added documentation tree.

docs/Makefile

@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/make.bat

@@ -0,0 +1,35 @@
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=source
+set BUILDDIR=build
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.https://www.sphinx-doc.org/
+	exit /b 1
+)
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd

docs/requirements.txt

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+alabaster==0.7.12
+Sphinx==5.1.0
+sphinx-rtd-theme==1.0.0

docs/source/conf.py

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+# Configuration file for the Sphinx documentation builder.
+#
+# For the full list of built-in configuration values, see the documentation:
+# https://www.sphinx-doc.org/en/master/usage/configuration.html
+
+# -- Project information -----------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
+import os
+import sys
+import sphinx_rtd_theme
+
+html_theme = "sphinx_rtd_theme"
+
+sys.path.insert(0, os.path.abspath("../../src/"))
+html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
+
+project = "fairgrad"
+copyright = "2022, Gaurav Maheshwari, Michael Perrot"
+author = "Gaurav Maheshwari, Michael Perrot"
+release = "0.1.1"
+
+# -- General configuration ---------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
+
+extensions = [
+    "sphinx.ext.autodoc",
+    "sphinx.ext.coverage",
+    "sphinx.ext.napoleon",
+    "sphinx.ext.intersphinx",
+]
+
+templates_path = ["_templates"]
+exclude_patterns = []
+
+html_static_path = ["_static"]
+
+intersphinx_mapping = {"python": ("http://docs.python.org/3", None)}
+
+autodoc_typehints = "description"
+
+
+# -- Options for HTML output -------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
+
+html_theme = "alabaster"
+html_static_path = ["_static"]

docs/source/index.rst

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+
+Welcome to fairgrad's documentation!
+====================================
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+   introduction.rst
+   reference.rst
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`

docs/source/introduction.rst

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+Introduction
+------------
+
+FairGrad, is an easy to use general purpose approach to enforce
+fairness for gradient descent based methods. The core idea is to enforce fairness by iteratively learns
+group specific weights based on whether they are advantaged or not. FairGrad is:
+
+    * Simple and easy to integrate with no significant overhead
+    * Supports Multiclass problems and can work with any gradient based methods
+    * Supports various group fairness notions including exact and approximate fairness
+    * Is competitive on various tasks including complex NLP and CV ones
+
+
+Installation
+------------
+
+You can install FairGrad from PyPI with `pip` or your favorite package manager::
+
+    pip install fairgrad
+
+
+Quick Start
+------------
+
+To use fairgrad simply replace your pytorch cross entropy loss with
+fairgrad cross entropy loss. Alongside, regular pytorch cross entropy arguments,
+it expects following *extra* arguments::
+
+    y_train (np.asarray[int], Tensor, optional): All train example's corresponding label
+    s_train (np.asarray[int], Tensor, optional): All train example's corresponding sensitive attribute. This means if there
+            are 2 sensitive attributes, with each of them being binary. For instance gender - (male and female) and
+            age (above 45, below 45). Total unique sentive attributes are 4.
+    fairness_measure (string): Currently we support "equal_odds", "equal_opportunity", and "accuracy_parity".
+    epsilon (float, optional): The slack which is allowed for the final fairness level.
+    fairness_rate (float, optional): Parameter which intertwines current fairness weights with sum of previous fairness rates.
+
+Usage Example
+-------------
+
+Below is a simple example::
+
+        >>> from fairgrad.torch import CrossEntropyLoss
+        >>> input = torch.randn(10, 5, requires_grad=True)
+        >>> target = torch.empty(10, dtype=torch.long).random_(2)
+        >>> s = torch.empty(10, dtype=torch.long).random_(2) # protected attribute
+        >>> loss = CrossEntropyLoss(y_train = target, s_train = s, fairness_measure = 'equal_odds')
+        >>> output = loss(input, target, s, mode='train')
+        >>> output.backward()

docs/source/reference.rst

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+Reference
+=========
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+   reference/fairness_function.rst
+   reference/torch/cross_entropy.rst

docs/source/reference/fairness_function.rst

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+fairness.functions
+========================
+.. automodule:: fairgrad.fairness_functions
+    :members:

docs/source/reference/torch/cross_entropy.rst

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+fairgrad.torch.cross_entropy
+=============================
+.. automodule:: fairgrad.torch.cross_entropy
+    :members: