[DGL-LifeSci] Release Preparation (CI, Docker, Conda build) (#1399)

* Update

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* add docs

* Fix style

* Fix lint

* Bug fix

* Fix test

* Update

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Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

apps/life_sci/docs/source/conf.py

+# -*- coding: utf-8 -*-
+#
+# Configuration file for the Sphinx documentation builder.
+#
+# This file does only contain a selection of the most common options. For a
+# full list see the documentation:
+# http://www.sphinx-doc.org/en/master/config
+
+# -- Path setup --------------------------------------------------------------
+
+# If extensions (or modules to document with autodoc) are in another directory,
+# 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.
+#
+import os
+import sys
+sys.path.insert(0, os.path.abspath('../../python'))
+
+
+# -- Project information -----------------------------------------------------
+
+project = 'DGL-LifeSci'
+copyright = '2020, DGL Team'
+author = 'DGL Team'
+
+import dgllife
+version = dgllife.__version__
+release = dgllife.__version__
+
+
+# -- General configuration ---------------------------------------------------
+
+# If your documentation needs a minimal Sphinx version, state it here.
+#
+# needs_sphinx = '1.0'
+
+# Add any Sphinx extension module names here, as strings. They can be
+# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
+# ones.
+extensions = [
+    'sphinx.ext.autodoc',
+    'sphinx.ext.autosummary',
+    'sphinx.ext.coverage',
+    'sphinx.ext.mathjax',
+    'sphinx.ext.napoleon',
+    'sphinx.ext.viewcode',
+    'sphinx.ext.intersphinx',
+    'sphinx.ext.graphviz',
+    'sphinx_gallery.gen_gallery',
+]
+
+# Add any paths that contain templates here, relative to this directory.
+templates_path = ['_templates']
+
+# The suffix(es) of source filenames.
+# You can specify multiple suffix as a list of string:
+#
+source_suffix = ['.rst', '.md']
+
+# The master toctree document.
+master_doc = 'index'
+
+# 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 pattern also affects html_static_path and html_extra_path.
+exclude_patterns = []
+
+# The name of the Pygments (syntax highlighting) style to use.
+pygments_style = None
+
+
+# -- 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'
+
+# 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 = {}
+
+# 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_static_path = ['_static']
+
+# Custom sidebar templates, must be a dictionary that maps document names
+# to template names.
+#
+# The default sidebars (for documents that don't match any pattern) are
+# defined by theme itself.  Builtin themes are using these templates by
+# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
+# 'searchbox.html']``.
+#
+# html_sidebars = {}
+
+
+# -- Options for HTMLHelp output ---------------------------------------------
+
+# Output file base name for HTML help builder.
+htmlhelp_basename = 'dgllifedoc'
+
+
+# -- 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, 'dgllife.tex', 'DGL-LifeSci Documentation',
+     'DGL Team', '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, 'dgllife', 'DGL-LifeSci 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, 'dgllife', 'DGL-LifeSci Documentation',
+     author, 'dgllife', 'Application library for XXXXXXXXXXXXXXXX.',
+     'Miscellaneous'),
+]
+
+
+# -- Options for Epub output -------------------------------------------------
+
+# Bibliographic Dublin Core info.
+epub_title = project
+
+# The unique identifier of the text. This can be a ISBN number
+# or the project homepage.
+#
+# epub_identifier = ''
+
+# A unique identification for the text.
+#
+# epub_uid = ''
+
+# A list of files that should not be packed into the epub file.
+epub_exclude_files = ['search.html']
+
+
+# -- Extension configuration -------------------------------------------------
+autosummary_generate = True
+
+intersphinx_mapping = {
+    'python': ('https://docs.python.org/{.major}'.format(sys.version_info), None),
+    'numpy': ('http://docs.scipy.org/doc/numpy/', None),
+    'scipy': ('http://docs.scipy.org/doc/scipy/reference', None),
+    'matplotlib': ('http://matplotlib.org/', None),
+    'networkx' : ('https://networkx.github.io/documentation/stable', None),
+}
+
+# sphinx gallery configurations
+from sphinx_gallery.sorting import FileNameSortKey
+
+examples_dirs = []  # path to find sources
+gallery_dirs = []  # path to generate docs
+reference_url = {
+    'dgllife' : None,
+    'numpy': 'http://docs.scipy.org/doc/numpy/',
+    'scipy': 'http://docs.scipy.org/doc/scipy/reference',
+    'matplotlib': 'http://matplotlib.org/',
+    'networkx' : 'https://networkx.github.io/documentation/stable',
+}
+
+sphinx_gallery_conf = {
+    'backreferences_dir' : 'generated/backreferences',
+    'doc_module' : ('dgllife', 'numpy'),
+    'examples_dirs' : examples_dirs,
+    'gallery_dirs' : gallery_dirs,
+    'within_subsection_order' : FileNameSortKey,
+    'filename_pattern' : '.py',
+    'download_all_examples' : False,
+}

