[Doc] Update (#175)

* Update * Update
awslabs · Mar 12, 2022 · 4ca5645 · 4ca5645
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diff --git a/docs/source/api/model.gnn.rst b/docs/source/api/model.gnn.rst
@@ -63,3 +63,13 @@ GNNOGB
 ------
 .. automodule:: dgllife.model.gnn.gnn_ogb
     :members:
+
+NF
+--
+.. automodule:: dgllife.model.gnn.nf
+    :members:
+
+PAGTN
+-----
+.. automodule:: dgllife.model.gnn.pagtn
+    :members:
diff --git a/docs/source/api/model.zoo.rst b/docs/source/api/model.zoo.rst
@@ -69,6 +69,16 @@ GNN OGB Predictor
 .. automodule:: dgllife.model.model_zoo.gnn_ogb_predictor
     :members:
 
+Neural Fingerprint Predictor
+````````````````````````````
+.. automodule:: dgllife.model.model_zoo.nf_predictor
+    :members:
+
+Path-Augmented Graph Transformer Predictor
+``````````````````````````````````````````
+.. automodule:: dgllife.model.model_zoo.pagtn_predictor
+    :members:
+
 Generative Models
 -----------------
 
@@ -77,6 +87,11 @@ DGMG
 .. automodule:: dgllife.model.model_zoo.dgmg
     :members:
 
+JTNNVAE
+```````
+.. automodule:: dgllife.model.model_zoo.jtvae
+    :members:
+
 Reaction Prediction
 
 WLN for Reaction Center Prediction
@@ -95,3 +110,8 @@ ACNN
 ````
 .. automodule:: dgllife.model.model_zoo.acnn
     :members:
+
+PotentialNet
+````````````
+.. automodule:: dgllife.model.model_zoo.potentialnet
+    :members:
diff --git a/docs/source/api/utils.complexes.rst b/docs/source/api/utils.complexes.rst
@@ -9,3 +9,4 @@ Utilities in DGL-LifeSci for working with protein-ligand complexes.
     :toctree: ../generated/
 
     dgllife.utils.ACNN_graph_construction_and_featurization
+    dgllife.utils.PN_graph_construction_and_featurization
diff --git a/docs/source/api/utils.mols.rst b/docs/source/api/utils.mols.rst
@@ -130,6 +130,8 @@ For using featurization methods like above in creating node features:
     dgllife.utils.PretrainAtomFeaturizer
     dgllife.utils.AttentiveFPAtomFeaturizer
     dgllife.utils.AttentiveFPAtomFeaturizer.feat_size
+    dgllife.utils.PAGTNAtomFeaturizer
+    dgllife.utils.PAGTNAtomFeaturizer.feat_size
 
 Featurization for Edges
 ```````````````````````
@@ -164,3 +166,5 @@ For using featurization methods like above in creating edge features:
     dgllife.utils.PretrainBondFeaturizer
     dgllife.utils.AttentiveFPBondFeaturizer
     dgllife.utils.AttentiveFPBondFeaturizer.feat_size
+    dgllife.utils.PAGTNEdgeFeaturizer
+    dgllife.utils.PAGTNEdgeFeaturizer.feat_size
diff --git a/docs/source/api/utils.pipeline.rst b/docs/source/api/utils.pipeline.rst
@@ -21,4 +21,4 @@ Early stopping is a standard practice for preventing models from overfitting and
 class for handling it.
 
 .. autoclass:: dgllife.utils.EarlyStopping
-    :members:
+    :members: step
diff --git a/docs/source/cli.rst b/docs/source/cli.rst
@@ -0,0 +1,35 @@
+.. _cli:
+
+Command Line Interface
+======================
+
+DGL-LifeSci provides command line interfaces that allow users
+to perform modeling without any background in programming and
+deep learning. In addition to installation, you will need to
+clone the github repo with
+
+.. code:: bash
+
+    git clone https://github.com/awslabs/dgl-lifesci.git
+
+Molecular Property Prediction
+-----------------------------
+
+Go to the directory below with
+
+.. code:: bash
+
+    cd dgl-lifesci/examples/property_prediction/csv_data_configuration/
+
+and then follow the README file.
+
+Reaction Prediction
+-------------------
+
+Go to the directory below with
+
+.. code:: bash
+
+    cd dgl-lifesci/examples/reaction_prediction/rexgen_direct/
+
+and then follow the README file.
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -2,25 +2,12 @@ DGL-LifeSci: Bringing Graph Neural Networks to Chemistry and Biology
 ===========================================================================================
 
