885be1784b
[Example][Refactor] Refactor GCN example ( #4160 )
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* Refactor GCN example
* Refactor GCN based on graphsage
* Readme update
* Minor update
* update
* Remove user-defined GCN implementation
* README update
* Update
* Update CONTRIBUTORS.md
* update task_example_test
Co-authored-by: Xin Yao <xiny@nvidia.com >
2022-07-05 15:58:31 +08:00
09ec6020ac
[Example] rm gcn spmv ( #2044 )
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* rm gcn spmv
* remove useless test
* remove useless test
Co-authored-by: Ubuntu <ubuntu@ip-172-31-51-214.ec2.internal >
2020-08-18 17:48:38 +08:00
f99725adbc
all demo use python-3 ( #555 )
2019-05-23 10:38:05 +08:00
4ea42e3e08
fix gcn. ( #469 )
2019-04-05 10:56:09 -07:00
565f0c88fc
[WIP] [NN] Refactor NN package ( #406 )
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* refactor graph conv
* docs & tests
* fix lint
* fix lint
* fix lint
* fix lint script
* fix lint
* Update
* Style fix
* Fix style
* Fix style
* Fix gpu case
* Fix for gpu case
* Hotfix edgesoftmax docs
* Handle repeated features
* Add docstring
* Set default arguments
* Remove dropout from nn.conv
* Fix
* add util fn for renaming
* revert gcn_spmv.py
* mx folder
* fix wierd bug
* fix mx
* fix lint
2019-02-25 18:41:21 -05:00
6c3dba867a
[Tutorial] Update prerequisites of README ( #380 )
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* Update prerequisites of README
* dependencies for pytorch models
* dependencies for mxnet models
* minor
2019-02-11 22:58:17 -05:00
ddc2faa547
[Bugfix] Fix gat residual bug ( #355 )
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* fix gat residual bug
* fix the residual addition; output heads; add some shape notations;
* minor
* fix the output head average
* add requests package in requirement
2019-01-12 08:37:01 -05:00
e557ed89ff
[Doc][Model] example folder doc and model summary ( #259 )
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* update example readme
* mx example readme
* add results in readme
* mx rgcn readme
2018-12-05 14:35:14 -05:00
78269cedfd
[Doc] Update GCN README.md ( #224 )
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* update readme.
* update readme
2018-12-04 12:07:05 -05:00
2758c24955
[NN] Fix GCN module ( #99 )
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1. Update `examples/pytorch/gcn` and `python/dgl/nn/pytorch` based on the latest APIs
2. Add full support for dropout in `examples/pytorch/gcn` and `python/dgl/nn/pytorch`
3. Rename `GCN` class in `python/dgl/nn/pytorch` to be `GraphConvolutionLayer` class
4. Make node field an argument that can be configured by users in GraphConvolutionLayer
Note that adjacency normalization has not been supported yet in the examples.
2018-10-28 04:35:33 +08:00
fde4f581d2
gcn runnable
2018-10-03 21:05:19 -04:00
0a78dbe12a
Three DGL-GCN implementations ( #35 )
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* synthetic dataset
* some fix
* gcn readme
2018-08-07 15:26:58 -04:00
Chang Liu