lasdi.latent_space
==================

.. py:module:: lasdi.latent_space


Attributes
----------

.. autoapisummary::

   lasdi.latent_space.act_dict


Classes
-------

.. autoapisummary::

   lasdi.latent_space.MultiLayerPerceptron
   lasdi.latent_space.Autoencoder


Functions
---------

.. autoapisummary::

   lasdi.latent_space.initial_condition_latent


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

.. py:data:: act_dict

.. py:function:: initial_condition_latent(param_grid, physics, autoencoder)

   Outputs the initial condition in the latent space: Z0 = encoder(U0)



.. py:class:: MultiLayerPerceptron(layer_sizes, act_type='sigmoid', reshape_index=None, reshape_shape=None, threshold=0.1, value=0.0, num_heads=1)

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


   .. py:attribute:: n_layers


   .. py:attribute:: layer_sizes


   .. py:attribute:: fcs
      :value: []



   .. py:attribute:: reshape_index
      :value: None



   .. py:attribute:: reshape_shape
      :value: None



   .. py:attribute:: act_type
      :value: 'sigmoid'



   .. py:attribute:: use_multihead
      :value: False



   .. py:method:: forward(x)


   .. py:method:: apply_attention(x, act_idx)


   .. py:method:: init_weight()


.. py:class:: Autoencoder(physics, config)

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


   .. py:attribute:: qgrid_size


   .. py:attribute:: space_dim


   .. py:attribute:: n_z


   .. py:attribute:: encoder


   .. py:attribute:: decoder


   .. py:method:: forward(x)


   .. py:method:: export()


   .. py:method:: load(dict_)