\ :py:mod:`clipppy.utils.distributions.extra_dimensions`
========================================================

.. py:module:: clipppy.utils.distributions.extra_dimensions


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

.. py:class:: ExtraBatched(base_dist: clipppy.utils.distributions.wrapper._Distribution, extra_shape: clipppy.utils.distributions.wrapper._size, validate_args=None)



   Base class for a distribution that delegates to another one.


.. py:class:: ExtraDimensions(base_dist: clipppy.utils.distributions.wrapper._Distribution, extra_shape: clipppy.utils.distributions.wrapper._size, batch_shape: clipppy.utils.distributions.wrapper._size = None, event_shape: clipppy.utils.distributions.wrapper._size = None, validate_args=None)



   Base class for a distribution that delegates to another one.

   .. py:method:: entropy(self)

      Returns entropy of distribution, batched over batch_shape.

      Returns:
          Tensor of shape batch_shape.


   .. py:method:: expand(self, batch_shape, _instance=None)

      Returns a new distribution instance (or populates an existing instance
      provided by a derived class) with batch dimensions expanded to
      `batch_shape`. This method calls :class:`~torch.Tensor.expand` on
      the distribution's parameters. As such, this does not allocate new
      memory for the expanded distribution instance. Additionally,
      this does not repeat any args checking or parameter broadcasting in
      `__init__.py`, when an instance is first created.

      Args:
          batch_shape (torch.Size): the desired expanded size.
          _instance: new instance provided by subclasses that
              need to override `.expand`.

      Returns:
          New distribution instance with batch dimensions expanded to
          `batch_size`.


   .. py:method:: roll_to_right(self, value: torch.Tensor)


   .. py:method:: rsample(self, sample_shape: clipppy.utils.distributions.wrapper._size = torch.Size())

      Generates a sample_shape shaped reparameterized sample or sample_shape
      shaped batch of reparameterized samples if the distribution parameters
      are batched.


   .. py:method:: sample_dim(self)
      :property:



.. py:class:: ExtraIndependent(base_dist: clipppy.utils.distributions.wrapper._Distribution, extra_shape: clipppy.utils.distributions.wrapper._size, validate_args=None)



   Add more event dimensions without consuming existing batch dimensions.

   Useful in order to treat multiple samples as a dimension in an event and
   sum them in the probability and to allow proper plating.

   .. py:method:: log_prob(self, value)

      Returns the log of the probability density/mass function evaluated at
      `value`.

      Args:
          value (Tensor):