HuggingMouse.pipelines.multitrial_regression
============================================

.. py:module:: HuggingMouse.pipelines.multitrial_regression


Classes
-------

.. autoapisummary::

   HuggingMouse.pipelines.multitrial_regression.ZIGRegression
   HuggingMouse.pipelines.multitrial_regression.MultiTrialRegressionPipeline


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

.. py:class:: ZIGRegression(ViTEmbDim, NNeurons, gen_nodes, factor)

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


   Base class for all neural network modules.

   Your models should also subclass this class.

   Modules can also contain other Modules, allowing to nest them in
   a tree structure. You can assign the submodules as regular attributes::

       import torch.nn as nn
       import torch.nn.functional as F

       class Model(nn.Module):
           def __init__(self):
               super().__init__()
               self.conv1 = nn.Conv2d(1, 20, 5)
               self.conv2 = nn.Conv2d(20, 20, 5)

           def forward(self, x):
               x = F.relu(self.conv1(x))
               return F.relu(self.conv2(x))

   Submodules assigned in this way will be registered, and will have their
   parameters converted too when you call :meth:`to`, etc.

   .. note::
       As per the example above, an ``__init__()`` call to the parent class
       must be made before assignment on the child.

   :ivar training: Boolean represents whether this module is in training or
                   evaluation mode.
   :vartype training: bool


   .. py:attribute:: fc1


   .. py:attribute:: fc2


   .. py:attribute:: fc_theta


   .. py:attribute:: fc_p


   .. py:attribute:: logk


   .. py:method:: forward(X, Y=None)


.. py:class:: MultiTrialRegressionPipeline(**kwargs)

   .. py:attribute:: model


   .. py:attribute:: model_name_str


   .. py:attribute:: model_prefix


   .. py:attribute:: regression_model


   .. py:attribute:: test_set_size


   .. py:attribute:: regr_analysis_results_cache


   .. py:attribute:: boc


   .. py:attribute:: eid_dict


   .. py:attribute:: stimulus_session_dict


   .. py:attribute:: processor