* add unit test
* Extend NDArrayPartition object
* Add method for setting embedding, and improve documentation
* Sync before returning
* Use name unique to sparse embedding class to avoid delete
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
* [Feature] add positive negative statistics
* [Feature] add permission information and fix import problem
* fix backend incompatible problem
* modify random split to remove sklearn usage
* modify file read to remove pandas usage
* add datasets into doc
* add random seed in data splitting
* add dataset unit test
* usage permission information update
Co-authored-by: zhjwy9343 <6593865@qq.com>
* add bruteforce impl
* add nn descent implementation
* change doc-string
* remove redundant func
* use local rng for cuda
* fix lint
* fix lint
* fix bug
* fix bug
* wrap nndescent_knn_graph into knn
* fix lint
* change function names
* add comment for dist funcs
* let the compiler do the unrolling
* use better blocksize setting
* remove redundant line
* check the return of the cub calls
Co-authored-by: Tong He <hetong007@gmail.com>
* add output device for dataloading
* Update dataloader
* Get sampler device from dataloader
* Fix line length
* Update examples
* Fix to_block GPU for empty relation types
* Handle the case where the DistGraph has None for the underlying graph
Co-authored-by: Da Zheng <zhengda1936@gmail.com>
* Split from NCCL PR
* Fix type in comment
* Expand documentation for sparse_all_to_all_push
* Restore previous behavior in example
* Re-work optimizer to use NCCL based on gradient location
* Allow for running with embedding on CPU but using NCCL for gradient exchange
* Optimize single partition case
* Fix pylint errors
* Add missing include
* fix gradient indexing
* Fix line continuation
* Migrate 'first_step'
* Skip tests without enough GPUs to run NCCL
* Improve empty tensor handling for pytorch 1.5
* Fix indentation
* Allow multiple NCCL communicator to coexist
* Improve handling of empty message
* Update python/dgl/nn/pytorch/sparse_emb.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
* Update python/dgl/nn/pytorch/sparse_emb.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
* Keepy empty tensor dimensionaless
* th.empty -> th.tensor
* Preserve shape for empty non-zero dimension tensors
* Use shared state, when embedding is shared
* Add support for gathering an embedding
* Fix typo
* Fix more typos
* Fix backend call
* Use NodeDataLoader to take advantage of ddp
* Update training script to share memory
* Only squeeze last dimension
* Better handle empty message
* Keep embedding on the target device GPU if dgl_sparse if false in RGCN example
* Fix typo in comment
* Add asserts
* Improve documentation in example
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
* add two fraud dataset
* add comments and modify to heterogenous graph
* modify the node name based on datasets
* add assertion message
Co-authored-by: zhjwy9343 <6593865@qq.com>
* Split NCCL wrapper from sparse optimizer and sparse embedding
* Add more unit tests for single node nccl
* Fix unit test for tf
* Switch to device histogram
* Fix histgram issues
* Finish migration to histogram
* Handle cases with zero send/recieve data
* Start on partition object
* Get compiling
* Updates
* Add unit tests
* Switch to partition object
* Fix linting issues
* Rename partition file
* Add python doc
* Fix python assert and finish doxygen comments
* Remove stubs for range based partition to satisfy pylint
* Wrap unit test in GPU only
* Wrap explicit cuda call in ifdef
* Merge with partition.py
* update docstrings
* Cleanup partition_op
* Add Workspace object
* Switch to using workspace object
* Move last remainder based function out of nccl_api
* Add error messages
* Update docs with examples
* Fix linting erros
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
* add bruteforce impl
* add support for bruteforce-sharemem
* modify python API
* add tests
* change file path
* change python API
* fix lint
* fix test
* also check worst_dist in the last few dim
* use heap and early-stop on CPU
* fix lint
* fix lint
* add device check
* use cuda function to determine max shared mem
* use cuda to determine block info
* add memory free for tmp var
* update doc-string and add dist option
* fix lint
* add more tests
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
* test commit
* fixes
* oops
* add docs
* lint
* why does it say I have a trailing whitespace
* oh ok
* fixes
* why there's an invalid argument error
* address comments
* fix
* address comments
* Auto stash before rebase of "origin/pytorch-nn-working"
GCNII model added
* linting
* linting
* lint
* Frequency Adaptive gcn init comit
* Revert "Frequency Adaptive gcn init comit"
This reverts commit 86a80586ac0040497c1edfa0e80df719992dcc4a.
* Update python/dgl/nn/pytorch/conv/gcn2conv.py
modified docstring
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* added beta formula and changed param name
* fix docstring
* lint
* white space lint
* update docstring
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* docstring formula update
* added gcn2
* added GCN2Conv
* Update nn.pytorch.rst
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* add implementation of twirls
* format the code
* fix some format error, and ignore others
* fix format errors
* fix format errors
* expose unfolding & attention
* Update nn.pytorch.rst
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* adapt send_and_recv example
* lint fix
* Change title and example order
* Update heterograph.py
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
nv-dlasalle