Unverified Commit 6d9433b0 authored by Mufei Li's avatar Mufei Li Committed by GitHub
Browse files

[Transform] [Doc] Rename transform to transforms and update doc (#3765)

* Update

* Update

* Update

* Fix

* Update

* Update

* Update

* Fix
parent ccaa0bf2
......@@ -97,7 +97,7 @@ def main():
print('partition graph...')
part_dict = dgl.transform.metis_partition(g, num_parts, 1)
part_dict = dgl.transforms.metis_partition(g, num_parts, 1)
tot_num_inner_edges = 0
for part_id in part_dict:
......
......@@ -15,11 +15,11 @@ def track_time(graph_name, k):
data = utils.process_data(graph_name)
graph = data[0]
# dry run
gg = dgl.transform.metis_partition(graph, k)
gg = dgl.transforms.metis_partition(graph, k)
# timing
with utils.Timer() as t:
for i in range(3):
gg = dgl.transform.metis_partition(graph, k)
gg = dgl.transforms.metis_partition(graph, k)
return t.elapsed_secs / 3
return t.elapsed_secs / 3
.wy-table-responsive table td,
.wy-table-responsive table th {
white-space: normal;
}
.wy-table-bordered-all,
.rst-content table.docutils {
border: none;
}
.wy-table-bordered-all td,
.rst-content table.docutils td {
border: none;
}
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padding: 14px;
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\ No newline at end of file
.. role:: hidden
:class: hidden-section
.. currentmodule:: {{ module }}
{{ name | underline}}
.. autoclass:: {{ name }}
:show-inheritance:
:members: __getitem__, __len__, collate_fn, forward, reset_parameters, rel_emb, rel_project, explain_node, explain_graph
......@@ -6,252 +6,104 @@ dgl.data
.. currentmodule:: dgl.data
.. automodule:: dgl.data
Quick links:
* `Node Prediction Datasets`_
* `Edge Prediction Datasets`_
* `Graph Prediction Datasets`_
Base Dataset Class
---------------------------
.. autoclass:: DGLDataset
:members: download, save, load, process, has_cache, __getitem__, __len__
Base Class
---------------------------------------
CSV Dataset Class
-----------------
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
.. autoclass:: CSVDataset
DGLDataset
CSVDataset
Node Prediction Datasets
---------------------------------------
DGL hosted datasets for node classification/regression tasks.
.. _sstdata:
Stanford sentiment treebank dataset
```````````````````````````````````
.. autoclass:: SSTDataset
:members: __getitem__, __len__
.. _karateclubdata:
Karate club dataset
```````````````````````````````````
.. autoclass:: KarateClubDataset
:members: __getitem__, __len__
.. _citationdata:
Citation network dataset
```````````````````````````````````
.. autoclass:: CoraGraphDataset
:members: __getitem__, __len__
.. autoclass:: CiteseerGraphDataset
:members: __getitem__, __len__
.. autoclass:: PubmedGraphDataset
:members: __getitem__, __len__
.. _corafulldata:
CoraFull dataset
```````````````````````````````````
.. autoclass:: CoraFullDataset
:members: __getitem__, __len__
.. _rdfdata:
RDF datasets
```````````````````````````````````
.. autoclass:: AIFBDataset
:members: __getitem__, __len__
.. autoclass:: MUTAGDataset
:members: __getitem__, __len__
.. autoclass:: BGSDataset
:members: __getitem__, __len__
.. autoclass:: AMDataset
:members: __getitem__, __len__
.. _amazoncobuydata:
Amazon Co-Purchase dataset
```````````````````````````````````
.. autoclass:: AmazonCoBuyComputerDataset
:members: __getitem__, __len__
.. autoclass:: AmazonCoBuyPhotoDataset
:members: __getitem__, __len__
.. _coauthordata:
Coauthor dataset
```````````````````````````````````
.. autoclass:: CoauthorCSDataset
:members: __getitem__, __len__
.. autoclass:: CoauthorPhysicsDataset
:members: __getitem__, __len__
.. _ppidata:
Protein-Protein Interaction dataset
```````````````````````````````````
.. autoclass:: PPIDataset
:members: __getitem__, __len__
.. _redditdata:
Reddit dataset
``````````````
.. autoclass:: RedditDataset
:members: __getitem__, __len__
.. _sbmdata:
Symmetric Stochastic Block Model Mixture dataset
````````````````````````````````````````````````
.. autoclass:: SBMMixtureDataset
:members: __getitem__, __len__, collate_fn
.. _frauddata:
Fraud dataset
``````````````
.. autoclass:: FraudDataset
:members: __getitem__, __len__
.. autoclass:: FraudYelpDataset
:members: __getitem__, __len__
.. autoclass:: FraudAmazonDataset
:members: __getitem__, __len__
Datasets for node classification/regression tasks
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
SSTDataset
KarateClubDataset
CoraGraphDataset
CiteseerGraphDataset
PubmedGraphDataset
CoraFullDataset
AIFBDataset
MUTAGDataset
BGSDataset
AMDataset
AmazonCoBuyComputerDataset
AmazonCoBuyPhotoDataset
CoauthorCSDataset
CoauthorPhysicsDataset
