CollaborativeCoding.models.jan_model
====================================

.. py:module:: CollaborativeCoding.models.jan_model


Attributes
----------

.. autoapisummary::

   CollaborativeCoding.models.jan_model.model


Classes
-------

.. autoapisummary::

   CollaborativeCoding.models.jan_model.JanModel


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

.. py:class:: JanModel(image_shape, num_classes)

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


   A simple MLP network model for image classification tasks. Two hidden layers with 100 neurons.

   Args
   ----
   image_shape : tuple(int, int, int)
       Shape of the input image (C, H, W).
   num_classes : int
       Number of classes in the dataset.

   Processing Images
   -----------------
   Input: (N, C, H, W)
       N: Batch size
       C: Number of input channels
       H: Height of the input image
       W: Width of the input image

   Example:
   For grayscale images, C = 1.

   Input Image Shape: (5, 1, 28, 28)
   flatten Output Shape: (5, 784)
   fc1 Output Shape: (5, 100)
   fc2 Output Shape: (5, 100)
   out Output Shape: (5, num_classes)


   .. py:attribute:: in_channels


   .. py:attribute:: height


   .. py:attribute:: width


   .. py:attribute:: num_classes


   .. py:attribute:: fc1


   .. py:attribute:: fc2


   .. py:attribute:: out


   .. py:attribute:: leaky_relu


   .. py:attribute:: flatten


   .. py:method:: forward(x)


.. py:data:: model