:py:mod:`box_embeddings.parameterizations.sigmoid_box_tensor`
=============================================================

.. py:module:: box_embeddings.parameterizations.sigmoid_box_tensor

.. autoapi-nested-parse::

   Implementation of sigmoid box parameterization.



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

.. py:class:: SigmoidBoxTensor(data: Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor]])

   Bases: :py:obj:`box_embeddings.parameterizations.box_tensor.BoxTensor`

   Sigmoid Box Tensor

   .. py:method:: z(self) -> torch.Tensor
      :property:

      Lower left coordinate as Tensor

      :returns: lower left corner
      :rtype: Tensor


   .. py:method:: Z(self) -> torch.Tensor
      :property:

      Top right coordinate as Tensor

      :returns: top right corner
      :rtype: Tensor


   .. py:method:: W(cls: Type[box_embeddings.parameterizations.box_tensor.TBoxTensor], z: torch.Tensor, Z: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor
      :classmethod:

      Given (z,Z), it returns one set of valid box weights W, such that
      Box(W) = (z,Z).

      :param z: Lower left coordinate of shape (..., hidden_dims)
      :param Z: Top right coordinate of shape (..., hidden_dims)
      :param \*args: extra arguments for child class
      :param \*\*kwargs: extra arguments for child class

      :returns:

                Parameters of the box. In base class implementation, this
                    will have shape (..., 2, hidden_dims).
      :rtype: Tensor


   .. py:method:: from_vector(cls: Type[box_embeddings.parameterizations.box_tensor.TBoxTensor], vector: torch.Tensor, *args: Any, **kwargs: Any) -> box_embeddings.parameterizations.box_tensor.BoxTensor
      :classmethod:

      Creates a box for a vector. In this base implementation the vector is split
      into two pieces and these are used as box weights.

      :param vector: tensor
      :param \*args: extra arguments for child class
      :param \*\*kwargs: extra arguments for child class

      :returns: A BoxTensor

      :raises ValueError: if last dimension is not even