dgl/docs/source/api/python at e17add560279b87bc5c5cd49679dbdd854cbfc0f - dgl

mirror of https://github.com/dmlc/dgl.git synced 2026-06-05 19:54:25 +08:00

Files

xiang song(charlie.song) e17add5602 [NN] Add MXNet impl for TAGCN module. (#799 )

* upd

* fig edgebatch edges

* add test

* trigger

* Update README.md for pytorch PinSage example.

Add noting that the PinSage model example under
example/pytorch/recommendation only work with Python 3.6+
as its dataset loader depends on stanfordnlp package
which work only with Python 3.6+.

* Provid a frame agnostic API to test nn modules on both CPU and CUDA side.

1. make dgl.nn.xxx frame agnostic
2. make test.backend include dgl.nn modules
3. modify test_edge_softmax of test/mxnet/test_nn.py and
    test/pytorch/test_nn.py work on both CPU and GPU

* Fix style

* Delete unused code

* Make agnostic test only related to tests/backend

1. clear all agnostic related code in dgl.nn
2. make test_graph_conv agnostic to cpu/gpu

* Fix code style

* fix

* doc

* Make all test code under tests.mxnet/pytorch.test_nn.py
work on both CPU and GPU.

* Fix syntex

* Remove rand

* Add TAGCN nn.module and example

* Now tagcn can run on CPU.

* Add unitest for TGConv

* Fix style

* For pubmed dataset, using --lr=0.005 can achieve better acc

* Fix style

* Fix some descriptions

* trigger

* Fix doc

* Add nn.TGConv and example

* Fix bug

* Update data in mxnet.tagcn test acc.

* Fix some comments and code

* delete useless code

* Fix namming

* Fix bug

* Fix bug

* Add test code for mxnet TAGCov

* Update some docs

* Fix some code

* Update docs dgl.nn.mxnet

* Update weight init

* Fix

2019-08-28 13:19:17 +08:00

batch.rst

[Feature] DGL Pooling modules (#669 )

2019-08-06 01:43:25 +08:00

data.rst

[Model] Add GIN Model (#471 )

2019-04-17 14:57:07 +08:00

function.rst

[NN] Add commonly used GNN models from examples to dgl.nn modules. (#748 )

2019-08-27 18:21:19 +08:00

graph_store.rst

[Doc] fix some document warnings (#645 )