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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_plot_load_and_predict.py:


.. _l-example-simple-usage:

Load and predict with ONNX Runtime and a very simple model
==========================================================

This example demonstrates how to load a model and compute
the output for an input vector. It also shows how to
retrieve the definition of its inputs and outputs.

.. GENERATED FROM PYTHON SOURCE LINES 14-19

.. code-block:: default


    import onnxruntime as rt
    import numpy
    from onnxruntime.datasets import get_example








.. GENERATED FROM PYTHON SOURCE LINES 20-22

Let's load a very simple model.
The model is available on github `onnx...test_sigmoid <https://github.com/onnx/onnx/tree/master/onnx/backend/test/data/node/test_sigmoid>`_.

.. GENERATED FROM PYTHON SOURCE LINES 22-26

.. code-block:: default


    example1 = get_example("sigmoid.onnx")
    sess = rt.InferenceSession(example1, providers=rt.get_available_providers())








.. GENERATED FROM PYTHON SOURCE LINES 27-28

Let's see the input name and shape.

.. GENERATED FROM PYTHON SOURCE LINES 28-36

.. code-block:: default


    input_name = sess.get_inputs()[0].name
    print("input name", input_name)
    input_shape = sess.get_inputs()[0].shape
    print("input shape", input_shape)
    input_type = sess.get_inputs()[0].type
    print("input type", input_type)





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

 Out:

 .. code-block:: none

    input name x
    input shape [3, 4, 5]
    input type tensor(float)




.. GENERATED FROM PYTHON SOURCE LINES 37-38

Let's see the output name and shape.

.. GENERATED FROM PYTHON SOURCE LINES 38-46

.. code-block:: default


    output_name = sess.get_outputs()[0].name
    print("output name", output_name)  
    output_shape = sess.get_outputs()[0].shape
    print("output shape", output_shape)
    output_type = sess.get_outputs()[0].type
    print("output type", output_type)





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

 Out:

 .. code-block:: none

    output name y
    output shape [3, 4, 5]
    output type tensor(float)




.. GENERATED FROM PYTHON SOURCE LINES 47-48

Let's compute its outputs (or predictions if it is a machine learned model).

.. GENERATED FROM PYTHON SOURCE LINES 48-54

.. code-block:: default


    import numpy.random
    x = numpy.random.random((3,4,5))
    x = x.astype(numpy.float32)
    res = sess.run([output_name], {input_name: x})
    print(res)




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

 Out:

 .. code-block:: none

    [array([[[0.7282232 , 0.55751914, 0.6318114 , 0.5736186 , 0.5210682 ],
            [0.5551789 , 0.50124794, 0.5218111 , 0.58663917, 0.7030232 ],
            [0.54759526, 0.60854995, 0.5004847 , 0.6313993 , 0.7113242 ],
            [0.5441941 , 0.5421912 , 0.5857317 , 0.6881397 , 0.63593704]],

           [[0.65265447, 0.52420175, 0.6876056 , 0.6252413 , 0.5143449 ],
            [0.5869513 , 0.58136684, 0.60523754, 0.59603804, 0.70649385],
            [0.65459174, 0.58812606, 0.59879124, 0.5215285 , 0.5047252 ],
            [0.5102888 , 0.5441282 , 0.674335  , 0.6463818 , 0.7018383 ]],

           [[0.592211  , 0.7291903 , 0.62842566, 0.50748336, 0.6976217 ],
            [0.615195  , 0.609173  , 0.66978675, 0.573927  , 0.7099608 ],
            [0.6536062 , 0.5290325 , 0.5949771 , 0.52116865, 0.5360124 ],
            [0.6968157 , 0.67949474, 0.6668297 , 0.68328327, 0.6817404 ]]],
          dtype=float32)]





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

   **Total running time of the script:** ( 0 minutes  0.009 seconds)


.. _sphx_glr_download_auto_examples_plot_load_and_predict.py:


.. only :: html

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



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

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



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

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


.. only:: html

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

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