:py:mod:`rofunc.learning.RofuncRL.agents.mixline.ase_agent`
===========================================================

.. py:module:: rofunc.learning.RofuncRL.agents.mixline.ase_agent

.. autodoc2-docstring:: rofunc.learning.RofuncRL.agents.mixline.ase_agent
   :allowtitles:

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

Classes
~~~~~~~

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

   * - :py:obj:`ASEAgent <rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent>`
     - .. autodoc2-docstring:: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent
          :summary:

API
~~~

.. py:class:: ASEAgent(cfg: omegaconf.DictConfig, observation_space: typing.Optional[typing.Union[int, typing.Tuple[int], gym.Space, gymnasium.Space]], action_space: typing.Optional[typing.Union[int, typing.Tuple[int], gym.Space, gymnasium.Space]], memory: typing.Optional[typing.Union[rofunc.learning.RofuncRL.utils.memory.Memory, typing.Tuple[rofunc.learning.RofuncRL.utils.memory.Memory]]] = None, device: typing.Optional[typing.Union[str, torch.device]] = None, experiment_dir: typing.Optional[str] = None, rofunc_logger: typing.Optional[rofunc.logger.BeautyLogger] = None, amp_observation_space: typing.Optional[typing.Union[int, typing.Tuple[int], gym.Space, gymnasium.Space]] = None, motion_dataset: typing.Optional[typing.Union[rofunc.learning.RofuncRL.utils.memory.Memory, typing.Tuple[rofunc.learning.RofuncRL.utils.memory.Memory]]] = None, replay_buffer: typing.Optional[typing.Union[rofunc.learning.RofuncRL.utils.memory.Memory, typing.Tuple[rofunc.learning.RofuncRL.utils.memory.Memory]]] = None, collect_reference_motions: typing.Optional[typing.Callable[[int], torch.Tensor]] = None)
   :canonical: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent

   Bases: :py:obj:`rofunc.learning.RofuncRL.agents.mixline.amp_agent.AMPAgent`

   .. autodoc2-docstring:: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent

   .. rubric:: Initialization

   .. autodoc2-docstring:: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent.__init__

   .. py:method:: act(states: torch.Tensor, deterministic: bool = False, ase_latents: torch.Tensor = None)
      :canonical: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent.act

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent.act

   .. py:method:: store_transition(states: torch.Tensor, actions: torch.Tensor, next_states: torch.Tensor, rewards: torch.Tensor, terminated: torch.Tensor, truncated: torch.Tensor, infos: torch.Tensor)
      :canonical: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent.store_transition

   .. py:method:: update_net()
      :canonical: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent.update_net

      .. autodoc2-docstring:: rofunc.learning.RofuncRL.agents.mixline.ase_agent.ASEAgent.update_net