GCMC Implementation (#524)

* aligned parameters to follow example

* fixed dgl issues for cuda runs

* Added biasedMF, pmf to example

* Fix bug in creating coo matrix when creating decoder graph

* Extend transform function, support None val_set

* Reorganised codes to individual files

* Added documentation

* Reorganized codes to smaller functions

* Update README.md to include GCMC

* Set verbose to False by default

* example file cleanup

* cleanup - missing empty row

* Updated examples readme

* Moved import to inner functions

* clean up test.sh

* list model alphabetically

* Add GCMC model in docs


---------

Co-authored-by: tqtg <tuantq.vnu@gmail.com>

README.md

@@ -115,6 +115,7 @@ The recommender models supported by Cornac are listed below. Why don't you join
 |      | [Hybrid neural recommendation with joint deep representation learning of ratings and reviews (HRDR)](cornac/models/hrdr), [paper](https://www.sciencedirect.com/science/article/abs/pii/S0925231219313207) | [requirements.txt](cornac/models/hrdr/requirements.txt) | [hrdr_example.py](examples/hrdr_example.py)
 | 2019 | [Embarrassingly Shallow Autoencoders for Sparse Data (EASEᴿ)](cornac/models/ease), [paper](https://arxiv.org/pdf/1905.03375.pdf) | N/A | [ease_movielens.py](examples/ease_movielens.py)
 | 2018 | [Collaborative Context Poisson Factorization (C2PF)](cornac/models/c2pf), [paper](https://www.ijcai.org/proceedings/2018/0370.pdf) | N/A | [c2pf_exp.py](examples/c2pf_example.py)
+|      | [Graph Convolutional Matrix Completion (GCMC)](cornac/models/gcmc), [paper](https://www.kdd.org/kdd2018/files/deep-learning-day/DLDay18_paper_32.pdf) | [requirements.txt](cornac/models/gcmc/requirements.txt) | [gcmc_example.py](examples/gcmc_example.py)
 |      | [Multi-Task Explainable Recommendation (MTER)](cornac/models/mter), [paper](https://arxiv.org/pdf/1806.03568.pdf) | N/A | [mter_exp.py](examples/mter_example.py)
 |      | [Neural Attention Rating Regression with Review-level Explanations (NARRE)](cornac/models/narre), [paper](http://www.thuir.cn/group/~YQLiu/publications/WWW2018_CC.pdf) | [requirements.txt](cornac/models/narre/requirements.txt) | [narre_example.py](examples/narre_example.py)
 |      | [Probabilistic Collaborative Representation Learning (PCRL)](cornac/models/pcrl), [paper](http://www.hadylauw.com/publications/uai18.pdf) | [requirements.txt](cornac/models/pcrl/requirements.txt) | [pcrl_exp.py](examples/pcrl_example.py)

cornac/models/__init__.py

@@ -33,6 +33,7 @@
 from .cvaecf import CVAECF
 from .ease import EASE
 from .efm import EFM
+from .gcmc import GCMC
 from .global_avg import GlobalAvg
 from .hft import HFT
 from .hpf import HPF

cornac/models/gcmc/__init__.py

@@ -0,0 +1,16 @@
+# Copyright 2018 The Cornac Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+from .recom_gcmc import GCMC