:py:mod:`neural_compressor.experimental.model_conversion`
=========================================================

.. py:module:: neural_compressor.experimental.model_conversion

.. autoapi-nested-parse::

   Helps convert one model format to another.



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

Classes
~~~~~~~

.. autoapisummary::

   neural_compressor.experimental.model_conversion.ModelConversion




.. py:class:: ModelConversion(conf_fname_or_obj=None)


   ModelConversion class is used to convert one model format to another.

      Currently Neural Compressor only supports Quantization-aware training TensorFlow model to Default
      quantized model.

      The typical usage is:
        from neural_compressor.experimental import ModelConversion, common
        conversion = ModelConversion()
        conversion.source = 'QAT'
        conversion.destination = 'default'
        conversion.model = '/path/to/saved_model'
        q_model = conversion()

   :param conf_fname_or_obj: Optional. The path to the YAML configuration file or
                             Conf class containing model conversion and evaluation setting if not specified by code.
   :type conf_fname_or_obj: string or obj