* add hilander model implementation draft
* use focal loss
* fix
* change data root
* add necessary scripts
* update download links
* update
* update example table
* fix
* update readme with numbers
* add empty folder
* only eval at the end
* set up hilander
* inform results may fluctuate
* address comments
Co-authored-by: sneakerkg <xiaotj1990327@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-212.us-east-2.compute.internal>
* csr and csc creation
* fix
* fix
* fixes to adj transpose
* fine
* raise error if indptr did not match number of nodes
* fix
* huh?
* oh
Co-authored-by: Minjie Wang <wmjlyjemaine@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>
* Make multigpu graphsage use whole datset
* Specify queeze dimension
* Remove squeeze dimension
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* graphsaint
* graphsaint
* graphsaint
* graphsaint
* fixed the model
* fixed some bugs
* fixed the computing of normalization and updated the results
* fixed some bugs and updated the results
* Update utils.py
* Update train_sampling.py
* Update train_sampling.py
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* Update README.md
Add description of RECT
* [Example] Add implementation of RECT
[Example] Add implementation of RECT
* Update classify.py
Modify the class names and the function names mentioned above
* Update main.py
Modify the function names mentioned above
* Update label_utils.py
Adjust the comments
* Update README.md
Add the github information
Co-authored-by: Tianjun Xiao <xiaotj1990327@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>
* multi gpus training for mag240m
* remove unused function
* small changes
* more fix
* use multi gpus to eval and more fix
Co-authored-by: Quan Gan <coin2028@hotmail.com>
* Add hgat example
* Add experiment
* Clean code
* clear the code
* Add index in README
* Add index in README
* Add index in README
* Add index in README
* Add index in README
* Add index in README
* Change the code title and folder name
* Ready to merge
* Prepare for rebase and change message passing function
* use git ignore to handle empty file
* change file permission to resolve empty file
* Change permission
* change file mode
* Finish Coding
* working code cpu
* pyg compare
* Accelerate with batching
* FastMode Enabled
* update readme
* Update README.md
* refractor code
* add graphsim code
* modified code
* few fix
* Modified graphsim
* Simple Model Added
* Clean up code
* Refractor the code for Merge
* Bugfix enable gradient when train
* update readme and format
Co-authored-by: Chen <chesirui@3c22fbe5458c.ant.amazon.com>
Co-authored-by: Tianjun Xiao <xiaotj1990327@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-4-63.ap-northeast-1.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-45-47.ap-northeast-1.compute.internal>
* Typo in command example.
process_nowplaying_rs.py is the right name under this folder.
* Update README.md
* Update README.md
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Hengrui Zhang