e17add5602
[NN] Add MXNet impl for TAGCN module. ( #799 )
...
* 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 code for mxnet TAGCov
* Update some docs
* Fix some code
* Update docs dgl.nn.mxnet
* Update weight init
* Fix
2019-08-28 13:19:17 +08:00
14bffe9728
[NN] Renaming NearestNeighborGraph to KNNGraph ( #802 )
...
* initial commit
* second commit
* another commit
* change docstring
* migrating to dgl.nn
* fixes
* docs
* lint
* multiple fixes
* doc
* renaming nearest neighbor graph
2019-08-28 12:20:35 +08:00
dc19cd5687
[Example] Dynamic Graph CNN on Point Cloud ( #789 )
...
* initial commit
* second commit
* another commit
* change docstring
* migrating to dgl.nn
* fixes
* docs
* lint
* multiple fixes
* doc
2019-08-28 09:21:57 +08:00
e590feeb62
[Model Zoo] GAT on Tox21 ( #793 )
...
* GAT
* Fix mistake
* Fix
* hotfix
* Fix
* Fix
* Fix
* Fix
* Fix
* Fix
* Fix
* Update
* Update
* Update
* Fix style
* Hotfix
* Hotfix
* Hotfix
* Fix
* Fix
* Update
* CI trial
* Update
* Update
* Update
2019-08-28 04:47:16 +08:00
9314aabd1f
[Refactor] Interface of nn modules ( #798 )
...
* refactor
* upd mpnn
2019-08-27 22:29:25 +08:00
650f6ee1e0
[NN] Add commonly used GNN models from examples to dgl.nn modules. ( #748 )
...
* 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
2019-08-27 18:21:19 +08:00
11fb217a76
[NN] Add TAGCN nn.module and example ( #788 )
...
* 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
2019-08-25 22:17:46 +08:00
708765f0a1
[NN] RGCN modules ( #744 )
...
* rgcn module
* support id input
* WIP: model codes
* use faster index select
* dropout
* self loop
* WIP: link prediction
* fix lint
* WIP: docs
* docstring
* docstring
* merge two child classes
* mxnet rgcn module
* fix lint
* fix lint
* fix rename bug
* add uniform edge sampler
* fix fn name
* docstring
* fix mxnet rgcn module
* fix mx rgcn
* enable test on cuda
2019-08-23 16:38:48 -04:00
2bff8339dd
[Test] Provid a frame agnostic API to test nn modules on both CPU and CUDA side. ( #775 )
...
* 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
2019-08-21 16:40:41 +08:00
742d79a792
upd ( #741 )
2019-08-06 18:39:05 +08:00
5d3f470b72
[Feature] DGL Pooling modules ( #669 )
...
* removal doc
* glob
* upd
* rm knn
* add softmax
* upd
* upd
* add broadcast and s2s
* optimize max_on
* forsaken changes to heterograph
* upd
* upd
* upd
* upd
* upd
* bugfix
* upd
* upd
* upd
* upd
* format upd
* upd format
* upd doc
* upd
* import order
* upd
* rm warnings
* fix
* upd test
* upd
* upd
* fix device
* upd
* upd
* upd
* upd
* remove 1.1
* upd
* trigger
* trigger
* add more tests
* fix device
* upd
* upd
* refactor
* fix?
* fix
* upd docstring
* refactor
* upd
* fix
* upd
* upd
* upd
* fix
* upd docs
* add shape
* refactor & upd doc
* upd doc
* upd
2019-08-06 01:43:25 +08:00
fc9d30fae4
[Graph] add local scope function ( #735 )
...
* add local scope function
* fix lint
* fix docstring
* change local_scope to local_var; add context manager
* address comments
2019-08-02 00:11:48 -04:00
fc2e166ba6
[Fix] Fix Memory Leak in Edge Softmax ( #692 )
...
* Add serialization
* fix memory leak
* Revert "Add serialization"
This reverts commit e838bb1faa2503d14593d702be00514f936c9027.
* fix
2019-06-28 17:31:54 -04:00
8ecedfb369
[Fix] Bugfix in docs and check gradient of edge_softmax in test ( #686 )
...
