beginning of docs

README.md

 # PyTorch Scatter
+
+```sh
+pip install torch_scatter
+```
+
+```py
+from torch_scatter import scatter_max
+
+input = torch.Tensor([[2, 0, 1, 4, 3], [0,2, 1, 3, 4]])
+torch.LongTensor([[4, 5, 2, 3], [0, 0, 2, 2, 1]])
+
+max, arg = scatter_max_(index, input, dim=1)
+```
+
+## Features
+
+* CPU and Cuda implementation
+* Backward implementation

docs/Makefile

+SPHINXOPTS  =
+SPHINXBUILD = sphinx-build
+SPHINXPROJ  = pytorch_scatter
+SOURCEDIR   = source
+BUILDDIR    = build
+
+# Put it first so that `make` without argument is like `make help`.
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/source/conf.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import os
+import sys
+import datetime
+import sphinx_rtd_theme
+
+sys.path.insert(0, os.path.abspath('../..'))
+
+# -- General configuration ------------------------------------------------
+
+extensions = [
+    'sphinx.ext.autodoc',
+    'sphinx.ext.autosummary',
+    'sphinx.ext.doctest',
+    'sphinx.ext.intersphinx',
+    'sphinx.ext.todo',
+    'sphinx.ext.coverage',
+    'sphinx.ext.mathjax',
+    'sphinx.ext.napoleon',
+    'sphinx.ext.viewcode',
+    'sphinx.ext.githubpages',
+]
+
+templates_path = ['_templates']
+source_suffix = '.rst'
+master_doc = 'index'
+
+# General information about the project.
+project = 'pytorch_scatter'
+copyright = '{}, Matthias Fey'.format(datetime.datetime.now().year)
+author = 'Matthias Fey'
+
+# The version info for the project you're documenting, acts as replacement for
+# |version| and |release|, also used in various other places throughout the
+# built documents.
+#
+# The short X.Y version.
+version = '0.1.0'
+# The full version, including alpha/beta/rc tags.
+release = '0.1.0'
+
+# The language for content autogenerated by Sphinx. Refer to documentation
+# for a list of supported languages.
+#
+# This is also used if you do content translation via gettext catalogs.
+# Usually you set "language" from the command line for these cases.
+language = None
+
+# List of patterns, relative to source directory, that match files and
+# directories to ignore when looking for source files.
+# This patterns also effect to html_static_path and html_extra_path
+exclude_patterns = []
+
+# The name of the Pygments (syntax highlighting) style to use.
+pygments_style = 'sphinx'
+
+# If true, `todo` and `todoList` produce output, else they produce nothing.
+todo_include_todos = True
+
+# -- Options for HTML output ----------------------------------------------
+
+# The theme to use for HTML and HTML Help pages.  See the documentation for
+# a list of builtin themes.
+#
+html_theme = 'sphinx_rtd_theme'
+html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
+
+# Theme options are theme-specific and customize the look and feel of a theme
+# further.  For a list of options available for each theme, see the
+# documentation.
+#
+html_theme_options = {
+    'collapse_navigation': False,
+    'display_version': True,
+    'logo_only': True,
+}
+
+# Add any paths that contain custom static files (such as style sheets) here,
+# relative to this directory. They are copied after the builtin static files,
+# so a file named "default.css" will overwrite the builtin "default.css".
+# html_logo = '_static/img/logo.svg'
+# html_static_path = ['_static']
+# html_context = {'css_files': ['_static/css/custom.css']}
+
+# Custom sidebar templates, must be a dictionary that maps document names
+# to template names.
+#
+# This is required for the alabaster theme
+# refs: http://alabaster.readthedocs.io/en/latest/installation.html#sidebars
+html_sidebars = {
+    '**': [
+        'relations.html',  # needs 'show_related': True theme option to display
+        'searchbox.html',
+    ]
+}
+
+# -- Options for HTMLHelp output ------------------------------------------
+
+# Output file base name for HTML help builder.
+htmlhelp_basename = 'pytorch_scatter_doc'
+
+# -- Options for LaTeX output ---------------------------------------------
+
+latex_elements = {
+    # The paper size ('letterpaper' or 'a4paper').
+    #
+    # 'papersize': 'letterpaper',
+
+    # The font size ('10pt', '11pt' or '12pt').
+    #
+    # 'pointsize': '10pt',
+
+    # Additional stuff for the LaTeX preamble.
+    #
+    # 'preamble': '',
+
+    # Latex figure (float) alignment
+    #
+    # 'figure_align': 'htbp',
+}
+
+# Grouping the document tree into LaTeX files. List of tuples
+# (source start file, target name, title,
+#  author, documentclass [howto, manual, or own class]).
+latex_documents = [
+    (master_doc, 'pytorch_scatter.tex', 'pytorch\\_scatter Documentation',
+     'Matthias Fey', 'manual'),
+]
+
+# -- Options for manual page output ---------------------------------------
+
+# One entry per manual page. List of tuples
+# (source start file, name, description, authors, manual section).
+man_pages = [(master_doc, 'pytorch_scatter', 'pytorch_scatter Documentation',
+              [author], 1)]
+
+# -- Options for Texinfo output -------------------------------------------
+
+# Grouping the document tree into Texinfo files. List of tuples
+# (source start file, target name, title, author,
+#  dir menu entry, description, category)
+texinfo_documents = [
+    (master_doc, 'pytorch_scatter', 'pytorch_scatter Documentation', author,
+     'pytorch_scatter', 'One line description of project.', 'Miscellaneous'),
+]
+
+# Example configuration for intersphinx: refer to the Python standard library.
+intersphinx_mapping = {'https://docs.python.org/': None}

