GitLab

* Refactor GCN example

* Refactor GCN based on graphsage

* Readme update

* Minor update

* update

* Remove user-defined GCN implementation

* README update

* Update

* Update CONTRIBUTORS.md

* update task_example_test
Co-authored-by: Xin Yao <xiny@nvidia.com>

* rm gcn spmv

* remove useless test

* remove useless test
Co-authored-by: Ubuntu <ubuntu@ip-172-31-51-214.ec2.internal>

* refactor graph conv

* docs & tests

* fix lint

* fix lint

* fix lint

* fix lint script

* fix lint

* Update

* Style fix

* Fix style

* Fix style

* Fix gpu case

* Fix for gpu case

* Hotfix edgesoftmax docs

* Handle repeated features

* Add docstring

* Set default arguments

* Remove dropout from nn.conv

* Fix

* add util fn for renaming

* revert gcn_spmv.py

* mx folder

* fix wierd bug

* fix mx

* fix lint

* Update prerequisites of README

* dependencies for pytorch models

* dependencies for mxnet models

* minor

* fix gat residual bug

* fix the residual addition; output heads; add some shape notations;

* minor

* fix the output head average

* add requests package in requirement

* update example readme

* mx example readme

* add results in readme

* mx rgcn readme

* update readme.

* update readme

1. Update `examples/pytorch/gcn` and `python/dgl/nn/pytorch` based on the latest APIs
2. Add full support for dropout in `examples/pytorch/gcn` and `python/dgl/nn/pytorch`
3. Rename `GCN` class in `python/dgl/nn/pytorch` to be `GraphConvolutionLayer` class
4. Make node field an argument that can be configured by users in GraphConvolutionLayer

Note that adjacency normalization has not been supported yet in the examples. 

* synthetic dataset

* some fix

* gcn readme