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

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

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

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

Classes
~~~~~~~

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

   * - :py:obj:`Noise <rofunc.learning.RofuncRL.processors.noises.Noise>`
     - .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.Noise
          :summary:
   * - :py:obj:`GaussianNoise <rofunc.learning.RofuncRL.processors.noises.GaussianNoise>`
     - .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.GaussianNoise
          :summary:

API
~~~

.. py:class:: Noise(device: typing.Optional[typing.Union[str, torch.device]] = None)
   :canonical: rofunc.learning.RofuncRL.processors.noises.Noise

   .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.Noise

   .. rubric:: Initialization

   .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.Noise.__init__

   .. py:method:: sample_like(tensor: torch.Tensor) -> torch.Tensor
      :canonical: rofunc.learning.RofuncRL.processors.noises.Noise.sample_like

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.Noise.sample_like

   .. py:method:: sample(size: typing.Union[typing.Tuple[int], torch.Size]) -> torch.Tensor
      :canonical: rofunc.learning.RofuncRL.processors.noises.Noise.sample
      :abstractmethod:

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.Noise.sample

.. py:class:: GaussianNoise(mean: float, std: float, device: typing.Optional[typing.Union[str, torch.device]] = None)
   :canonical: rofunc.learning.RofuncRL.processors.noises.GaussianNoise

   Bases: :py:obj:`rofunc.learning.RofuncRL.processors.noises.Noise`

   .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.GaussianNoise

   .. rubric:: Initialization

   .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.GaussianNoise.__init__

   .. py:method:: sample(size: typing.Union[typing.Tuple[int], torch.Size]) -> torch.Tensor
      :canonical: rofunc.learning.RofuncRL.processors.noises.GaussianNoise.sample

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.processors.noises.GaussianNoise.sample