model.continuous
================

.. py:module:: model.continuous


Classes
-------

.. autoapisummary::

   model.continuous.ContinuousFeaturesNN


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

.. py:class:: ContinuousFeaturesNN(n_features: int, weights: torch.Tensor)

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


   A crafted neural network model that incorporates continuous features with ReLU.

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

   Initializes a ContinuousFeaturesNN object.

   :param n_features: dimensions of the input.
   :type n_features: int
   :param weights: weights of the model. Should have length `n_features`.
   :type weights: torch.Tensor


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

      Creates the weights for the layers in a ContinuousFeaturesNN model.

      :param n_features: Number of features.
      :type n_features: 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.