* upd
* Add stronger test
* Update test_nn.py
* Update test_nn.py
* trigger
* trigger
* trigger
2019-06-27 00:43:26 +08:00
5549c70d33
[BugFix] Fix memory leak in DGL edge softmax module ( #643 )
...
* fix gat memory increase bug
* work around mxnet memory leak bug
* comments
* poke linter
* lint
* lint
2019-06-10 18:44:23 -04:00
74e13eea61
[Model] Update GAT model code ( #622 )
...
* fix gat code to use latest edge softmax module
* avoid transpose
* update README
* use edge_softmax op
* mxnet edge softmax op
* mxnet gat
* update README
* fix unittest
* fix ci
* fix mxnet nn test; relax criteria for prod reducer
2019-06-08 21:41:38 -04:00
8bf97719fa
[Bugfix] Fix performance bug in edge softmax operator ( #624 )
2019-06-07 16:15:29 -07:00
34dfaf7532
quick-fix ( #620 )
2019-06-08 00:49:36 +08:00
653428bdc7
[Feature][Kernel] DGL kernel support ( #596 )
...
* [Kernel] Minigun integration and fused kernel support (#519 )
* kernel interface
* add minigun
* Add cuda build
* functors
* working on binary elewise
* binary reduce
* change kernel interface
* WIP
* wip
* fix minigun
* compile
* binary reduce kernels
* compile
* simple test passed
* more reducers
* fix thrust problem
* fix cmake
* fix cmake; add proper guard for atomic
* WIP: bcast
* WIP
* bcast kernels
* update to new minigun pass-by-value practice
* broadcasting dim
* add copy src and copy edge
* fix linking
* fix none array problem
* fix copy edge
* add device_type and device_id to backend operator
* cache csr adj, remove cache for adjmat and incmat
* custom ops in backend and pytorch impl
* change dgl-mg kernel python interface
* add id_mapping var
* clean up plus v2e spmv schedule
* spmv schedule & clean up fall back
* symbolic message and reduce func, remove bundle func
* new executors
* new backend interface for dgl kernels and pytorch impl
* minor fix
* fix
* fix docstring, comments, func names
* nodeflow
* fix message id mapping and bugs...
* pytorch test case & fix
* backward binary reduce
* fix bug
* WIP: cusparse
* change to int32 csr for cusparse workaround
* disable cusparse
* change back to int64
* broadcasting backward
* cusparse; WIP: add rev_csr
* unit test for kernels
* pytorch backward with dgl kernel
* edge softmax
* fix backward
* improve softmax
* cache edge on device
* cache mappings on device
* fix partial forward code
* cusparse done
* copy_src_sum with cusparse
* rm id getter
* reduce grad for broadcast
* copy edge reduce backward
* kernel unit test for broadcasting
* full kernel unit test
* add cpu kernels
* edge softmax unit test
* missing ref
* fix compile and small bugs
* fix bug in bcast
* Add backward both
* fix torch utests
* expose infershape
* create out tensor in python
* fix c++ lint
* [Kernel] Add GPU utest and kernel utest (#524 )
* fix gpu utest
* cuda utest runnable
* temp disable test nodeflow; unified test for kernel
* cuda test kernel done
* [Kernel] Update kernel branch (#550 )
* [Model] add multiprocessing training with sampling. (#484 )
* reorganize sampling code.
* add multi-process training.
* speed up gcn_cv
* fix graphsage_cv.
* add new API in graph store.
* update barrier impl.
* support both local and distributed training.
* fix multiprocess train.
* fix.
* fix barrier.
* add script for loading data.
* multiprocessing sampling.
* accel training.
* replace pull with spmv for speedup.
* nodeflow copy from parent with context.
* enable GPU.
* fix a bug in graph store.
* enable multi-GPU training.
* fix lint.
* add comments.
* rename to run_store_server.py
* fix gcn_cv.
* fix a minor bug in sampler.
* handle error better in graph store.
* improve graphsage_cv for distributed mode.
* update README.
* fix.
* update.
* [Tutorial] add sampling tutorial. (#522 )
* add sampling tutorial.
* add readme
* update author list.
* fix indent in the code.
