* Add failing unit test
* Fix negative sampler edge types
* fix test
* oops
* revert
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
* fix uva sampling with features
* fix
* add is_listlike function to distinguish strings from sequence
* fix
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
* 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>
Make the default value of parameter replace in docstring consistent with code
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
* [Feature] enable async transfer in NodeDataLoader for homograph
* fix lint issues
* fix device choose when creating stream
* fix test on cpu only machine
* fix pin_memory config
* support homo only
* avoid creating stream in each step and sync via event
* fix lint
* enable graph copy on non-default stream
* fix lint
* refine arg description
* fix conflicts
* gpu compact graph template
* cuda compact graph draft
* fix typo
* compact graphs
* pass unit test but fail in training
* example using EdgeDataLoader on the GPU
* refactor cuda_compact_graph and cuda_to_block
* update training scripts
* fix linting
* fix linting
* fix exclude_edges for the GPU
* add --data-cpu & fix copyright
* [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>
* 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>
* 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>
* Start on uniform GPU sampling
* Save more work
* Get cu file compiling
* Update sampling
* More changes
* Get GPU sampling for uniform probabilities solved
* Fix batch tensor migration
* Fix
* update kernels
* expand blocking
* Undo testing change
* Cut down on sampling overhead
* Fix replacement
* Update unit tests
* Add option to gpu sample in graphsage
* Copy only csc to gpu
* Add ogbn support
* Fix linting
* Remove nvtx from sample
* Improve documentation and error checking
* Expand documentation
* Update assert checking
* delete extra space
* Use standard dataloader when dataset is a dictionary
* ogb -> ogbn
* Fix edge selection determinism
* Fix typos
* Remove nvtx
* Add comment for self.fanout_arrays and assert
* Fix linting
* Migrate to scalarbatcher
* Fix indentation
* Fix batcher
* Fix indexing
* Only use databatcher for GPU
* Convert to DGL NDArray to PyTorch Tensor
* Add optimization for PyTorch's F.tensor() for list of GPU tensors
Co-authored-by: Da Zheng <zhengda1936@gmail.com>
Sai Kandregula