Merge b71a8aa into b1cac7b

docs/models.rst

@@ -1,7 +1,11 @@
 Model Classes
 =============
 
-DeepChem maintains an extensive collection of models for scientific applications.
+DeepChem maintains an extensive collection of models for scientific
+applications. DeepChem's focus is on facilitating scientific applications, so
+we support a broad range of different machine learning frameworks (currently
+scikit-learn, xgboost, TensorFlow, and PyTorch) since different frameworks are
+more and less suited for different scientific applications.
 
 Model Cheatsheet
 ----------------
@@ -125,29 +129,51 @@ read off what's needed to train the model from the table below.
 +----------------------------------------+------------+----------------------+------------------------+----------------------------------------------------------------+----------------------+
 | :code:`WGAN`                           | Adversarial| Pair                 |                        |                                                                | :code:`fit_gan`      |
 +----------------------------------------+------------+----------------------+------------------------+----------------------------------------------------------------+----------------------+
+| :code:`CGCNNModel`                     | Classifier/| :code:`GraphData`    |                        | :code:`CGCNNFeaturizer`                                        | :code:`fit`          |
+|                                        | Regressor  |                      |                        |                                                                |                      |
++----------------------------------------+------------+----------------------+------------------------+----------------------------------------------------------------+----------------------+
+| :code:`GATModel`                       | Classifier/| :code:`GraphData`    |                        | :code:`MolGraphConvFeaturizer`                                 | :code:`fit`          |
+|                                        | Regressor  |                      |                        |                                                                |                      |
++----------------------------------------+------------+----------------------+------------------------+----------------------------------------------------------------+----------------------+
 
 Model
 -----
 
 .. autoclass:: deepchem.models.Model
   :members:
 
+Scikit-Learn Models
+===================
+
+Scikit-learn's models can be wrapped so that they can interact conveniently
+with DeepChem. Oftentimes scikit-learn models are more robust and easier to
+train and are a nice first model to train.
+
 SklearnModel
 ------------
 
 .. autoclass:: deepchem.models.SklearnModel
   :members:
 
+Xgboost Models
+==============
+
+Xgboost models can be wrapped so they can interact with DeepChem.
+
 XGBoostModel
 ------------
 
 .. autoclass:: deepchem.models.XGBoostModel
   :members:
 
 
-Keras Models
-============
-DeepChem extensively uses `Keras`_ to build powerful machine learning models.
+Deep Learning Infrastructure
+============================
+
+DeepChem maintains a lightweight layer of common deep learning model
+infrastructure that can be used for models built with different underlying
+frameworks. The losses and optimizers can be used for both TensorFlow and
+PyTorch models.
 
 Losses
 ------
@@ -216,6 +242,12 @@ Optimizers
   :members:
 
 
+Keras Models
+============
+
+DeepChem extensively uses `Keras`_ to build deep learning models.
+
+
 KerasModel
 ----------
 
@@ -373,3 +405,31 @@ ChemCeption
 
 .. autoclass:: deepchem.models.ChemCeption
   :members:
+
+PyTorch Models
+==============
+
+DeepChem supports the use of `PyTorch`_ to build deep learning models.
+
+.. _`PyTorch`: https://pytorch.org/ 
+
+TorchModel
+----------
+
+You can wrap an arbitrary :code:`torch.nn.Module` in a :code:`TorchModel` object.
+
+.. autoclass:: deepchem.models.TorchModel
+  :members:
+
+CGCNNModel
+----------
+
+.. autoclass:: deepchem.models.CGCNNModel
+  :members:
+
+
+GATModel
+--------
+
+.. autoclass:: deepchem.models.GATModel
+  :members:

docs/requirements.txt

@@ -3,3 +3,5 @@ scikit-learn
 sphinx_rtd_theme
 tensorflow==2.2.0
 transformers
+xgboost
+torch==1.6.0