:py:mod:`pycasx.tools.NNet.converters.nnet_to_onnx`
===================================================

.. py:module:: pycasx.tools.NNet.converters.nnet_to_onnx

.. autoapi-nested-parse::

   Convert NNet to onnx.

   The file was adapted from <https://github.com/sisl/NNet>.
   The original file was licensed under MIT License.
   The original license is included below.

   The MIT License (MIT)

   Copyright (c) 2018 Stanford Intelligent Systems Laboratory

   Permission is hereby granted, free of charge, to any person obtaining a copy
   of this software and associated documentation files (the "Software"), to deal
   in the Software without restriction, including without limitation the rights
   to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
   copies of the Software, and to permit persons to whom the Software is
   furnished to do so, subject to the following conditions:

   The above copyright notice and this permission notice shall be included in all
   copies or substantial portions of the Software.

   THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
   IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
   FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
   AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
   LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
   OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
   SOFTWARE.



Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   pycasx.tools.NNet.converters.nnet_to_onnx.nnet_to_onnx
   pycasx.tools.NNet.converters.nnet_to_onnx.main



.. py:function:: nnet_to_onnx(nnet_file, onnx_file = '', output_var = 'y_out', input_var = 'X', normalize_network = False)

   Convert a .nnet file to onnx format.

   :param nnet_file: .nnet file to convert to onnx
   :type nnet_file: string
   :param onnx_file: name for the created .onnx file
   :type onnx_file: string
   :param output_var: name of the output variable in
                      onnx
   :type output_var: string
   :param input_var: name of the input variable in
   :type input_var: string
   :param normalize_network: if true, adapt the network weights and
                             biases so that networks and inputs do not need to be
                             normalized. Default is False.
   :type normalize_network: bool


.. py:function:: main()

   Convert nnet file to onnx.

   Read user inputs from sys.argv and run nnet2onnx function for
   different numbers of inputs.

   :raises ValueError: if no .nnet file is specified via sys.argv