Commit a5b93dc0 authored by M. François's avatar M. François

partial update

parent 38b26d13
.idea/
*~ *~
docs/html docs/html
docs/sphinx/_build docs/sphinx/_build
......
neural_filters neural_filters is a PyTorch toolbox implementing linear IIR filters as recurrent neural units
...@@ -2,38 +2,6 @@ Welcome to Neural Filters’s documentation! ...@@ -2,38 +2,6 @@ Welcome to Neural Filters’s documentation!
****************************************** ******************************************
NeuralFilter1P
==============
This module implements a 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 NeuralFilter1P.NeuralFilter1P(input_size, hidden_size)
A trainable first-order all-pole filter \frac{K}{1 - P z^{-1}}
* **input_size** (int) - the size of the input vector
* **hidden_size** (int) - the size of the output vector
Indices and tables Indices and tables
****************** ******************
......
...@@ -16,10 +16,13 @@ ...@@ -16,10 +16,13 @@
# add these directories to sys.path here. If the directory is relative to the # add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here. # documentation root, use os.path.abspath to make it absolute, like shown here.
# #
import os import os
import sys import sys
sys.path.insert(0, os.path.abspath(os.path.join('..','..','neural_filters')))
import NeuralFilter1P sys.path.insert(0, os.path.abspath(os.path.join('..', '..', 'neural_filters')))
import neural_filters
# -- General configuration ------------------------------------------------ # -- General configuration ------------------------------------------------
...@@ -119,7 +122,6 @@ pygments_style = 'sphinx' ...@@ -119,7 +122,6 @@ pygments_style = 'sphinx'
# If true, `todo` and `todoList` produce output, else they produce nothing. # If true, `todo` and `todoList` produce output, else they produce nothing.
todo_include_todos = False todo_include_todos = False
# -- Options for HTML output ---------------------------------------------- # -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for # The theme to use for HTML and HTML Help pages. See the documentation for
...@@ -244,21 +246,21 @@ htmlhelp_basename = 'NeuralFiltersdoc' ...@@ -244,21 +246,21 @@ htmlhelp_basename = 'NeuralFiltersdoc'
# -- Options for LaTeX output --------------------------------------------- # -- Options for LaTeX output ---------------------------------------------
latex_elements = { latex_elements = {
# The paper size ('letterpaper' or 'a4paper'). # The paper size ('letterpaper' or 'a4paper').
# #
# 'papersize': 'letterpaper', # 'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt'). # The font size ('10pt', '11pt' or '12pt').
# #
# 'pointsize': '10pt', # 'pointsize': '10pt',
# Additional stuff for the LaTeX preamble. # Additional stuff for the LaTeX preamble.
# #
# 'preamble': '', # 'preamble': '',
# Latex figure (float) alignment # Latex figure (float) alignment
# #
# 'figure_align': 'htbp', # 'figure_align': 'htbp',
} }
# Grouping the document tree into LaTeX files. List of tuples # Grouping the document tree into LaTeX files. List of tuples
......
...@@ -10,7 +10,7 @@ Welcome to Neural Filters's documentation! ...@@ -10,7 +10,7 @@ Welcome to Neural Filters's documentation!
:maxdepth: 2 :maxdepth: 2
:caption: Contents: :caption: Contents:
.. automodule:: NeuralFilter1P .. automodule:: neural_filters
:members: :members:
Indices and tables Indices and tables
......
...@@ -25,7 +25,6 @@ def atanh(x): ...@@ -25,7 +25,6 @@ def atanh(x):
return numpy.arctanh(x) return numpy.arctanh(x)
from .log_loss import *
from .neural_filter import * from .neural_filter import *
from .neural_filter_2CC import * from .neural_filter_2CC import *
from .neural_filter_2CD import * from .neural_filter_2CD import *
......
...@@ -2,18 +2,18 @@ from setuptools import setup ...@@ -2,18 +2,18 @@ from setuptools import setup
setup( setup(
name='neural_filters', name='neural_filters',
version='0.1', version='1.0',
description='Linear filters for neural networks in pyTorch', description='Linear filters for neural networks in pyTorch',
author='Idiap research institute - Francois Marelli', author='Idiap research institute - Francois Marelli',
author_email='francois.marelli@idiap.ch', author_email='francois.marelli@idiap.ch',
classifiers=[ classifiers=[
# 3 - Alpha 'Development Status :: 5 - Production/Stable',
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 3 - Alpha',
'Intended Audience :: Developers', 'Intended Audience :: Developers',
'License :: OSI Approved :: GNU GPL v3', 'License :: OSI Approved :: GNU GPL v3',
'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.6',
], ],
install_requires=['torch>=0.4.0'], install_requires=[
'torch>=0.4.0',
'numpy',
],
) )
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