ncalab.training.pool
====================

.. py:module:: ncalab.training.pool


Classes
-------

.. autoapisummary::

   ncalab.training.pool.Pool


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

.. py:class:: Pool(n_seed: int = 1, damage: bool = False, p_damage: float = 0.2)

   Sample pool that retains previous predictions. Also applies damaging patterns to
   images to increase the robustness of the trained NCA.

   :param n_seed: How many seed images to retain, defaults to 1
   :type n_seed: int, optional
   :param damage: Whether to apply damaging patterns, defaults to False
   :type damage: bool, optional
   :param p_damage: Probability at which a damaging pattern is applied, defaults to 0.2
   :type p_damage: float, optional


   .. py:attribute:: n_seed
      :value: 1



   .. py:attribute:: damage
      :value: False



   .. py:attribute:: batch
      :type:  torch.Tensor | None
      :value: None



   .. py:attribute:: p_damage
      :value: 0.2



   .. py:method:: update(batch: torch.Tensor)

      :param batch: BCWH



   .. py:method:: sample(seed: torch.Tensor) -> torch.Tensor

      :param seed: BCWH
      :return: BCWH