* huuuuge update
* remove
* lint
* lint
* fix
* what happened to nccl
* update multi-gpu unsupervised graphsage example
* replace most of the dgl.mp.process with torch.mp.spawn
* update if condition for use_uva case
* update user guide
* address comments
* incorporating suggestions from @jermainewang
* oops
* fix tutorial to pass CI
* oops
* fix again
Co-authored-by: Xin Yao <xiny@nvidia.com>
* implement pin_memory/unpin_memory/is_pinned for dgl.graph
* update python docstring
* update c++ docstring
* add test
* fix the broken UnifiedTensor
* XPU_SWITCH for kDLCPUPinned
* a rough version ready for testing
* eliminate extra context parameter for pin/unpin
* update train_sampling
* fix linting
* fix typo
* multi-gpu uva sampling case
* disable new format materialization for pinned graphs
* update python doc for pin_memory_
* fix unit test
* UVA sampling for link prediction
* dispatch most csr ops
* update graphsage example to combine uva sampling and UnifiedTensor
* update graphsage example to combine uva sampling and UnifiedTensor
* update graphsage example to combine uva sampling and UnifiedTensor
* update doc
* update examples
* change unitgraph and heterograph's PinMemory to in-place
* update examples for multi-gpu uva sampling
* update doc
* fix linting
* fix cpu build
* fix is_pinned for DistGraph
* fix is_pinned for DistGraph
* update graphsage unsupervised example
* update doc for gpu sampling
* update some check for sampling device switching
* fix linting
* adapt for new dataloader
* fix linting
* fix
* fix some name issue
* adjust device check
* add unit test for uva sampling & fix some zero_copy bug
* fix linting
* update num_threads in graphsage examples
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
* implement pin_memory/unpin_memory/is_pinned for dgl.graph
* update python docstring
* update c++ docstring
* add test
* fix the broken UnifiedTensor
* eliminate extra context parameter for pin/unpin
* fix linting
* fix typo
* disable new format materialization for pinned graphs
* update python doc for pin_memory_
* fix unit test
* update doc
* change unitgraph and heterograph's PinMemory to in-place
* update comments for NDArray's PinMemory_ and PinData
* update doc
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
* Pass the std:min argument's type, to avoid the compilation error.
* Update parallel_for.h
* Update negative_sampling.cc
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* [Feature] enable create/set/free cuda stream for internal use
* add unit test
* fix unit test failure on mxnet and tf
* refactor stream wrapper
* fix lint error
* fix lint error
* [Feature] Exclude edges in sample_neighbors
Extending sample_neighbors and sample_frontier
API to support exclude_edges parameter.
exclude_edges support tensor and dict data
Feature enable excluding certain edges
during neighborhood sampling
Exclude_edges contains EID's of edges
which will be excluded
during neighbor picking for seed nodes.
Added test case for heterograph and homograph
RFC issue id: 2944
* compatibility
* fix
* fix
Co-authored-by: Quan Gan <coin2028@hotmail.com>
* [CPU, Parallel] Rewriting omp pragmas with parallel_for
* [CPU, Parallel] Decrease number of calls to task function
* c[CPU, Parallel] Modify calls to new interface of parallel_for
* fix.
* fix.
* fix.
* fix.
* Fix test
* Deprecate old DistEmbedding impl, use synchronized embedding impl
* Basic imple of heterogeneous on homogenenous sampling
* make pass
* Pass C++ test
* Add python test code
* lint
* lint
* Add MultiLayerEtypeNeighborSampler
* Add unitest for single machine dataloader
* Add dist dataloader test for edge type sampler
* Fix lint
* fix
* support for per etype sample
* Fix some bug and enable distributed training with per edge sample
* fix
* Now distributed training works
* turn off some mxnet
* turn off mxnet for some dist test
* fix
* upd
* upd according to the comments
* Fix
* Fix test and now distributed works.
* upd
* upd
* Fix
* Fix bug
* remove dead code.
* upd
* Fix
* upd
* Fix
Co-authored-by: Ubuntu <ubuntu@ip-172-31-71-112.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-66.ec2.internal>
Co-authored-by: Da Zheng <zhengda1936@gmail.com>
* [CPU Parallel] implementation of parallel_for with grain size
* Create parallel_for.h
* Update parallel_for.h
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* Add row/col sorted flags
* improve sorting paths
* Remove print statement
* Keep track of sorted matrices
* Remove sort check in to_block
* Improve CPU sorted COO->CSR
* Handle the zero edge case
* Remove omp default clause to work with MSVC
* Update comments on sorted COO->CSR cpu implementatoin
* Expose sorted to python interface
* Make check_sorted default to false for dgl.graph()
* remove check sorted; add utests
* remove check_sorted flag
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
* Remove double-checking sorted
* Remove sorting of CSR by default
* Update unit test to use unsorted matix
* delete whitespace
* Expand unit tests
* Replace cusparse sort
* Fix row column sorting
* Explicitly don't sort columns
* Fix linting errors
* Fix bit-width calculation
* Fix sorting assertion and unit test
* Fix linting
* Improve CPU COO2CSR
* Remove references
* Rename and add documentation to edge encoding/decoding funcionts
* Fix sorting keys as 64 bit
* Revert cosmetic changes to unit tests
* Update documentation
* Update complexity documentation for coo to csr conversion
* Remove COOIsSorted check in CPU implementation too
* first commit
* some thoughts
* move around
* more commit
* more fixes
* now it uses torch allocator
* fix symbol export error
* fix
* fixes
* test fix
* add script
* building separate library per version
* fix for vs2019
* more fixes
* fix on windows build
* update jenkinsfile
* auto copy built dlls for windows
* lint and installation guide update
* fix
* specify conda environment
* set environment for ci
* fix
* fix
* fix
* fix again
* revert
* fix cmake
* fix
* switch to using python interpreter path
* remove scripts
* debug
* oops sorry
* Update index.rst
* Update index.rst
* copies automatically, no need for this
* do not print message if library not found
* tiny fixes
* debug on nightly
* replace add_compile_definitions to make CMake 3.5 happy
* fix linking to wrong lib for multiple pytorch envs
* changed building strategy
* fix nightly
* fix windows
* fix windows again
* setup bugfix
* address comments
* change README
* Add async transferer class
* Add async ndarray copy interface
* Add python bindings
* Fix comment
* Add python class
* Fix linting issues
* Add python unit test
* Update python interface
* move async_transferer to cuda only directory
* Fix linting issue
* Move out of contrib
* Add doc strings
* Move test compute from backend
* Update comment
* Fix test naming
* Fix argument usage
* Wrap/unwrap backend parameters
* Move to dataloading
* Move to 'dataloading'
* Make GPU/CPU compatible
* Fix unit tests
* Add docs
* Use only backend interface for datamovement in unit test
Quan Gan