GitLab

* Edit for grammar and style

In the opening paragraph, it would be helpful to provide some overall scenario and the prerequisites you expect readers to have completed before they start here. "This tutorial assumes you have already..." Add a link to Install DGL topic perhaps and any other framework or IDE or even specialized knowledge. With this context, you help readers to succeed by setting expectations.

Better to group all tutorials (this, PageRank with, Batched Graph, Working with) at the same level in the left navigation rail and all as subsections of DGL Basics.

* Update tutorials/basics/2_basics.py

* 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 tagcn can run on CPU.

* Add unitest for TGConv

* Fix style

* For pubmed dataset, using --lr=0.005 can achieve better acc

* Fix style

* Fix some descriptions

* trigger

* Fix doc

* Add nn.TGConv and example

* Fix bug

* Update data in mxnet.tagcn test acc.

* Fix some comments and code

* delete useless code

* Fix namming

* Fix bug

* Fix bug

* Add test for mxnet TAGCov

* Add test code for mxnet TAGCov

* Update some docs

* Fix some code

* Update docs dgl.nn.mxnet

* Update weight init

* Fix

* reproduce the bug

* Fix concurrency bug reported at #755.
Also make test_shared_mem_store.py more deterministic.

* Update test_shared_mem_store.py

* Update dmlc/core

* networkx >= 2.4 will break our examples

* Update tutorials/requirements

* fix selfloop edges

* upd version

Simple editorial updates

* heterograph tutorial skeleton

* [WIP][Tutorial] Heterogeneous graph tutorial

* fix

* update

* enable tutorial test in CI.

* reduce overhead.

* fix doc

* fix some format and warnings

* fix

* doc page for builtin functions; install from source doc

* upload rst

* update

* minor fix

* Update 2_giant.py

* fix.

* fix.

* tutorial.

* update images.

* add index.

* update.

* update tutorial.

* add sampling tutorial.

* add readme

* update author list.

* fix indent in the code.

* rename the file.

* update tutorial.

* fix the last API.

* update image.

* Update 9_gat.py

* Update 1_gcn.py

* refactored sampler code

* docstring

* fix tutorial

* don't return aux_info.

* fix sampler test.

* fix sse.

* fix.

* add comment.

* 9_gat.py

* readme

* Update 9_gat.py

* Update 9_gat.py

* fix format

* sample layer subgraphs.

* fix.

* fix.

* add layered subgraph.

* fix lint.

* fix.

* fix tutorial.

* fix.

* remove copy_to_parent.

* add num_layers

* move sampling code to sampler.cc

* fix.

* move subgraph construction out.

* Revert "move subgraph construction out."

This reverts commit 24b3d13b0d8ed5f91847ea75a7674ee8f7d45cff.

* change to NodeFlow.

* use NodeFlow in Python.

* use NodeFlowIndex.

* add node_mapping and edge_mapping.

* remove unnecessary code in SSE tutorial.

* Revert "remove unnecessary code in SSE tutorial."

This reverts commit 093f0413d5fa2e63ca5f80c46c80a126a9fb720c.

* fix tutorial.

* move to node_flow.

* update gcn cv updater.

* import NodeFlow.

* update.

* add demo code for vanilla control variate sampler.

* update.

* update.

* add neighbor sampling.

* return flow offsets.

* update node_flow.

* add test.

* fix sampler.

* fix graph index.

* fix a bug in sampler.

* fix map_to_layer_nid and map_to_flow_eid.

* fix apply_flow.

* remove model code.

* implement flow_compute.

* fix a bug.

* reverse the csr physically.

* add mini-batch test.

* add mini batch test.

* update flow_compute.

* add prop_flows

* run on specific nodes.

* test copy

* fix a bug in creating frame in NodeFlow.

* add init gcn_cv_updater.

* fix a minor bug.

* fix gcn_cv_updater.

* fix a bug.

* fix a bug in NodeFlow.

* use new h in gcn_cv_updater.

* add layer_in_degree and layer_out_degree.

* fix gcn_cv_updater for gpu.

* temp fix in NodeFlow for diff context.

* allow enabling/disabling copy back.

* add with-updater option.

* fix a bug in computing degree.