 DGL-LifeSci is a python package for applying graph neural networks to various tasks in chemistry
-and biology, on top of PyTorch and DGL. It provides:
+and biology, on top of PyTorch, DGL, and RDKit. It covers various applications, including:
 
-* Various utilities for data processing, training and evaluation.
-* Efficient and flexible model implementations.
-* Pre-trained models for use without training from scratch.
-
-We cover various applications in our
-`examples <https://github.com/awslabs/dgl-lifesci/tree/master/examples>`_, including:
-
-* `Molecular property prediction <https://github.com/awslabs/dgl-lifesci/tree/master/examples/property_prediction>`_
-* `Attention visualization <https://github.com/awslabs/dgl-lifesci/tree/master/examples/property_prediction/pubchem_aromaticity>`_
-* `Generative models <https://github.com/awslabs/dgl-lifesci/tree/master/examples/generative_models>`_
-* `Protein-ligand binding affinity prediction <https://github.com/awslabs/dgl-lifesci/tree/master/examples/binding_affinity_prediction>`_
-* `Reaction prediction <https://github.com/awslabs/dgl-lifesci/tree/master/examples/reaction_prediction>`_
-
-Get Started
-------------
-
-Follow the :doc:`instructions<install/index>` to install DGL.
+* Molecular property prediction
+* Generative models
+* Reaction prediction
+* Protein-ligand binding affinity prediction
 
 .. toctree::
    :maxdepth: 1
@@ -29,6 +16,7 @@ Follow the :doc:`instructions<install/index>` to install DGL.
    :glob:
 
    install/index
+   cli
 
 .. toctree::
     :maxdepth: 2
@@ -50,7 +38,3 @@ Free software
 -------------
 DGL-LifeSci is free software; you can redistribute it and/or modify it under the terms
 of the Apache License 2.0. We welcome contributions. Join us on `GitHub <https://github.com/awslabs/dgl-lifesci>`_.
-
-Index
------
-* :ref:`genindex`
diff --git a/docs/source/install/index.rst b/docs/source/install/index.rst
@@ -1,11 +1,9 @@
-Install DGL-LifeSci
-===================
-
-This topic explains how to install DGL-LifeSci. We recommend installing DGL-LifeSci by using ``conda`` or ``pip``.
+Installation
+============
 
 System requirements
 -------------------
-DGL-LifeSci works with the following operating systems:
+DGL-LifeSci should work on:
 
 * Ubuntu 16.04
 * macOS X
@@ -17,15 +15,6 @@ DGL-LifeSci requires:
 * `DGL 0.4.3 or later <https://www.dgl.ai/pages/start.html>`_
 * `PyTorch 1.2.0 or later <https://pytorch.org/>`_
 
-If you have just installed DGL, the first time you use it, a message will pop up as follows:
-
-.. code:: bash
-
-    DGL does not detect a valid backend option. Which backend would you like to work with?
-    Backend choice (pytorch, mxnet or tensorflow):
-
-and you need to enter ``pytorch``.
-
 Additionally, we require **RDKit 2018.09.3** for cheminformatics. We recommend installing it with
 
 .. code:: bash
@@ -34,15 +23,6 @@ Additionally, we require **RDKit 2018.09.3** for cheminformatics. We recommend i
 
 Other verions of RDKit are not tested.
 
-Install from conda
-----------------------
-If ``conda`` is not yet installed, get either `miniconda <https://conda.io/miniconda.html>`_ or
-the full `anaconda <https://www.anaconda.com/download/>`_.
-
-.. code:: bash
-
-    conda install -c dglteam dgllife
-
 Install from pip
 ----------------
 