apps/life_sci/docs/source/get_started.rst

+Get Started
+===========

apps/life_sci/docs/source/index.rst

+DGL-LifeSci: A GNN Package for Chemistry and Molecular Applications
+===========================================================================================
+
+Blahlah ...
+
+Get Started
+------------
+
+You could borrow some from the README page.
+
+API Reference
+---------------
+
+The highest level breakdown. What are the APIs for?
+
+
+.. toctree::
+    :maxdepth: 1
+    :caption: Get Started
+    :hidden:
+    :glob:
+
+    get_started
+
+.. toctree::
+    :maxdepth: 2
+    :caption: API Reference
+    :hidden:
+    :glob:
+
+    api/data
+    api/model
+    api/model.gnn
+    api/model.zoo
+    api/model.readout
+    api/utils
+
+Index
+-----
+* :ref:`genindex`

apps/life_sci/python/dgllife/__init__.py

-__version__ = '0.2.0'
+"""DGL-based package for applications in life science."""
+from . import data
+from . import model
+from . import utils
+from .libinfo import __version__

apps/life_sci/python/dgllife/libinfo.py

+"""Information for the library."""
+__version__ = '0.2.0'

apps/life_sci/python/dgllife/model/gnn/attentivefp.py

 """AttentiveFP"""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import dgl.function as fn
 import torch
 import torch.nn as nn
@@ -8,6 +9,7 @@ from dgl.nn.pytorch import edge_softmax
 
 __all__ = ['AttentiveFPGNN']
 
+# pylint: disable=W0221, C0103, E1101
 class AttentiveGRU1(nn.Module):
     """Update node features with attention and GRU.
 
@@ -298,7 +300,7 @@ class AttentiveFPGNN(nn.Module):
 
         self.init_context = GetContext(node_feat_size, edge_feat_size, graph_feat_size, dropout)
         self.gnn_layers = nn.ModuleList()
-        for i in range(num_layers - 1):
+        for _ in range(num_layers - 1):
             self.gnn_layers.append(GNNLayer(graph_feat_size, graph_feat_size, dropout))
 
     def forward(self, g, node_feats, edge_feats):

apps/life_sci/python/dgllife/model/gnn/gat.py

 """Graph Attention Networks"""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import torch.nn as nn
 import torch.nn.functional as F
 
@@ -6,6 +7,7 @@ from dgl.nn.pytorch import GATConv
 
 __all__ = ['GAT']
 
+# pylint: disable=W0221
 class GATLayer(nn.Module):
     r"""Single GAT layer from `Graph Attention Networks <https://arxiv.org/abs/1710.10903>`__
 

apps/life_sci/python/dgllife/model/gnn/gcn.py

 """Graph Convolutional Networks."""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import torch.nn as nn
 import torch.nn.functional as F
 
@@ -6,6 +7,7 @@ from dgl.nn.pytorch import GraphConv
 
 __all__ = ['GCN']
 
+# pylint: disable=W0221, C0103
 class GCNLayer(nn.Module):
     r"""Single GCN layer from `Semi-Supervised Classification with Graph Convolutional Networks
     <https://arxiv.org/abs/1609.02907>`__
@@ -33,7 +35,7 @@ class GCNLayer(nn.Module):
 
         self.activation = activation
         self.graph_conv = GraphConv(in_feats=in_feats, out_feats=out_feats,
-                                    norm=False, activation=activation)
+                                    norm='none', activation=activation)
         self.dropout = nn.Dropout(dropout)
 
         self.residual = residual

apps/life_sci/python/dgllife/model/gnn/mgcn.py

 """MGCN"""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import dgl.function as fn
 import torch
 import torch.nn as nn
@@ -7,6 +8,7 @@ from .schnet import RBFExpansion
 
 __all__ = ['MGCNGNN']
 
+# pylint: disable=W0221, E1101
 class EdgeEmbedding(nn.Module):
     """Module for embedding edges.
 
