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  1. 07 Oct, 2021 1 commit
    • K's avatar
      [Model] Refine GraphSAINT (#3328) · aef96dfa
      K authored 
      

* The start of experiments of Jiahang Li on GraphSAINT.

* a nightly build

* a nightly build

Check the basic pipeline of codes. Next to check the details of samplers , GCN layer (forward propagation) and loss (backward propagation)

* a night build

* Implement GraphSAINT with torch.dataloader

There're still some bugs with sampling in training procedure

* Test validity

Succeed in testing validity on ppi_node experiments without testing other setup.
1. Online sampling on ppi_node experiments performs perfectly.
2. Sampling speed is a bit slow because the operations on [dgl.subgraphs], next step is to improve this part by putting the conversion into parallelism
3. Figuring out why offline+online sampling method performs bad, which does not make sense
4. Doing experiments on other setup

* Implement saint with torch.dataloader

Use torch.dataloader to speed up saint sampling with experiments. Except experiments on too large dataset Amazon, we've done some experiments on other four datasets including ppi, flickr, reddit and yelp. Preliminary experimental results show consumed time and metrics reach not bad level. Next step is to employ more accurate profiler which is the line_profiler to test consumed period, and adjust num_workers to speed up sampling procedures on same certain datasets faster.

* a nightly build

* Update .gitignore

* reorganize codes

Reorganize some codes and comments.

* a nightly build

* Update .gitignore

* fix bugs

Fix bugs about why fully offline sampling and author's version don't work

* reorganize files and codes

Reorganize files and codes then do some experiments to test the performance of offline sampling and online sampling

* do some experiments and update README

* a nightly build

* a nightly build

* Update README.md

* delete unnecessary files

* Update README.md

* a nightly update

1. handle directory named 'graphsaintdata'
2. control graph shift between gpu and cpu related to large dataset ('amazon')
3. remove parameter 'train'
4. refine annotations of the sampler
5. update README.md including updating dataset info, dependencies info, etc

* a nightly update

explain config differences in TEST part
remove a sampling time variant
make 'online' an argument
change 'norm' to 'sampler'
explain parameters in README.md

* Update README.md

* a nightly build

* make online an argument
* refine README.md
* refine codes of `collate_fn` in sampler.py, in training phase only return one subgraph, no need to check if the number of subgraphs larger than 1

* Update sampler.py

check the problem on flickr is about overfitting.

* a nightly update

Fix the overfitting problem of `flickr` dataset. We need to restrict the number of subgraphs (also the number of iterations) used in each epoch of training phase. Or it might overfit when validating at the end of each epoch. The method to limit the number is a formula specified by the author.

* Set up a new flag `full` specifying if the number of subgraphs used in training phase equals to that of pre-sampled subgraphs

* Modify codes and annotations related the new flag

* Add a new parameter called `node_budget` in the base class `SAINTSampler` to compute the specific formula

* set `gpu` as a command line argument

* Update README.md

* Finish the experiments on Flickr, which is done after adding new flag `full`

* a nightly update

* use half of edges in the original graph to do sampling
* test dgl.random.choice with or without replacement with half of edges
~ next is to test what if put the calculating probability part out of __getitem__ can speed up sampling and try to implement sampling method of author

* employ cython to implement edge sampling for per edge

* employ cython to implement edge sampling for per edge
* doing experiments to test consumed time and performance
** the consumed time decreased to approximately 480s, the performance decrease about 5 points.
* deprecate cython implementation

* Revert "employ cython to implement edge sampling for per edge"

* This reverts commit 4ba4f092
* Deprecate cython implementation
* Reserve half-edges mechanism

* a nightly update

* delete unnecessary annotations
Co-authored-by: default avatarMufei Li <mufeili1996@gmail.com>
      aef96dfa
  3. 23 Sep, 2021 1 commit
  5. 21 Sep, 2021 1 commit
  7. 20 Sep, 2021 1 commit
  9. 13 Sep, 2021 2 commits
  11. 02 Sep, 2021 1 commit
  13. 27 Aug, 2021 1 commit
    • esang's avatar
      [Model] Point transformer (#3284) · 4fb50be4
      esang authored 
      

* some modifications for pointnet2

* temporarily save changes

* move files to new directory point_transformer

* implement point transformer for classification

* restore train_cls in pointnet

* implement point transformer for partseg

* fix point transformer for nan loss

* modify point transformer for cls

* modify training setting

* update transformer for cls

* update code

* update code for latest performance

* update the example index

* some minor changes
Co-authored-by: default avatarTong He <hetong007@gmail.com>
      4fb50be4
  15. 23 Aug, 2021 1 commit
  17. 20 Aug, 2021 1 commit
  19. 19 Aug, 2021 1 commit
  21. 16 Aug, 2021 1 commit
  23. 11 Aug, 2021 1 commit
    • JOHNW02's avatar
      [example] Create EEG-GCNN example. (#3186) · 738b75f4
      JOHNW02 authored 
      * Create EEG-GCNN example.

* Update README.md

* Remove gitignore file.

* Update README.md

* change 'datas' to 'datasets'.

* Change train.py to main.py

* Added an entry in the indexing page.

* State "simplified version"; change how to run.

* Fix bug in contact

* Remove paper link in reference.

* Create working branch

* Add normalization of x.

* Update paper link and tags

* Update paper link in readme

* Update readme; add patient level indices

* Update readme. Add comments to models

* Update README.md

* change to with; specify location for ch and el; move note

* fix bug for note

* Add args for models; clean code.

* delete = in readme

* Add reference for spec_coh_values
      738b75f4
  25. 02 Aug, 2021 1 commit
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