* rename the file.
* update tutorial.
* fix the last API.
* update image.
* [BUGFIX] fix the problems in the sampling tutorial. (#523 )
* add index.
* update.
* update tutorial.
* fix gpu utest
* cuda utest runnable
* temp disable test nodeflow; unified test for kernel
* cuda test kernel done
* Fixing typo in JTNN after interface change (#536 )
* [BugFix] Fix getting src and dst id of ALL edges in NodeFlow.apply_block (#515 )
* [Bug Fix] Fix inplace op at backend (#546 )
* Fix inplace operation
* fix line seprator
* [Feature] Add batch and unbatch for immutable graph (#539 )
* Add batch and unbatch for immutable graph
* fix line seprator
* fix lintr
* remove unnecessary include
* fix code review
* [BUGFix] Improve multi-processing training (#526 )
* fix.
* add comment.
* remove.
* temp fix.
* initialize for shared memory.
* fix graphsage.
* fix gcn.
* add more unit tests.
* add more tests.
* avoid creating shared-memory exclusively.
* redefine remote initializer.
* improve initializer.
* fix unit test.
* fix lint.
* fix lint.
* initialize data in the graph store server properly.
* fix test.
* fix test.
* fix test.
* small fix.
* add comments.
* cleanup server.
* test graph store with a random port.
* print.
* print to stderr.
* test1
* test2
* remove comment.
* adjust the initializer signature.
* [API] update graph store API. (#549 )
* add init_ndata and init_edata in DGLGraph.
* adjust SharedMemoryGraph API.
* print warning.
* fix comment.
* update example
* fix.
* fix examples.
* add unit tests.
* add comments.
* [Refactor] Immutable graph index (#543 )
* WIP
* header
* WIP .cc
* WIP
* transpose
* wip
* immutable graph .h and .cc
* WIP: nodeflow.cc
* compile
* remove all tmp dl managed ctx; they caused refcount issue
* one simple test
* WIP: testing
* test_graph
* fix graph index
* fix bug in sampler; pass pytorch utest
* WIP on mxnet
* fix lint
* fix mxnet unittest w/ unfortunate workaround
* fix msvc
* fix lint
* SliceRows and test_nodeflow
* resolve reviews
* resolve reviews
* try fix win ci
* try fix win ci
* poke win ci again
* poke
* lazy multigraph flag; stackoverflow error
* revert node subgraph test
* lazy object
* try fix win build
* try fix win build
* poke ci
* fix build script
* fix compile
* add a todo
* fix reviews
* fix compile
* [Kernel] Update kernel branch (#576 )
* [Model] add multiprocessing training with sampling. (#484 )
* reorganize sampling code.
* add multi-process training.
* speed up gcn_cv
* fix graphsage_cv.
* add new API in graph store.
* update barrier impl.
* support both local and distributed training.
* fix multiprocess train.
* fix.
* fix barrier.
* add script for loading data.
* multiprocessing sampling.
* accel training.
* replace pull with spmv for speedup.
* nodeflow copy from parent with context.
* enable GPU.
* fix a bug in graph store.
* enable multi-GPU training.
* fix lint.
* add comments.
* rename to run_store_server.py
* fix gcn_cv.
* fix a minor bug in sampler.
* handle error better in graph store.
* improve graphsage_cv for distributed mode.
* update README.
* fix.
* update.
* [Tutorial] add sampling tutorial. (#522 )
* add sampling tutorial.
* add readme
* update author list.
* fix indent in the code.
* rename the file.
* update tutorial.
* fix the last API.
* update image.
* [BUGFIX] fix the problems in the sampling tutorial. (#523 )
* add index.
* update.
* update tutorial.
* fix gpu utest
* cuda utest runnable
* temp disable test nodeflow; unified test for kernel
* cuda test kernel done
* Fixing typo in JTNN after interface change (#536 )
* [BugFix] Fix getting src and dst id of ALL edges in NodeFlow.apply_block (#515 )
* [Bug Fix] Fix inplace op at backend (#546 )
* Fix inplace operation
* fix line seprator
* [Feature] Add batch and unbatch for immutable graph (#539 )
* Add batch and unbatch for immutable graph
* fix line seprator
* fix lintr
* remove unnecessary include
* fix code review
* [BUGFix] Improve multi-processing training (#526 )
* fix.
