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

.. only:: html

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

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

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

.. _sphx_glr_gyexamples_plot_converters.py:


.. _l-b-transformed-target-regressor:

A converter for a TransformedTargetRegressor
============================================

There is no easy way to convert a
:class:`sklearn.preprocessing.FunctionTransformer` or
a :epkg:`sklearn.compose.TransformedTargetRegressor` unless
the function is written in such a way the conversion is implicit.

.. GENERATED FROM PYTHON SOURCE LINES 13-24

.. code-block:: default

    from typing import Any
    import numpy as np
    from sklearn.compose import TransformedTargetRegressor
    from sklearn.preprocessing import FunctionTransformer
    from sklearn.linear_model import LinearRegression
    from mlprodict.onnx_conv import to_onnx
    from mlprodict import __max_supported_opset__ as TARGET_OPSET
    from mlprodict.npy import onnxnumpy_default, NDArray
    from mlprodict.onnxrt import OnnxInference
    import mlprodict.npy.numpy_onnx_impl as npnx








.. GENERATED FROM PYTHON SOURCE LINES 25-27

TransformedTargetRegressor
++++++++++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 27-49

.. code-block:: default



    @onnxnumpy_default
    def onnx_log_1(x: NDArray[Any, np.float32]) -> NDArray[(None, None), np.float32]:
        return npnx.log1p(x)


    @onnxnumpy_default
    def onnx_exp_1(x: NDArray[Any, np.float32]) -> NDArray[(None, None), np.float32]:
        return npnx.exp(x) - np.float32(1)


    model = TransformedTargetRegressor(
        regressor=LinearRegression(),
        func=onnx_log_1, inverse_func=onnx_exp_1)

    x = np.arange(18).reshape((-1, 3)).astype(np.float32)
    y = x.sum(axis=1)
    model.fit(x, y)
    expected = model.predict(x)
    print(expected)





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

 .. code-block:: none

    [ 5.3555384  9.108676  15.0781555 24.572792  39.67432   63.693733 ]




.. GENERATED FROM PYTHON SOURCE LINES 50-51

Conversion to ONNX

.. GENERATED FROM PYTHON SOURCE LINES 51-57

.. code-block:: default


    onx = to_onnx(model, x, rewrite_ops=True, target_opset=TARGET_OPSET)
    oinf = OnnxInference(onx)
    got = oinf.run({'X': x})
    print(got)





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

 .. code-block:: none

    {'variable': array([[ 5.3555384],
           [ 9.108676 ],
           [15.0781555],
           [24.572792 ],
           [39.67432  ],
           [63.693733 ]], dtype=float32)}




.. GENERATED FROM PYTHON SOURCE LINES 58-60

FunctionTransformer
+++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 60-66

.. code-block:: default


    model = FunctionTransformer(onnx_log_1)
    model.fit(x, y)
    expected = model.transform(x)
    print(expected)





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

 .. code-block:: none

    [[0.        0.6931472 1.0986123]
     [1.3862944 1.609438  1.7917595]
     [1.9459101 2.0794415 2.1972246]
     [2.3025851 2.3978953 2.4849067]
     [2.5649493 2.6390574 2.7080503]
     [2.7725887 2.8332133 2.8903718]]




.. GENERATED FROM PYTHON SOURCE LINES 67-68

Conversion to ONNX

.. GENERATED FROM PYTHON SOURCE LINES 68-73

.. code-block:: default


    onx = to_onnx(model, x, rewrite_ops=True, target_opset=TARGET_OPSET)
    oinf = OnnxInference(onx)
    got = oinf.run({'X': x})
    print(got)




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

 .. code-block:: none

    {'variable': array([[0.       , 0.6931472, 1.0986123],
           [1.3862944, 1.609438 , 1.7917595],
           [1.9459101, 2.0794415, 2.1972246],
           [2.3025851, 2.3978953, 2.4849067],
           [2.5649493, 2.6390574, 2.7080503],
           [2.7725887, 2.8332133, 2.8903718]], dtype=float32)}





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

   **Total running time of the script:** ( 0 minutes  3.255 seconds)


.. _sphx_glr_download_gyexamples_plot_converters.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_converters.py <plot_converters.py>`

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

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


.. only:: html

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

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