GitLab

* change ci image

* fix

* force bash

* fix

* fix python version

* fix

* fix

* fix

* update gpu

* cuda

* jenkins

* fix build sh

* fix

* Revert "fix"

This reverts commit 6b091914b3ef6b4300fa662ee375aa4b27944f5c.

* try fix

* fix

* Revert "fix"

This reverts commit e42c3035fa4974c6b197aaba0748f7b45113ddaa.

* try fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix tests

* try fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix ctx problem

* fix many tests

* fix typo

* add backend

* move to pytorch folder

* fix?

* fix ci

* try skip

* try false

* try?

* try?

* Revert to 7d9a52f

* fix various

* fix lint

* Revert Jenkinsfile

* revert env

* revert env

* address comment

* remove file

* upd

* fig edgebatch edges

* add test

* trigger

* Update README.md for pytorch PinSage example.

Add noting that the PinSage model example under
example/pytorch/recommendation only work with Python 3.6+
as its dataset loader depends on stanfordnlp package
which work only with Python 3.6+.

* Provid a frame agnostic API to test nn modules on both CPU and CUDA side.

1. make dgl.nn.xxx frame agnostic
2. make test.backend include dgl.nn modules
3. modify test_edge_softmax of test/mxnet/test_nn.py and
    test/pytorch/test_nn.py work on both CPU and GPU

* Fix style

* Delete unused code

* Make agnostic test only related to tests/backend

1. clear all agnostic related code in dgl.nn
2. make test_graph_conv agnostic to cpu/gpu

* Fix code style

* fix

* doc

* Make all test code under tests.mxnet/pytorch.test_nn.py
work on both CPU and GPU.

* Fix syntex

* Remove rand

* Add TAGCN nn.module and example

* Now t...

* use the right version of mxnet.

* fix.

* new jenkins script

* fix ci

* poke ci

* new config

* new config

* new config

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* update docker image; poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* poke ci

* update image

* update image

* fix

* Windows CI support

* typo

* typo*2

* missed sh

* typo*3

* missed dir

* use mxnet 20190528 build

* fix mxnet api name

* update docker image

* specify lint version

* rm torch import from unified tests

* new capsule tutorial

* capsule for new API

* fix deprecated API

* New tutorial and example

* investigate gc problem

* add viz code

* new capsule tutorial

* remove ipynb

* move u_hat

* add link

* add requirements.txt

* remove ani.save

* update ci to install requirements

* add graphviz

* change ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* update ci

* nx package

* update ci

* update ci

* update ci

* fix

* mx dockerfile by zhengda

* python3.6->3.5

* update ci image

* add tutorial test

* fix ci

* fix ssl problem

* minor change

* small fix on traversal utest

* fix syntax

* add matplotlib in image

* fix

* update ci

* update ci

* Test CPP branch CI (#2)

* Fix batching node-only graphs (#62)

* fixing batching with graphs with no edges

* oops forgot test

* fix readme

* Docker and Jenkins (#1)

* docker ci cpu

* install python packages

* docker ci gpu

* add readme

* use dgl cpu image

* run command in container as root

* use python3

* fix test case

* remove nose from docker file

* docker folder readme

* parallelize cpu and gpu

* top level stages

* comment out python2 related installation

* fix

* remove igraph

* building for cpp

* change building order

* export env in test stage

* withEnv

* run docker container as root

* fix test cases

* fix test cases

* minor

* remove old build