* add comment.
* remove.
* temp fix.
* initialize for shared memory.
* fix graphsage.
* fix gcn.
* add more unit tests.
* add more tests.
* avoid creating shared-memory exclusively.
* redefine remote initializer.
* improve initializer.
* fix unit test.
* fix lint.
* fix lint.
* initialize data in the graph store server properly.
* fix test.
* fix test.
* fix test.
* small fix.
* add comments.
* cleanup server.
* test graph store with a random port.
* print.
* print to stderr.
* test1
* test2
* remove comment.
* adjust the initializer signature.
* [API] update graph store API. (#549 )
* add init_ndata and init_edata in DGLGraph.
* adjust SharedMemoryGraph API.
* print warning.
* fix comment.
* update example
* fix.
* fix examples.
* add unit tests.
* add comments.
* [Refactor] Immutable graph index (#543 )
* WIP
* header
* WIP .cc
* WIP
* transpose
* wip
* immutable graph .h and .cc
* WIP: nodeflow.cc
* compile
* remove all tmp dl managed ctx; they caused refcount issue
* one simple test
* WIP: testing
* test_graph
* fix graph index
* fix bug in sampler; pass pytorch utest
* WIP on mxnet
* fix lint
* fix mxnet unittest w/ unfortunate workaround
* fix msvc
* fix lint
* SliceRows and test_nodeflow
* resolve reviews
* resolve reviews
* try fix win ci
* try fix win ci
* poke win ci again
* poke
* lazy multigraph flag; stackoverflow error
* revert node subgraph test
* lazy object
* try fix win build
* try fix win build
* poke ci
* fix build script
* fix compile
* add a todo
* fix reviews
* fix compile
* all demo use python-3 (#555 )
* [DEMO] Reproduce numbers of distributed training in AMLC giant graph paper (#556 )
* update
* update
* update
* update num_hops
* fix bug
* update
* report numbers of distributed training in AMLC giant graph paper
* [DEMO] Remove duplicate code for sampling (#557 )
* update
* update
* re-use single-machine code
* update
* use relative path
* update
* update
* update
* add __init__.py
* add __init__.py
* import sys, os
* fix typo
* update
* [Perf] Improve performance of graph store. (#554 )
* fix.
* use inplace.
* move to shared memory graph store.
* fix.
* add more unit tests.
* fix.
* fix test.
* fix test.
* disable test.
* fix.
* [BUGIFX] fix a bug in edge_ids (#560 )
* add test.
* fix compute.
* fix test.
* turn on test.
* fix a bug.
* add test.
* fix.
* disable test.
* [DEMO] Add Pytorch demo for distributed sampler (#562 )
* update
* update
* update
* add sender
* update
* remove duplicate cpde
* [Test] Add gtest to project (#547 )
* add gtest module
* add gtest
* fix
* Update CMakeLists.txt
* Update README.md
* [Perf] lazily create msg_index. (#563 )
* lazily create msg_index.
* update test.
* [BUGFIX] fix bugs for running GCN on giant graphs. (#561 )
* load mxnet csr.
* enable load large csr.
* fix
* fix.
* fix int overflow.
* fix test.
* [BugFix] Fix error when bfs_level = 0 in Entity Classification with RGCN (#559 )
* [DEMO] Update demo of distributed sampler (#564 )
* update
* update
* update demo
* add network cpp test (#565 )
* Add unittest for C++ RPC (#566 )
* [CI] Fix CI for cpp test (#570 )
* fix CI for cpp test
* update port number
* [Docker] update docker image (#575 )
* update docker image
* specify lint version
* rm torch import from unified tests
* [Kernel][Scheduler][MXNet] Scheduler for DGL kernels and MXNet backend support (#541 )
* [Model] add multiprocessing training with sampling. (#484 )
* reorganize sampling code.
* add multi-process training.
* speed up gcn_cv
* fix graphsage_cv.
* add new API in graph store.
* update barrier impl.
* support both local and distributed training.