docs/source/index.rst

+:github_url: https://github.com/rusty1s/pytorch_scatter
+
+PyTorch Scatter documentation
+===============================
+
+.. toctree::
+   :glob:
+   :maxdepth: 1
+   :caption: PackageReference
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`

setup.py

@@ -17,7 +17,7 @@ setup(
     author_email='matthias.fey@tu-dortmund.de',
     install_requires=install_requires,
     setup_requires=setup_requires,
-    tests_require=tests_require,
+    tests_require=tests_require + docs_require,
     packages=find_packages(exclude=['build']),
     ext_package='',
     cffi_modules=[osp.join(osp.dirname(__file__), 'build.py:ffi')], )

torch_scatter/functions/__init__.py

 from .scatter import scatter
 from .utils import gen_filled_tensor, gen_output
 
-
-def scatter_add_(output, index, input, dim=0):
-    """ -> Tensor
-
-    Sums up all values from the tensor :attr:`input` into :attr:`output` at
-    the indices specified in the :attr:`index` tensor along an given axis
-    :attr:`dim`. For each value in :attr:`input`, its output index is specified
-    by its index in :attr:`input` for dimension != :attr:`dim` and by the
-    corresponding value in :attr:`index` for dimension = :attr:`dim`. If
-    multiple indices reference the same location, their contributions add.
-
-    If :attr:`input` and :attr:`index` are n-dimensional tensors with size
-    :math:`(x_0, ..., x_{i-1}, x_i, x_{i+1}, ..., x_{n-1})` and
-    :attr:`dim` = i, then :attr:`output` must be an n-dimensional tensor with
-    size :math:`(x_0, ..., x_{i-1}, y, x_{i+1}, ..., x_{n-1})`. Moreover, the
-    values of :attr:`index` must be between `0` and `output.size(dim) - 1`.
-
-    For one-dimensional tensors, the operation computes
-    :math:`output_i = output_i + \sum_j input_j`, where sum is over
-    :math:`j` such that :math:`index_j = i`.
-
-    Args:
-        output (Tensor): The destination tensor
-        index (LongTensor): The indices of elements to scatter
-        input (Tensor): The source tensor
-        dim (int, optional): The axis along which to index
-
-    Example::
-        >> input = torch.Tensor([[2, 0, 1, 4, 3], [0,2, 1, 3, 4]])
-        >> index = torch.LongTensor([[4, 5, 2, 3], [0, 0, 2, 2, 1]])
-        >> output = torch.zeros(2, 6)
-        >> scatter_add_(output, index, input, dim=1)
-        0  0  4  3  3  0
-        2  4  4  0  0  0
-        [torch.FloatTensor of size 2x6]
-    """
-    return output.scatter_add_(dim, index, input)
-
-
-def scatter_add(index, input, dim=0, size=None, fill_value=0):
-    """ -> Tensor
-
-    Sums ap all values from the tensor :attr:`input` at the indices
-    specified in the :attr:`index` tensor along an given axis :attr:`dim`.
-    The output size at dimension :attr:`dim` is given by :attr:`size` and must
-    be at least size `index.max(dim) - 1`. If :attr:`size` is not given, a
-    minimal sized output tensor is returned. The output tensor is initially
-    filled with the specified value at :attr:`fill_value`.
-
-    For one-dimensional tensors, the operation computes
-    :math:`output_i = fill_value + \sum_j input_j`, where sum is over
-    :math:`j` such that :math:`index_j = i`.
-
-    A more detailed explanation is described in :meth:`~scatter_add_`.
-
-    Args:
-        index (LongTensor): The indices of elements to scatter
-        input (Tensor): The source tensor
-        dim (int, optional): The axis along which to index
-        size (int, optional): Output size at dimension :attr:`dim`
-        fill_value (int, optional): Initial filling of output tensor
-    """
-    output = gen_output(index, input, dim, size, fill_value)
-    return scatter_add_(output, index, input, dim)
+from .add import scatter_add_, scatter_add
 
