: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 specifed by code.
   :type conf_fname_or_obj: string or obj

   .. py:property:: source

      Return source.

   .. py:property:: destination

      Return destination.

   .. py:property:: eval_dataloader

      Return eval dataloader.

   .. py:property:: model

      Return model.

   .. py:property:: metric

      Return metric.

   .. py:property:: postprocess

      Check postprocess.

   .. py:property:: eval_func

      Return eval_func.

   .. py:method:: dataset(dataset_type, *args, **kwargs)

      Return dataset.

      :param dataset_type: dataset type

      :returns: dataset class
      :rtype: class