* fix multiprocess train.
* fix.
* fix barrier.
* add script for loading data.
* multiprocessing sampling.
* accel training.
* replace pull with spmv for speedup.
* nodeflow copy from parent with context.
* enable GPU.
* fix a bug in graph store.
* enable multi-GPU training.
* fix lint.
* add comments.
* rename to run_store_server.py
* fix gcn_cv.
* fix a minor bug in sampler.
* handle error better in graph store.
* improve graphsage_cv for distributed mode.
* update README.
* fix.
* update.
* [Tutorial] add sampling tutorial. (#522 )
* add sampling tutorial.
* add readme
* update author list.
* fix indent in the code.
* rename the file.
* update tutorial.
* fix the last API.
* update image.
* [BUGFIX] fix the problems in the sampling tutorial. (#523 )
* add index.
* update.
* update tutorial.
* fix gpu utest
* cuda utest runnable
* temp disable test nodeflow; unified test for kernel
* cuda test kernel done
* edge softmax module
* WIP
* Fixing typo in JTNN after interface change (#536 )
* mxnet backend support
* improve reduce grad
* add max to unittest backend
* fix kernel unittest
* [BugFix] Fix getting src and dst id of ALL edges in NodeFlow.apply_block (#515 )
* lint
* lint
* win build
* [Bug Fix] Fix inplace op at backend (#546 )
* Fix inplace operation
* fix line seprator
* [Feature] Add batch and unbatch for immutable graph (#539 )
* Add batch and unbatch for immutable graph
* fix line seprator
* fix lintr
* remove unnecessary include
* fix code review
* [BUGFix] Improve multi-processing training (#526 )
* fix.
* add comment.
* remove.
* temp fix.
* initialize for shared memory.
* fix graphsage.
* fix gcn.
* add more unit tests.
* add more tests.
* avoid creating shared-memory exclusively.
* redefine remote initializer.
* improve initializer.
* fix unit test.
* fix lint.
* fix lint.
* initialize data in the graph store server properly.
* fix test.
* fix test.
* fix test.
* small fix.
* add comments.
* cleanup server.
* test graph store with a random port.
* print.
* print to stderr.
* test1
* test2
* remove comment.
* adjust the initializer signature.
* try
* fix
* fix
* fix
* fix
* fix
* try
* test
* test
* test
* try
* try
* try
* test
* fix
* try gen_target
* fix gen_target
* fix msvc var_args expand issue
* fix
* [API] update graph store API. (#549 )
* add init_ndata and init_edata in DGLGraph.
* adjust SharedMemoryGraph API.
* print warning.
* fix comment.
* update example
* fix.
* fix examples.
* add unit tests.
* add comments.
* [Refactor] Immutable graph index (#543 )
* WIP
* header
* WIP .cc
* WIP
* transpose
* wip
* immutable graph .h and .cc
* WIP: nodeflow.cc
* compile
* remove all tmp dl managed ctx; they caused refcount issue
* one simple test
* WIP: testing
* test_graph
* fix graph index
* fix bug in sampler; pass pytorch utest
* WIP on mxnet
* fix lint
* fix mxnet unittest w/ unfortunate workaround
* fix msvc
* fix lint
* SliceRows and test_nodeflow
* resolve reviews
* resolve reviews
* try fix win ci
* try fix win ci
* poke win ci again
* poke
* lazy multigraph flag; stackoverflow error
* revert node subgraph test
* lazy object
* try fix win build
* try fix win build
* poke ci
* fix build script
* fix compile
* add a todo
* fix reviews
* fix compile
* WIP
* WIP
* all demo use python-3 (#555 )
* ToImmutable and CopyTo
* [DEMO] Reproduce numbers of distributed training in AMLC giant graph paper (#556 )
* update
* update
* update
* update num_hops
* fix bug
* update
* report numbers of distributed training in AMLC giant graph paper
* [DEMO] Remove duplicate code for sampling (#557 )
* update
* update
* re-use single-machine code
* update
* use relative path
* update
* update
* update
* add __init__.py
* add __init__.py
* import sys, os
* fix typo
* update
* [Perf] Improve performance of graph store. (#554 )
* fix.