 
 def scatter_sub_(output, index, input, dim=0):

torch_scatter/functions/add.py

+from .utils import gen_output
+
+
+def scatter_add_(output, index, input, dim=0):
+    """ -> Tensor
+
+    Sums up all values from the tensor :attr:`input` into :attr:`output` at
+    the indices specified in the :attr:`index` tensor along an given axis
+    :attr:`dim`. For each value in :attr:`input`, its output index is specified
+    by its index in :attr:`input` for dimension != :attr:`dim` and by the
+    corresponding value in :attr:`index` for dimension = :attr:`dim`. If
+    multiple indices reference the same location, their contributions add.
+
+    If :attr:`input` and :attr:`index` are n-dimensional tensors with size
+    :math:`(x_0, ..., x_{i-1}, x_i, x_{i+1}, ..., x_{n-1})` and
+    :attr:`dim` = i, then :attr:`output` must be an n-dimensional tensor with
+    size :math:`(x_0, ..., x_{i-1}, y, x_{i+1}, ..., x_{n-1})`. Moreover, the
+    values of :attr:`index` must be between `0` and `output.size(dim) - 1`.
+
+    For one-dimensional tensors, the operation computes
+    :math:`output_i = output_i + \sum_j input_j`, where sum is over
+    :math:`j` such that :math:`index_j = i`.
+
+    Args:
+        output (Tensor): The destination tensor
+        index (LongTensor): The indices of elements to scatter
+        input (Tensor): The source tensor
+        dim (int, optional): The axis along which to index
+
+    Example::
+        >> input = torch.Tensor([[2, 0, 1, 4, 3], [0,2, 1, 3, 4]])
+        >> index = torch.LongTensor([[4, 5, 2, 3], [0, 0, 2, 2, 1]])
+        >> output = torch.zeros(2, 6)
+        >> scatter_add_(output, index, input, dim=1)
+        0  0  4  3  3  0
+        2  4  4  0  0  0
+        [torch.FloatTensor of size 2x6]
+    """
+    return output.scatter_add_(dim, index, input)
+
+
+def scatter_add(index, input, dim=0, size=None, fill_value=0):
+    """ -> Tensor
+
+    Sums ap all values from the tensor :attr:`input` at the indices
+    specified in the :attr:`index` tensor along an given axis :attr:`dim`.
+    The output size at dimension :attr:`dim` is given by :attr:`size` and must
+    be at least size `index.max(dim) - 1`. If :attr:`size` is not given, a
+    minimal sized output tensor is returned. The output tensor is initially
+    filled with the specified value at :attr:`fill_value`.
+
+    For one-dimensional tensors, the operation computes
+    :math:`output_i = fill_value + \sum_j input_j`, where sum is over
+    :math:`j` such that :math:`index_j = i`.
+
+    A more detailed explanation is described in :meth:`~scatter_add_`.
+
+    Args:
+        index (LongTensor): The indices of elements to scatter
+        input (Tensor): The source tensor
+        dim (int, optional): The axis along which to index
+        size (int, optional): Output size at dimension :attr:`dim`
+        fill_value (int, optional): Initial filling of output tensor
+    """
+    output = gen_output(index, input, dim, size, fill_value)
+    return scatter_add_(output, index, input, dim)