.. 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

        :ref:`Go to the end <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 14-20

.. code-block:: Python


    import numpy

    import onnxruntime as rt
    from onnxruntime.datasets import get_example








.. GENERATED FROM PYTHON SOURCE LINES 21-23

Let's load a very simple model.
The model is available on github `onnx...test_sigmoid <https://github.com/onnx/onnx/blob/v1.22.0/onnx/backend/test/data/node/test_sigmoid>`_.

.. GENERATED FROM PYTHON SOURCE LINES 23-27

.. code-block:: Python


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








.. GENERATED FROM PYTHON SOURCE LINES 28-29

Let's see the input name and shape.

.. GENERATED FROM PYTHON SOURCE LINES 29-37

.. code-block:: Python


    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

 .. code-block:: none

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




.. GENERATED FROM PYTHON SOURCE LINES 38-39

Let's see the output name and shape.

.. GENERATED FROM PYTHON SOURCE LINES 39-47

.. code-block:: Python


    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

 .. code-block:: none

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




.. GENERATED FROM PYTHON SOURCE LINES 48-49

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

.. GENERATED FROM PYTHON SOURCE LINES 49-56

.. code-block:: Python


    import numpy.random  # noqa: E402

    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

 .. code-block:: none

    [array([[[0.5160057 , 0.7166697 , 0.5675714 , 0.54535687, 0.5339971 ],
            [0.6529523 , 0.6951029 , 0.5401793 , 0.56377375, 0.6852754 ],
            [0.5730017 , 0.5257642 , 0.7282217 , 0.61076474, 0.5805669 ],
            [0.5228421 , 0.6778554 , 0.51807076, 0.52089953, 0.5925686 ]],

           [[0.6670459 , 0.64841074, 0.6030437 , 0.6005311 , 0.6947219 ],
            [0.6192975 , 0.65113866, 0.61059296, 0.59591657, 0.57756394],
            [0.6870088 , 0.5341192 , 0.5685398 , 0.5863307 , 0.5289824 ],
            [0.5137127 , 0.5811924 , 0.621683  , 0.54564   , 0.6946349 ]],

           [[0.5791891 , 0.6960951 , 0.66067314, 0.51487327, 0.61670446],
            [0.6313322 , 0.51381683, 0.52351415, 0.6139147 , 0.5511605 ],
            [0.5292715 , 0.5560558 , 0.5730416 , 0.6627769 , 0.54993975],
            [0.5996757 , 0.5937923 , 0.5990792 , 0.5196933 , 0.61731654]]],
          dtype=float32)]





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

   **Total running time of the script:** (0 minutes 0.007 seconds)


.. _sphx_glr_download_auto_examples_plot_load_and_predict.py:

.. only:: html

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

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

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

    .. 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-zip

      :download:`Download zipped: plot_load_and_predict.zip <plot_load_and_predict.zip>`


.. only:: html

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

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