* use inplace.
* move to shared memory graph store.
* fix.
* add more unit tests.
* fix.
* fix test.
* fix test.
* disable test.
* fix.
* [BUGIFX] fix a bug in edge_ids (#560 )
* add test.
* fix compute.
* fix test.
* turn on test.
* fix a bug.
* add test.
* fix.
* disable test.
* DGLRetValue DGLContext conversion
* [DEMO] Add Pytorch demo for distributed sampler (#562 )
* update
* update
* update
* add sender
* update
* remove duplicate cpde
* [Test] Add gtest to project (#547 )
* add gtest module
* add gtest
* fix
* Update CMakeLists.txt
* Update README.md
* Add support to convert immutable graph to 32 bits
* [Perf] lazily create msg_index. (#563 )
* lazily create msg_index.
* update test.
* fix binary reduce following new minigun template
* enable both int64 and int32 kernels
* [BUGFIX] fix bugs for running GCN on giant graphs. (#561 )
* load mxnet csr.
* enable load large csr.
* fix
* fix.
* fix int overflow.
* fix test.
* new kernel interface done for CPU
* docstring
* rename & docstring
* copy reduce and backward
* [BugFix] Fix error when bfs_level = 0 in Entity Classification with RGCN (#559 )
* [DEMO] Update demo of distributed sampler (#564 )
* update
* update
* update demo
* adapt cuda kernels to the new interface
* add network cpp test (#565 )
* fix bug
* Add unittest for C++ RPC (#566 )
* [CI] Fix CI for cpp test (#570 )
* fix CI for cpp test
* update port number
* [Docker] update docker image (#575 )
* update docker image
* specify lint version
* rm torch import from unified tests
* remove pytorch-specific test_function
* fix unittest
* fix
* fix unittest backend bug in converting tensor to numpy array
* fix
* mxnet version
* [BUGFIX] fix for MXNet 1.5. (#552 )
* remove clone.
* turn on numpy compatible.
* Revert "remove clone."
This reverts commit 17bbf76ed72ff178df6b3f35addc428048672457.
* revert format changes
* fix mxnet api name
* revert mistakes in previous revert
* roll back CI to 20190523 build
* fix unittest
* disable test_shared_mem_store.py for now
* remove mxnet/test_specialization.py
* sync win64 test script
* fix lowercase
* missing backend in gpu unit test
* transpose to get forward graph
* pass update all
* add sanity check
* passing test_specialization.py
* fix and pass test_function
* fix check
* fix pytorch softmax
* mxnet kernels
* c++ lint
* pylint
* try
* win build
* fix
* win
* ci enable gpu build
* init submodule recursively
* backend docstring
* try
* test win dev
* doc string
* disable pytorch test_nn
* try to fix windows issue
* bug fixed, revert changes
* [Test] fix CI. (#586 )
* disable unit test in mxnet tutorial.
* retry socket connection.
* roll back to set_np_compat
* try to fix multi-processing test hangs when it fails.
* fix test.
* fix.
* doc string
* doc string and clean up
* missing field in ctypes
* fix node flow schedule and unit test
* rename
* pylint
* copy from parent default context
* fix unit test script
* fix
* demo bug in nodeflow gpu test
* [Kernel][Bugfix] fix nodeflow bug (#604 )
* fix nodeflow bug
* remove debug code
* add build gtest option
* fix cmake; fix graph index bug in spmv.py
* remove clone
* fix div rhs grad bug
* [Kernel] Support full builtin method, edge softmax and unit tests (#605 )
* add full builtin support
* unit test
* unit test backend
* edge softmax
* apply edge with builtin
* fix kernel unit test
* disable mxnet test_shared_mem_store
* gen builtin reduce
* enable mxnet gpu unittest
* revert some changes
* docstring
* add note for the hack
* [Kernel][Unittest][CI] Fix MXNet GPU CI (#607 )
* update docker image for MXNet GPU CI
* force all dgl graph input and output on CPU
* fix gpu unittest
* speedup compilation
* add some comments
* lint
* add more comments
* fix as requested
* add some comments
* comment
* lint
* lint
* update pylint
* fix as requested
* lint
* lint
* lint
* docstrings of python DGL kernel entries
* disable lint warnings on arguments in kernel.py
* fix docstring in scheduler
* fix some bug in unittest; try again
* Revert "Merge branch 'kernel' of github.com:zzhang-cn/dgl into kernel"
This reverts commit 1d2299e68b004182ea6130b088de1f1122b18a49, reversing
changes made to ddc97fbf1bec2b7815c0da7c74f7ecb2f428889b.
