model.conflicting
=================

.. py:module:: model.conflicting


Attributes
----------

.. autoapisummary::

   model.conflicting.continuous_dim


Classes
-------

.. autoapisummary::

   model.conflicting.ConflictingFeaturesNN


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

.. py:class:: ConflictingFeaturesNN(continuous_dim: int, weights: torch.Tensor)

   Bases: :py:obj:`torch.nn.Sequential`


   A crafted neural network model that incorporates cancellation features.

   Inherits from:
       torch.nn.Sequential: Parent class for implementing neural networks with modules defined in a
       sequential manner.

   Initializes a ConflictingFeaturesNN object.

   :param continuous_dim: Dimension length of the continuous features, excluding cancellation features.
   :type continuous_dim: int
   :param weights: Feature weights of the model. Should have length `continuous_dim`.
   :type weights: torch.Tensor


   .. py:method:: _create_layer_weights(continuous_dim: int, weights: torch.Tensor) -> Tuple

      Creates the weights for the layers in a ConflictingFeaturesNN model.

      :param continuous_dim: Number of continuous features.
      :type continuous_dim: int
      :param weights: Feature weights of the model. Should have length `continuous_dim`.
      :type weights: torch.Tensor

      :returns: Tuple containing the weights and activation functions for the
                neural network model.
      :rtype: tuple[list, NoneType, list]

      :raises AssertionError: If weights are not specified in a valid shape.



.. py:data:: continuous_dim
   :value: 2