* Several optimizations on DGL-KG:
1. Sorted positive edges for sampling which can reduce random
memory access during positive sampling
2. Asynchronous node embedding update
3. Balanced Relation Partition that gives balanced number of
edges in each partition. When there is no cross partition
relation, relation embedding can be pin into GPU memory
4. tunable neg_sample_size instead of fixed neg_sample_size
* Fix test
* Fix test and eval.py
* Now TransR is OK
* Fix single GPU with mix_cpu_gpu
* Add app tests
* Fix test script
* fix mxnet
* Fix sample
* Add docstrings
* Fix
* Default value for num_workers
* Upd
* upd
* unit graph that prefers coo queries
* auto detect coo preference
* forgot some functions
* disable lint on detect_prefer_coo
* reorg
* change comment
* lint
* fix
* move array_utils.h to src
* compact graph impl
* fix redundant copying in idhashmap
* docstring
* moving preference detection to C
* lint
* fix unit test & address comments
* hypersparse autorestrict
* docstring & fix
* revert copyto and asnumbits
* fix stupid bug
* lint
* leave a TODO for sorted COO
* fixing same node type mapping to different id in different graphs
* addresses comments
* made induced nodes a feautre column
* lint?
* 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
Minjie Wang