* Revert "fix some bug in unittest; try again"
This reverts commit ddc97fbf1bec2b7815c0da7c74f7ecb2f428889b.
* more comprehensive kernel test
* remove shape check in test_specialization
2019-06-06 15:47:55 -04:00
6f603bbf8f
[BugFix] Fix performance bug in EdgeSoftmax ( #452 )
...
* fix performance bug in EdgeSoftmax
* minor
2019-03-18 16:22:38 -04:00
fe44ffe5dc
[Doc] fix equation in nn.conv ( #425 )
2019-03-01 15:56:08 -05:00
565f0c88fc
[WIP] [NN] Refactor NN package ( #406 )
...
* refactor graph conv
* docs & tests
* fix lint
* fix lint
* fix lint
* fix lint script
* fix lint
* Update
* Style fix
* Fix style
* Fix style
* Fix gpu case
* Fix for gpu case
* Hotfix edgesoftmax docs
* Handle repeated features
* Add docstring
* Set default arguments
* Remove dropout from nn.conv
* Fix
* add util fn for renaming
* revert gcn_spmv.py
* mx folder
* fix wierd bug
* fix mx
* fix lint
2019-02-25 18:41:21 -05:00
2758c24955
[NN] Fix GCN module ( #99 )
...
1. Update `examples/pytorch/gcn` and `python/dgl/nn/pytorch` based on the latest APIs
2. Add full support for dropout in `examples/pytorch/gcn` and `python/dgl/nn/pytorch`
3. Rename `GCN` class in `python/dgl/nn/pytorch` to be `GraphConvolutionLayer` class
4. Make node field an argument that can be configured by users in GraphConvolutionLayer
Note that adjacency normalization has not been supported yet in the examples.
2018-10-28 04:35:33 +08:00
5567f4a4d9
[BACKEND] Add MXNet backend. ( #77 )
...
* support mxnet.
* add mxnet version of GCN.
* rename mxnet.nd as F.
* add mxnet GAT.
* enable GPU for GCN.
* fix MXNet GCN train.
* Use adam to optimize GAT
* support more operators.
* support sparse arrays.
* update mxnet backend.
* support index_copy.
* remove NN.
* update mxnet backend.
* temp check in.
* fix data conversion.
* add test.
* clean up mxnet backend.
* update mxnet examples.
* Revert "remove NN."
This reverts commit d815d9a0ec619f9ce9099c48cd35db9d8e947483.
* temp disable MXNet version of NN.
2018-10-14 11:15:48 -04:00
b24daa6607
change to rel import within dgl
2018-09-16 16:14:37 -04:00
61fa3c6cf5
Builtin function and API changes ( #53 )
...
* WIP: API renaming
* API rewrite and node function refactor
* builtin functions
* builtin functions tested
* fix test
* send and recv spmv test
* WIP: fix examples
* Fix examples using new APIs
2018-09-01 13:38:01 -04:00
96179b0c96
Deep Generative Models of Graphs ( #14 )
...
* model code for generative graphs
* batched version for dynamic graph generation using padding
* renaming function train back to forward
* remove old util function for padding DGMG
* override networkx clear to reset state, add dgl.nn
* Dynamic graph without batching
* use relative import path
* load dataset, pad batch
* bug fix
* experimental batch and unbatch
* dgmg batched version
* minor tweak
* move preprocessing padding into data loading
* batch graph test code
* minor
* batched graph class and test cases
* make dgl.nn.gcn a simple layer plus minor fix
* update dgmg model
* test forward using attribute field
* use frame append, minor changes
* moving networkx operations out of forward
* revert some changes
* remove structural immutability check
2018-08-16 14:05:50 -04:00
xiang song(charlie.song)