dmlc--dgl
xiang song(charlie.song)
e17add5602
* 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
35 行
615 B
ReStructuredText
35 行
615 B
ReStructuredText
.. _apinn-mxnet:
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dgl.nn.mxnet
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============
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dgl.nn.mxnet.conv
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-----------------
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.. automodule:: dgl.nn.mxnet.conv
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.. autoclass:: dgl.nn.mxnet.conv.GraphConv
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:members: weight, bias, forward
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:show-inheritance:
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.. autoclass:: dgl.nn.mxnet.conv.RelGraphConv
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:members: forward
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:show-inheritance:
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.. autoclass:: dgl.nn.mxnet.conv.TAGConv
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:members: forward
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:show-inheritance:
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dgl.nn.mxnet.glob
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-----------------
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.. automodule:: dgl.nn.mxnet.glob
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:members:
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:show-inheritance:
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dgl.nn.mxnet.softmax
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--------------------
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.. automodule:: dgl.nn.mxnet.softmax
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:members: edge_softmax
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