diff --git a/python/dgllife/model/model_zoo/weave_predictor.py b/python/dgllife/model/model_zoo/weave_predictor.py
@@ -46,10 +46,10 @@ class WeavePredictor(nn.Module):
         specifies the mean and std for constructing a normal
         distribution. This argument comes into effect only when
         ``gaussian_expand==True``. By default, we set this to be
-        ``[(-1.645, 0.283), (-1.080, 0.170), (-0.739, 0.134),
-        (-0.468, 0.118), (-0.228, 0.114), (0., 0.114),
-        (0.228, 0.114), (0.468, 0.118), (0.739, 0.134),
-        (1.080, 0.170), (1.645, 0.283)]``.
+        a list consisting of ``(-1.645, 0.283)``, ``(-1.080, 0.170)``,
+        ``(-0.739, 0.134)``, ``(-0.468, 0.118)``, ``(-0.228, 0.114)``, ``(0., 0.114)``,
+        ``(0.228, 0.114)``, ``(0.468, 0.118)``, ``(0.739, 0.134)``,
+        ``(1.080, 0.170)``, ``(1.645, 0.283)``.
     readout_activation : callable
         Activation function to be used in computing graph
         representations out of node representations. Default to Tanh.

diff --git a/python/dgllife/model/readout/weave_readout.py b/python/dgllife/model/readout/weave_readout.py
@@ -30,9 +30,9 @@ class WeaveGather(nn.Module):
         For each tuple, the first and second element separately specifies the mean
         and std for constructing a normal distribution. This argument comes into
         effect only when ``gaussian_expand==True``. By default, we set this to be
-        ``[(-1.645, 0.283), (-1.080, 0.170), (-0.739, 0.134), (-0.468, 0.118),
-        (-0.228, 0.114), (0., 0.114), (0.228, 0.114), (0.468, 0.118),
-        (0.739, 0.134), (1.080, 0.170), (1.645, 0.283)]``.
+        a list consisting of ``(-1.645, 0.283)``, ``(-1.080, 0.170)``, ``(-0.739, 0.134)``,
+        ``(-0.468, 0.118)``, ``(-0.228, 0.114)``, ``(0., 0.114)``, ``(0.228, 0.114)``,
+        ``(0.468, 0.118)``, ``(0.739, 0.134)``, ``(1.080, 0.170)``, ``(1.645, 0.283)``.
     activation : callable
         Activation function to apply. Default to tanh.
     """

diff --git a/python/dgllife/utils/analysis.py b/python/dgllife/utils/analysis.py
@@ -142,9 +142,7 @@ def analyze_mols(smiles=None, mols=None, num_processes=1, path_to_export=None):
      'valid_proportion': 0.6666666666666666,  # Proportion of valid molecules
      'cano_smi': ['CCO',                      # Canonical SMILES for valid molecules
      'CC1(C)S[C@@H]2[C@H](NC(=O)Cc3ccccc3)C(=O)N2[C@H]1C(=O)O'],
-
      # The following items give the number of times each descriptor value appears in molecules
-
      'atom_type_frequency': {'O': 2, 'C': 2, 'N': 1, 'S': 1},
      'degree_frequency': {1: 2, 2: 2, 3: 1, 4: 1},
      'total_degree_frequency': {2: 2, 4: 2, 1: 1, 3: 1},

diff --git a/python/dgllife/utils/featurizers.py b/python/dgllife/utils/featurizers.py
@@ -1234,9 +1234,9 @@ class PretrainAtomFeaturizer(object):
         choice of 1-118.
     chiral_types : list of Chem.rdchem.ChiralType or None
         Atom chirality to consider for one-hot encoding. If None, we will use a default
-        choice of ``Chem.rdchem.ChiralType.CHI_UNSPECIFIED,
-        Chem.rdchem.ChiralType.CHI_TETRAHEDRAL_CW,
-        Chem.rdchem.ChiralType.CHI_TETRAHEDRAL_CCW, Chem.rdchem.ChiralType.CHI_OTHER``.
+        choice, including ``Chem.rdchem.ChiralType.CHI_UNSPECIFIED``,
+        ``Chem.rdchem.ChiralType.CHI_TETRAHEDRAL_CW``,
+        ``Chem.rdchem.ChiralType.CHI_TETRAHEDRAL_CCW``, ``Chem.rdchem.ChiralType.CHI_OTHER``.
 
     Examples
     --------
Original file line number	Diff line number	Diff line change
Expand Up		@@ -9,3 +9,4 @@ Utilities in DGL-LifeSci for working with protein-ligand complexes.
		:toctree: ../generated/

		dgllife.utils.ACNN_graph_construction_and_featurization
		dgllife.utils.PN_graph_construction_and_featurization