* add with-cv option.

* rename and add comments.

* fix lint complain.

* fix lint.

* avoid assert.

* remove assert.

* fix.

* fix.

* fix.

* fix.

* fix the methods in NodeFlow.

* fix lint.

* update SSE.

* remove gcn_cv_updater.

* correct comments for the schedulers.

* update comment.

* add map_to_nodeflow_nid

* address comment.

* remove duplicated test.

* fix int.

* fix comments.

* fix lint

* fix.

* replace subgraph with NodeFlow.

* move view.

* address comments.

* fix lint.

* fix lint.

* remove static_cast.

* fix docstring.

* fix comments.

* break SampleSubgraph.

* move neighbor sampling to sampler.cc

* fix comments.

* rename.

* split neighbor_list.

* address comments.

* fix.

* remove TODO.

* fix rgcn tutorial

* small fix

* upd

* batched_graph_classification

* Fix

* Fix

* update tutorial with new dataset

* Final

* Fix doc for dataset

* small fix

* minor spelling tweaks

* Update CONTRIBUTORS.md

* reorg the doc mainpage

* contribute guide

* update GNN tutorial.

* Update README.txt

* remove loading backend in sse

* build mxnet in a second run

* a third run to fix everything

* fix docstring in sampler

* fix docstring in transformer

* README for doc build

* some reordering and printing

* use filename_pattern instead of ignore_pattern to reduce warning at the cost of redundant work...

* add env var to use mxnet in Jenkinsfile

* remove step 3, it's already fixed by previous commit

* update version; add news.md; modify contributing.md

* change urls to dmlc

* upd tutorial

* upd tutorial

* change the signature of node/edge filter

* upd filter

* Support multi-dimension node feature in SPMV

* push transformer

* remove some experimental settings

* stable version

* hotfix

* upd tutorial

* upd README

* merge

* remove redundency

* remove tqdm

* several changes

* Refactor

* Refactor

* tutorial train

* fixed a bug

* fixed perf issue

* upd

* change dir

* move un-related to contrib

* tutuorial code

* remove redundency

* upd

* upd

* upd

* upd

* improve viz

* universal done

* halt norm

* fixed a bug

* add draw graph

* fixed several bugs

* remove dependency on core

* upd format of README

* trigger

* trigger

* upd viz

* trigger

* add transformer tutorial

* fix tutorial

* fix readme

* small fix on tutorials

* url fix in readme

* fixed func link

* upd

* move pytorch code to examples.

* fix.

* fix tutorial

* add sse tutorial

* add mxnet tutorial ci

* fix ci

* fix ci

* fix ci

* fix ci

* fix ci

* fix ci

* Fix ci

* Fix ci

* Fix ci

* fix ci

* fix ci

* fix ci

* fix ci

* fix ci

* fix ci

* Fix CI

Fix CI image

* permission fix

* fix a bug in the code.

* small fix

* fix doc

* fix ci

* shorten the iters

* fix

* remove extra file

* add load_backend api to dynamically switch to another backend

* try fix

* fix tutorial

* fix tutorial

* fix bug in tutorial

* fix all code tutorial links and typos in texts

* sse readme format

* fix

* sse paper link

* gat readme

* fix

* change Index.tolist -> Index.tonumpy; fix bug in traversal; remove dependencies in data

* fix import

* fix __all__ and some docstring

* improve capsule tutorial with jinyang

* fix wrong layout of second-level tutorial

* delete transformer

* tutorial notebook added

* lg tutorial cleaned up

* dataset scaffold

* move dataloader to data

* fix model

* remove todo

* utils seperated

* [model]line graph new implementation + tutorial + binary sub graph dataset

* [tutorial] line graph sphinx scaffold

* [tutorial] lgnn tutorial improved

* [tutorial] remove notebook

* [tutorial] fix lg and gcn links

* [tutorial] fix random seed

* [tutorial]fix

* WIP

* code refactor done

* new mini dataset; remove utils code

* fix

* word fix

* fix link

* minor fix

* minor fix

* minor fix

* model tutorials overview

* update the 1_first

* revised overview and summarized "what is DGL" in glance

* WIP

* new at glance