004 0.00016 -- _onnx_check_model.py:405:_enforce_has_field (_enforce_has_field) +++
                    _enforce_non_empty_field                     --    1    1 -- 0.00001 0.00001 -- _onnx_check_model.py:417:_enforce_non_empty_field (_enforce_non_empty_field) +++
                    _check_value_info                            --    2    2 -- 0.00016 0.00049 -- _onnx_check_model.py:423:_check_value_info (_check_value_info)
                        is_main_graph                            --    2    2 -- 0.00000 0.00000 -- _onnx_check_model.py:342:is_main_graph (is_main_graph)
                        _enforce_has_field                       --    6    6 -- 0.00001 0.00003 -- _onnx_check_model.py:405:_enforce_has_field (_enforce_has_field) +++
                        _enforce_non_empty_field                 --    2    2 -- 0.00000 0.00001 -- _onnx_check_model.py:417:_enforce_non_empty_field (_enforce_non_empty_field) +++
                        <method 'ByteSize' ...CMessage' objects> --   12   12 -- 0.00003 0.00003 -- ~:0:<method 'ByteSize' of 'google.protobuf.pyext._message.CMessage' objects> (<method 'ByteSize' of 'google.protobuf.pyext._message.CMessage' objects>)
                        <method 'endswith' of 'str' objects>     --  138  138 -- 0.00006 0.00006 -- ~:0:<method 'endswith' of 'str' objects> (<method 'endswith' of 'str' objects>) +++
                        <built-in method builtins.dir>           --    2    2 -- 0.00014 0.00014 -- ~:0:<built-in method builtins.dir> (<built-in method builtins.dir>)
                        <built-in method builtins.getattr>       --   12   12 -- 0.00005 0.00005 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>) +++
                    _check_tensor                                --   20   20 -- 0.01124 0.04066 -- _onnx_check_model.py:484:_check_tensor (_check_tensor)
                        _enforce_has_field                       --   20   20 -- 0.00002 0.00005 -- _onnx_check_model.py:405:_enforce_has_field (_enforce_has_field) +++
                        _check_data_field                        --  100  100 -- 0.00043 0.01959 -- _onnx_check_model.py:465:_check_data_field (_check_data_field)
                            <built-in method builtins.getattr>   --  120  120 -- 0.01901 0.01901 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>) +++
                            <built-in method builtins.len>       --  100  100 -- 0.00015 0.00015 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>) +++
                        <built-in method builtins.hasattr>       --   40   40 -- 0.00971 0.00971 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
                        <built-in method builtins.len>           --   20   20 -- 0.00008 0.00008 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>) +++
                    _check_node                                  --   20   20 -- 0.00061 0.00579 -- _onnx_check_model.py:911:_check_node (_check_node)
                        __getattr__                              --   20   20 -- 0.00013 0.00031 -- _onnx_check_model.py:68:__getattr__ (__getattr__) +++
                        verify                                   --   20   20 -- 0.00141 0.00415 -- _onnx_check_model.py:83:verify (verify)
                            __init__                             --   20   20 -- 0.00006 0.00006 -- _onnx_check_model.py:31:__init__ (__init__)
                            __getattr__                          --  140  140 -- 0.00086 0.00248 -- _onnx_check_model.py:68:__getattr__ (__getattr__) +++
                            num_inputs_allowed                   --   20   20 -- 0.00001 0.00001 -- _onnx_check_model.py:73:num_inputs_allowed (num_inputs_allowed)
                            num_outputs_allowed                  --   20   20 -- 0.00001 0.00001 -- _onnx_check_model.py:78:num_outputs_allowed (num_outputs_allowed)
                            <built-in method builtins.len>       --  200  200 -- 0.00017 0.00017 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>) +++
                        GetSchema                                --   20   20 -- 0.00003 0.00055 -- _onnx_check_model.py:302:GetSchema (GetSchema)
                            get_schema                           --   20   20 -- 0.00008 0.00052 -- _onnx_check_model.py:295:get_schema (get_schema)
                                __init__                         --   20   20 -- 0.00003 0.00003 -- _onnx_check_model.py:65:__init__ (__init__)
                                <built-in metho...fs.get_schema> --   20   20 -- 0.00041 0.00041 -- ~:0:<built-in method onnx.onnx_cpp2py_export.defs.get_schema> (<built-in method onnx.onnx_cpp2py_export.defs.get_schema>)
                        get_opset_imports                        --   20   20 -- 0.00001 0.00001 -- _onnx_check_model.py:334:get_opset_imports (get_opset_imports) +++
                        get_schema_registry                      --   20   20 -- 0.00001 0.00001 -- _onnx_check_model.py:354:get_schema_registry (get_schema_registry)
                        _enforce_non_empty_field                 --   20   20 -- 0.00002 0.00007 -- _onnx_check_model.py:417:_enforce_non_empty_field (_enforce_non_empty_field) +++
                        check_is_experimental_op                 --   20   20 -- 0.00007 0.00007 -- _onnx_check_model.py:1296:check_is_experimental_op (check_is_experimental_op)
                    <method 'append' of 'list' objects>          --   20   20 -- 0.00001 0.00001 -- ~:0:<method 'append' of 'list' objects> (<method 'append' of 'list' objects>)
                    <method 'add' of 'set' objects>              --   20   20 -- 0.00002 0.00002 -- ~:0:<method 'add' of 'set' objects> (<method 'add' of 'set' objects>) +++
                _check_model_local_functions                     --    1    1 -- 0.00002 0.00004 -- _onnx_check_model.py:1122:_check_model_local_functions (_check_model_local_functions)
                    __init__                                     --    1    1 -- 0.00001 0.00001 -- _onnx_check_model.py:312:__init__ (__init__) +++
                    get_opset_imports                            --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:334:get_opset_imports (get_opset_imports) +++
                    set_opset_imports                            --    1    1 -- 0.00000 0.00000 -- _onnx_check_model.py:338:set_opset_imports (set_opset_imports) +++
    <built-in method builtins.len>                               --  321  321 -- 0.00041 0.00041 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>)
    <method 'add' of 'set' objects>                              --   61   61 -- 0.00006 0.00006 -- ~:0:<method 'add' of 'set' objects> (<method 'add' of 'set' objects>)
    <built-in method builtins.hasattr>                           --  246  246 -- 0.01083 0.01083 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>)
    <method 'endswith' of 'str' objects>                         --  298  298 -- 0.00026 0.00026 -- ~:0:<method 'endswith' of 'str' objects> (<method 'endswith' of 'str' objects>)
    <built-in method builtins.getattr>                           --  315  315 -- 0.01978 0.01978 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>)





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 2 minutes  9.090 seconds)


.. _sphx_glr_download_gyexamples_plot_benchmark_onnx_serialize.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example


    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_benchmark_onnx_serialize.py <plot_benchmark_onnx_serialize.py>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_benchmark_onnx_serialize.ipynb <plot_benchmark_onnx_serialize.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_