Dist version checked

docs/README.rst

@@ -2,6 +2,181 @@ Welcome to Neural Filters’s documentation!
 ******************************************
 
 
+NeuralFilterCell
+================
+
+This module implements a basic trainable all-pole first order filter
+using pyTorch
+
+Copyright (c) 2018 Idiap Research Institute, http://www.idiap.ch/
+
+Written by Francois Marelli <Francois.Marelli@idiap.ch>
+
+This file is part of neural_filters.
+
+neural_filters is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License version 3 as
+published by the Free Software Foundation.
+
+neural_filters is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with neural_filters. If not, see <http://www.gnu.org/licenses/>.
+
+class neural_filters.neural_filter.NeuralFilter(hidden_size)
+
+   A trainable first-order all-pole filter \frac{1}{1 - P z^{-1}}
+
+   * **hidden_size** (int) - the size of the data vector
+
+   forward(input_var, hidden=None)
+
+      Defines the computation performed at every call.
+
+      Should be overridden by all subclasses.
+
+      Note: Although the recipe for forward pass needs to be defined
+        within this function, one should call the "Module" instance
+        afterwards instead of this since the former takes care of
+        running the registered hooks while the latter silently ignores
+        them.
+
+
+NeuralFilter2R
+==============
+
+This module implements a trainable all-pole second order filter with
+real poles using pyTorch
+
+Copyright (c) 2018 Idiap Research Institute, http://www.idiap.ch/
+
+Written by Francois Marelli <Francois.Marelli@idiap.ch>
+
+This file is part of neural_filters.
+
+neural_filters is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License version 3 as
+published by the Free Software Foundation.
+
+neural_filters is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with neural_filters. If not, see <http://www.gnu.org/licenses/>.
+
+class neural_filters.neural_filter_2R.NeuralFilter2R(hidden_size)
+
+   A trainable second-order all-(real)pole filter \frac{1}{1 - P_{1}
+   z^{-1}} \frac{1}{1 - P_{2} z^{-1}}
+
+   * **hidden_size** (int) - the size of data vector
+
+   forward(input_var, hx=(None, None))
+
+      Defines the computation performed at every call.
+
+      Should be overridden by all subclasses.
+
+      Note: Although the recipe for forward pass needs to be defined
+        within this function, one should call the "Module" instance
+        afterwards instead of this since the former takes care of
+        running the registered hooks while the latter silently ignores
+        them.
+
+
+NeuralFilter2CD
+===============
+
+This module implements a trainable critically damped  all-pole second
+order filter with real poles using pyTorch
+
+Copyright (c) 2018 Idiap Research Institute, http://www.idiap.ch/
+
+Written by Francois Marelli <Francois.Marelli@idiap.ch>
+
+This file is part of neural_filters.
+
+neural_filters is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License version 3 as
+published by the Free Software Foundation.
+
+neural_filters is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with neural_filters. If not, see <http://www.gnu.org/licenses/>.
+
+class neural_filters.neural_filter_2CD.NeuralFilter2CD(hidden_size)
+
+   A trainable second-order critically damped all-pole filter
+   \frac{1}{(1 - P z^{-1})^{2}}
+
+   * **hidden_size** (int) - the size of data vector
+
+   forward(input_var, hx=(None, None))
+
+      Defines the computation performed at every call.
+
+      Should be overridden by all subclasses.
+
+      Note: Although the recipe for forward pass needs to be defined
+        within this function, one should call the "Module" instance
+        afterwards instead of this since the former takes care of
+        running the registered hooks while the latter silently ignores
+        them.
+
+
+NeuralFilter2CC
+===============
+
+This module implements a trainable all-pole second order filter with
+complex conjugate poles using pyTorch
+
+Copyright (c) 2018 Idiap Research Institute, http://www.idiap.ch/
+
+Written by Francois Marelli <Francois.Marelli@idiap.ch>
+
+This file is part of neural_filters.
+
+neural_filters is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License version 3 as
+published by the Free Software Foundation.
+
+neural_filters is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with neural_filters. If not, see <http://www.gnu.org/licenses/>.
+
+class neural_filters.neural_filter_2CC.NeuralFilter2CC(hidden_size)
+
+   A trainable second-order all-pole filter \frac{1}{1 - 2 P
+   \cos(\theta) z^{-1} + P^{2} z^{-2}}
+
+   * **hidden_size** (int) - the size of the data vector
+
+   forward(input_var, hidden=None)
+
+      Defines the computation performed at every call.
+
+      Should be overridden by all subclasses.
+
+      Note: Although the recipe for forward pass needs to be defined
+        within this function, one should call the "Module" instance
+        afterwards instead of this since the former takes care of
+        running the registered hooks while the latter silently ignores
+        them.
+
+
 Indices and tables
 ******************
 

docs/sphinx/conf.py

@@ -17,11 +17,6 @@
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 #
 
-import os
-import sys
-
-sys.path.insert(0, os.path.abspath(os.path.join('..', '..', 'neural_filters')))
-
 import neural_filters
 
 # -- General configuration ------------------------------------------------

docs/sphinx/index.rst

@@ -10,7 +10,16 @@ Welcome to Neural Filters's documentation!
    :maxdepth: 2
    :caption: Contents:
 
-.. automodule:: neural_filters
+.. automodule:: neural_filters.neural_filter
+   :members:
+
+.. automodule:: neural_filters.neural_filter_2R
+   :members:
+
+.. automodule:: neural_filters.neural_filter_2CD
+   :members:
+
+.. automodule:: neural_filters.neural_filter_2CC
    :members:
 
 Indices and tables

setup.py

@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
 
 setup(
     name='neural-filters',
-    version='0.2',
+    version='1.0',
     description='Linear filters for neural networks in pyTorch',
     author='Idiap research institute - Francois Marelli',
     author_email='francois.marelli@idiap.ch',