:py:mod:`rofunc.learning.RofuncRL.processors.running_mean_std`
==============================================================

.. py:module:: rofunc.learning.RofuncRL.processors.running_mean_std

.. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.running_mean_std
   :allowtitles:

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

Classes
~~~~~~~

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

   * - :py:obj:`RunningMeanStd <rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStd>`
     -
   * - :py:obj:`RunningMeanStdObs <rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStdObs>`
     -

API
~~~

.. py:class:: RunningMeanStd(insize, epsilon=1e-05, per_channel=False, norm_only=False)
   :canonical: rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStd

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

   .. py:method:: forward(input, unnorm=False)
      :canonical: rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStd.forward

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStd.forward

.. py:class:: RunningMeanStdObs(insize, epsilon=1e-05, per_channel=False, norm_only=False)
   :canonical: rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStdObs

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

   .. py:method:: forward(input, unnorm=False)
      :canonical: rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStdObs.forward

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.running_mean_std.RunningMeanStdObs.forward