@@ -232,7 +234,7 @@ class MGCNGNN(nn.Module):
         self.rbf = RBFExpansion(high=cutoff, gap=gap)
 
         self.gnn_layers = nn.ModuleList()
-        for i in range(n_layers):
+        for _ in range(n_layers):
             self.gnn_layers.append(MultiLevelInteraction(feats, len(self.rbf.centers)))
 
     def forward(self, g, node_types, edge_dists):

apps/life_sci/python/dgllife/model/gnn/mpnn.py

 """MPNN"""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import torch.nn as nn
 import torch.nn.functional as F
 
@@ -6,6 +7,7 @@ from dgl.nn.pytorch import NNConv
 
 __all__ = ['MPNNGNN']
 
+# pylint: disable=W0221
 class MPNNGNN(nn.Module):
     """MPNN.
 
@@ -69,7 +71,7 @@ class MPNNGNN(nn.Module):
         node_feats = self.project_node_feats(node_feats) # (V, node_out_feats)
         hidden_feats = node_feats.unsqueeze(0)           # (1, V, node_out_feats)
 
-        for i in range(self.num_step_message_passing):
+        for _ in range(self.num_step_message_passing):
             node_feats = F.relu(self.gnn_layer(g, node_feats, edge_feats))
             node_feats, hidden_feats = self.gru(node_feats.unsqueeze(0), hidden_feats)
             node_feats = node_feats.squeeze(0)

apps/life_sci/python/dgllife/model/gnn/schnet.py

 # -*- coding:utf-8 -*-
-# pylint: disable=C0103, C0111, W0621
+# pylint: disable=C0103, C0111, W0621, W0221, E1102, E1101
 """SchNet"""
 import numpy as np
 import torch
@@ -10,7 +10,7 @@ from dgl.nn.pytorch import CFConv
 __all__ = ['SchNetGNN']
 
 class RBFExpansion(nn.Module):
-    """Expand distances between nodes by radial basis functions.
+    r"""Expand distances between nodes by radial basis functions.
 
     .. math::
         \exp(- \gamma * ||d - \mu||^2)

apps/life_sci/python/dgllife/model/gnn/wln.py

 """WLN"""
-import dgl.function as fn
+# pylint: disable= no-member, arguments-differ, invalid-name
 import math
+import dgl.function as fn
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -10,7 +11,7 @@ from torch.nn import Parameter
 __all__ = ['WLN']
 
 class WLNLinear(nn.Module):
-    """Linear layer for WLN
+    r"""Linear layer for WLN
 
     Let stddev be
 
@@ -50,12 +51,12 @@ class WLNLinear(nn.Module):
             bound = 1 / math.sqrt(fan_in)
             nn.init.uniform_(self.bias, -bound, bound)
 
-    def forward(self, input):
+    def forward(self, feats):
         """Applies the layer.
 
         Parameters
         ----------
-        input : float32 tensor of shape (N, *, in_feats)
+        feats : float32 tensor of shape (N, *, in_feats)
             N for the number of samples, * for any additional dimensions.
 
         Returns
@@ -63,7 +64,7 @@ class WLNLinear(nn.Module):
         float32 tensor of shape (N, *, out_feats)
             Result of the layer.
         """
-        return F.linear(input, self.weight, self.bias)
+        return F.linear(feats, self.weight, self.bias)
 
     def extra_repr(self):
         """Return a description of the layer."""
@@ -133,7 +134,7 @@ class WLN(nn.Module):
             Updated node representations.
         """
         node_feats = self.project_node_in_feats(node_feats)
-        for l in range(self.n_layers):
+        for _ in range(self.n_layers):
             g = g.local_var()
             g.ndata['hv'] = node_feats
             g.apply_edges(fn.copy_src('hv', 'he_src'))

apps/life_sci/python/dgllife/model/model_zoo/acnn.py

 """Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity"""
-# pylint: disable=C0103, C0123
+# pylint: disable=C0103, C0123, W0221, E1101, R1721
 import itertools
 import numpy as np
 import torch

apps/life_sci/python/dgllife/model/model_zoo/attentivefp_predictor.py

 """AttentiveFP"""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import torch.nn as nn
 
 from ..gnn import AttentiveFPGNN
@@ -6,6 +7,7 @@ from ..readout import AttentiveFPReadout
 
