* 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
* Update Knowledge Graph CI with new Docker image
* Remove unused line_profierx
* Poke Jenkins
* Update test with exit code check and simplify docker
* Update Jenkinsfile to make app test a standalone stage
* Update kg_test
* Update Jenkinsfile
* Make some KG test parallel
* Update
* KG MXNet does not support ComplEx
* Update Jenkinsfile
* Update Jenkins file
* Change torch-1.2 to torch-1.2-cu92
* ci
* Update ubuntu_install_mxnet_cpu.sh
* Update ubuntu_install_mxnet_gpu.sh
* We only need to test train and eval script.
Delete some test code
* 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
* init version.
* change default value of regularization.
* avoid specifying adversarial_temperature
* use default eval_interval.
* remove original model.
* remove optimizer.
* set default value of num_proc
* set default value of log_interval.
* don't need to set neg_sample_size_valid.
* remove unused code.
* use uni_weight by default.
* unify model.
* rename model.
* remove unnecessary data sampler.
* remove the code for checkpoint.
* fix eval.
* raise exception in invalid arguments.
* remove RowAdagrad.
* remove unsupported score function for now.
* Fix bugs of kg
Update README
* Update Readme for mxnet distmult
* Update README.md
* Update README.md
* revert changes on dmlc
* add tests.
* update CI.
* add tests script.
* reorder tests in CI.
* measure performance.
* add results on wn18
* remove some code.
* rename the training script.
* new results on TransE.
* remove --train.
* add format.
* fix.
* use EdgeSubgraph.
* create PBGNegEdgeSubgraph to simplify the code.
* fix test
* fix CI.
* run nose for unit tests.
* remove unused code in dataset.
* change argument to save embeddings.
* test training and eval scripts in CI.
* check Pytorch version.
* fix a minor problem in config.
* fix a minor bug.
* fix readme.
* Update README.md
* Update README.md
* Update README.md
* fix graph store for Pytorch.
* add test.
* fix dtype error in test
* disable test on GPU.
* test avoid windows.
* fix shared-memory test.
* use script to control testing environment.
* update test.
* enable all tests.
* fix test script.
* cmake fixes for older systems
* allow specification of cuda path
* test script fixes to enable openmp & test
* update minigun; disable minigun partial frontier compile
* to simple
* WIP: multigraph flag
* graph index refactor; pass basic testing
* graph index refactor; pass basic testing
* fix bug in to_simple; pass torch test
* fix mx utest
* fix example
* fix lint
* fix ci
* poke ci
* poke ci
* WIP
* poke ci
* poke ci
* poke ci
* change ci workspace
* poke ci
* poke ci
* poke ci
* poke ci
* delete ci
* use enum for multigraph flag
* 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
* test basics
* batched graph & filter, mxnet filter fix
* frame and function; bugfix
* test graph adj and inc matrices
* fixing start = 0 for mxnet
* test index
* inplace update & line graph
* multi send recv
* more tests
* oops
* more tests
* removing old test files; readonly graphs for mxnet still kept
* modifying test scripts
* adding a placeholder for pytorch to reserve directory
* torch 0.4.1 compat fixes
* moving backend out of compute to avoid nose detection
* tests guide
* mx sparse-to-dense/sparse-to-numpy is buggy
* oops
* contribution guide for unit tests
* printing incmat
* printing dlpack
* small push
* typo
* fixing duplicate entries that causes undefined behavior
* move equal comparison to backend
* fix lint for graph_index.py
* pylint for base.py
* pylint for batched_graph.py
* pylint for frame.py; simplify and fix bugs in frame when index is slice type
* pylint for graph.py
* pylint for immutable_graph_index.py
* pylint for init.py
* pylint for rest files in root package
* pylint for _ffi package
* pylint for function package
* pylint for runtime package
* pylint for runtime.ir package
* add pylint to ci
* fix mx tests
* fix lint errors
* fix ci
* fix as requested
* fix lint
* Jenkins build & test on Windows
* oops
* still running nohup on Windows slaves
* ooops again
* squishing vcvars and cmake
* another try
* reverting back
* --user
* switching to msbuild
* made the graph size in cache testing bigger
* put commands into script files
* oooops
* 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
* 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
* Add SH tutorials
* setup sphinx-gallery; work on graph tutorial
* draft dglgraph tutorial
* update readme to include document url
* rm obsolete file
* Draft the message passing tutorial
* Capsule code (#102)
* add capsule example
* clean code
* better naming
* better naming
* [GCN]tutorial scaffold
* fix capsule example code
* remove previous capsule example code
* graph struc edit
* modified: 2_graph.py
* update doc of capsule
* update capsule docs
* update capsule docs
* add msg passing prime
* GCN-GAT tutorial Section 1 and 2
* comment for API improvement
* section 3
* Tutorial API change (#115)
* change the API as discusses; toy example
* enable the new set/get syntax
* fixed pytorch utest
* fixed gcn example
* fixed gat example
* fixed mx utests
* fix mx utest
* delete apply edges; add utest for update_edges
* small change on toy example
* fix utest
* fix out in degrees bug
* update pagerank example and add it to CI
* add delitem for dataview
* make edges() return form that is compatible with send/update_edges etc
* fix index bug when the given data is one-int-tensor
* fix doc
xiang song(charlie.song)