gflownet.proxy.tree
===================

.. py:module:: gflownet.proxy.tree


Classes
-------

.. autoapisummary::

   gflownet.proxy.tree.TreeProxy


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

.. py:class:: TreeProxy(use_prior = True, beta = 1.0, **kwargs)

   Bases: :py:obj:`gflownet.proxy.base.Proxy`


   :param use_prior: Whether to use -likelihood * prior for energy computation or just the
                     -likelihood.
   :type use_prior: bool
   :param beta: Beta coefficient in ``prior = np.exp(-self.beta * n_nodes)``. Note that
                this is temporary prior implementation that was used for debugging,
                in combination with reward_func="boltzmann" it doesn't make much sense.
   :type beta: float


   .. py:attribute:: use_prior
      :value: True



   .. py:attribute:: beta
      :value: 1.0



   .. py:attribute:: X
      :value: None



   .. py:attribute:: y
      :value: None



   .. py:method:: setup(env = None)


   .. py:method:: __call__(states)

      Implement  this function to call the get_reward method of the appropriate Proxy
      Class (EI, UCB, Proxy, Oracle etc).

      :param states:
      :type states: ndarray