:py:mod:`rofunc.learning.RofuncRL.state_encoders.base_encoders`
===============================================================

.. py:module:: rofunc.learning.RofuncRL.state_encoders.base_encoders

.. autodoc2-docstring:: rofunc.learning.RofuncRL.state_encoders.base_encoders
   :allowtitles:

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

Classes
~~~~~~~

.. list-table::
   :class: autosummary longtable
   :align: left

   * - :py:obj:`EmptyEncoder <rofunc.learning.RofuncRL.state_encoders.base_encoders.EmptyEncoder>`
     -
   * - :py:obj:`BaseEncoder <rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder>`
     -
   * - :py:obj:`MLPEncoder <rofunc.learning.RofuncRL.state_encoders.base_encoders.MLPEncoder>`
     -

API
~~~

.. py:class:: EmptyEncoder()
   :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.EmptyEncoder

   Bases: :py:obj:`torch.nn.Module`

   .. py:method:: forward(x)
      :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.EmptyEncoder.forward

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.state_encoders.base_encoders.EmptyEncoder.forward

.. py:class:: BaseEncoder(cfg: omegaconf.DictConfig, cfg_name: str = 'state_encoder')
   :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder

   Bases: :py:obj:`torch.nn.Module`

   .. py:method:: set_up()
      :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.set_up

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.set_up

   .. py:method:: freeze_network()
      :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.freeze_network

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.freeze_network

   .. py:method:: pre_trained_mode()
      :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.pre_trained_mode

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.pre_trained_mode

   .. py:method:: save_ckpt(path: str)
      :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.save_ckpt

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.save_ckpt

   .. py:method:: load_ckpt(path: str)
      :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.load_ckpt

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.state_encoders.base_encoders.BaseEncoder.load_ckpt

.. py:class:: MLPEncoder(cfg, cfg_name)
   :canonical: rofunc.learning.RofuncRL.state_encoders.base_encoders.MLPEncoder

   Bases: :py:obj:`rofunc.learning.RofuncRL.models.base_models.BaseMLP`