 __all__ = ['AttentiveFPPredictor']
 
+# pylint: disable=W0221
 class AttentiveFPPredictor(nn.Module):
     """AttentiveFP for regression and classification on graphs.
 

apps/life_sci/python/dgllife/model/model_zoo/dgmg.py

-# pylint: disable=C0103, W0622, R1710, W0104
+# pylint: disable=C0103, W0622, R1710, W0104, E1101, W0221, C0411
 """
 Learning Deep Generative Models of Graphs
 https://arxiv.org/pdf/1803.03324.pdf

apps/life_sci/python/dgllife/model/model_zoo/gat_predictor.py

 """GAT-based model for regression and classification on graphs."""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import torch.nn as nn
-import torch.nn.functional as F
 
 from .mlp_predictor import MLPPredictor
 from ..gnn.gat import GAT
 from ..readout.weighted_sum_and_max import WeightedSumAndMax
 
+# pylint: disable=W0221
 class GATPredictor(nn.Module):
     r"""GAT-based model for regression and classification on graphs.
 
@@ -65,8 +66,8 @@ class GATPredictor(nn.Module):
     n_tasks : int
         Number of tasks, which is also the output size. Default to 1.
     """
-    def __init__(self, in_feats, hidden_feats=None, num_heads=None, feat_drops=None, attn_drops=None,
-                 alphas=None, residuals=None, agg_modes=None, activations=None,
+    def __init__(self, in_feats, hidden_feats=None, num_heads=None, feat_drops=None,
+                 attn_drops=None, alphas=None, residuals=None, agg_modes=None, activations=None,
                  classifier_hidden_feats=128, classifier_dropout=0., n_tasks=1):
         super(GATPredictor, self).__init__()
 

apps/life_sci/python/dgllife/model/model_zoo/gcn_predictor.py

 """GCN-based model for regression and classification on graphs."""
+# pylint: disable= no-member, arguments-differ, invalid-name
 import torch.nn as nn
 
 from .mlp_predictor import MLPPredictor
 from ..gnn.gcn import GCN
 from ..readout.weighted_sum_and_max import WeightedSumAndMax
 
+# pylint: disable=W0221
 class GCNPredictor(nn.Module):
     """GCN-based model for regression and classification on graphs.
 

apps/life_sci/python/dgllife/model/model_zoo/jtnn/chemutils.py

-# pylint: disable=C0111, C0103, E1101, W0611, W0612, W0703, C0200, R1710
-import rdkit.Chem as Chem
-
+# pylint: disable=C0111, C0103, E1101, W0611, W0612, W0703, C0200, R1710, I1101, R1721
 from collections import defaultdict
+import rdkit.Chem as Chem
 from rdkit.Chem.EnumerateStereoisomers import EnumerateStereoisomers
 from scipy.sparse import csr_matrix
 from scipy.sparse.csgraph import minimum_spanning_tree

apps/life_sci/python/dgllife/model/model_zoo/jtnn/jtmpn.py

-# pylint: disable=C0111, C0103, E1101, W0611, W0612, W1508
+# pylint: disable=C0111, C0103, E1101, W0611, W0612, W1508, I1101, W0221
 # pylint: disable=redefined-outer-name
 import os
 import rdkit.Chem as Chem

apps/life_sci/python/dgllife/model/model_zoo/jtnn/jtnn_dec.py

-# pylint: disable=C0111, C0103, E1101, W0611, W0612
+# pylint: disable=C0111, C0103, E1101, W0611, W0612, W0221, E1102
 import numpy as np
 import torch
 import torch.nn as nn