ProdLDA
=======

.. py:module:: topmost.models.basic.ProdLDA



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



.. autoapisummary::


   topmost.models.basic.ProdLDA.ProdLDA





.. py:class:: ProdLDA(vocab_size, num_topics=50, en_units=200, dropout=0.4)

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


   Autoencoding Variational Inference For Topic Models. ICLR 2017

   Akash Srivastava, Charles Sutton.


   .. py:attribute:: num_topics
      :value: 50



   .. py:attribute:: a


   .. py:attribute:: mu2


   .. py:attribute:: var2


   .. py:attribute:: fc11


   .. py:attribute:: fc12


   .. py:attribute:: fc21


   .. py:attribute:: fc22


   .. py:attribute:: mean_bn


   .. py:attribute:: logvar_bn


   .. py:attribute:: decoder_bn


   .. py:attribute:: fc1_drop


   .. py:attribute:: theta_drop


   .. py:attribute:: fcd1


   .. py:method:: get_beta()


   .. py:method:: get_theta(x)


   .. py:method:: reparameterize(mu, logvar)


   .. py:method:: encode(x)


   .. py:method:: decode(theta)


   .. py:method:: forward(x)


   .. py:method:: loss_function(x, recon_x, mu, logvar)