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* Change Byte to Bool for training masks

* Check if module has Bool, otherwise use Byte

* refactor

* upd mpnn

* gat

* upd

* upd sage

* upd

* upd

* upd

* upd

* upd

* add gmmconv

* upd ggnn

* upd

* upd

* upd

* upd

* add citation examples

* add README

* fix cheb

* improve doc

* formula

* upd

* trigger

* lint

* lint

* upd

* add test for transform

* add test

* check

* upd

* improve doc

* shape check

* upd

* densechebconv, currently not correct (?)

* fix cheb

* fix

* upd

* upd sgc-reddit

* upd

* trigger

* all pytorch examples

* scan through mxnet examples

* change reddit data

* tweak numerical range for unittest

* fix ci

* fix ci

* fix

* add seed to workaround

* [Model] Add edge dropout to APPNP

[Model] Add edge dropout to APPNP

* [Model] Refactor the sampling examples (#498)

* reorganize sampling code.

* speedup gcn_ns.

* speed up gcn_cv

* fix graphsage_cv.

* undo the modification.

* accel training.

* update readme.

* [Model] Add edge dropout to APPNP

[Model] Add edge dropout to APPNP

update

* [Model] Add APPNP model

* update

* Revert "update"

This reverts commit a8e42d19c8b421fb382305a8f04d7426e78ea53c.

* update

* Update appnp.py