PPIDataset
RedditDataset
SBMMixtureDataset
FraudDataset
FraudYelpDataset
FraudAmazonDataset
Edge Prediction Datasets
---------------------------------------
DGL hosted datasets for edge classification/regression and link prediction tasks.
.. _kgdata:
Knowlege graph dataset
```````````````````````````````````
.. autoclass:: FB15k237Dataset
:members: __getitem__, __len__
.. autoclass:: FB15kDataset
:members: __getitem__, __len__
.. autoclass:: WN18Dataset
:members: __getitem__, __len__
.. _bitcoinotcdata:
Datasets for edge classification/regression and link prediction
BitcoinOTC dataset
```````````````````````````````````
.. autoclass:: BitcoinOTCDataset
:members: __getitem__, __len__
ICEWS18 dataset
```````````````````````````````````
.. autoclass:: ICEWS18Dataset
:members: __getitem__, __len__
GDELT dataset
```````````````````````````````````
.. autoclass:: GDELTDataset
:members: __getitem__, __len__
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
FB15k237Dataset
FB15kDataset
WN18Dataset
BitcoinOTCDataset
ICEWS18Dataset
GDELTDataset
Graph Prediction Datasets
---------------------------------------
DGL hosted datasets for graph classification/regression tasks.
.. _qm7bdata:
QM7b dataset
```````````````````````````````````
.. autoclass:: QM7bDataset
:members: __getitem__, __len__
.. _qm9data:
QM9 dataset
```````````````````````````````````
.. autoclass:: QM9Dataset
:members: __getitem__, __len__
Datasets for graph classification/regression tasks
.. _qm9edgedata:
QM9Edge dataset
```````````````````````````````````
.. autoclass:: QM9EdgeDataset
:members: __getitem__, __len__
.. _minigcdataset:
Mini graph classification dataset
`````````````````````````````````
.. autoclass:: MiniGCDataset
:members: __getitem__, __len__
.. _tudata:
TU dataset
``````````
.. autoclass:: TUDataset
:members: __getitem__, __len__
.. autoclass:: LegacyTUDataset
:members: __getitem__, __len__
.. _gindataset:
Graph isomorphism network dataset
```````````````````````````````````
.. autoclass:: GINDataset
:members: __getitem__, __len__
.. _fakenewsdata:
Fake news dataset
```````````````````````````````````
.. autoclass:: FakeNewsDataset
:members: __getitem__, __len__
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
QM7bDataset
QM9Dataset
QM9EdgeDataset
MiniGCDataset
TUDataset
LegacyTUDataset
GINDataset
FakeNewsDataset
AsNodePredDataset
AsEdgePredDataset
Dataset adapters
-------------------
Node prediction adapter
```````````````````````
.. autoclass:: AsNodePredDataset
:members: __getitem__, __len__
Link prediction adapter
```````````````````````
.. autoclass:: AsLinkPredDataset
:members: __getitem__, __len__
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
AsNodePredDataset
AsLinkPredDataset
Utilities
-----------------
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
utils.get_download_dir
utils.download
......@@ -262,6 +114,4 @@ Utilities
utils.save_info
utils.load_info
utils.add_nodepred_split
.. autoclass:: dgl.data.utils.Subset
:members: __getitem__, __len__
utils.Subset
......@@ -15,4 +15,4 @@ API Reference
dgl.sampling
dgl.contrib.UnifiedTensor
udf
transform
transforms
.. _apinn-mxnet:
NN Modules (MXNet)
===================
Conv Layers
----------------------------------------
.. automodule:: dgl.nn.mxnet.conv
GraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.GraphConv
:members: weight, bias, forward
:show-inheritance:
RelGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.RelGraphConv
:members: forward
:show-inheritance:
TAGConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.TAGConv
:members: forward
:show-inheritance:
GATConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.GATConv
:members: forward
:show-inheritance:
EdgeConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.EdgeConv
:members: forward
:show-inheritance:
SAGEConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.SAGEConv
:members: forward
:show-inheritance:
SGConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.SGConv
:members: forward
:show-inheritance:
APPNPConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.APPNPConv
:members: forward
:show-inheritance:
GINConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.GINConv
:members: forward
:show-inheritance:
GatedGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.GatedGraphConv
:members: forward
:show-inheritance:
GMMConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.GMMConv
:members: forward
:show-inheritance:
ChebConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.ChebConv
:members: forward
:show-inheritance:
AGNNConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.AGNNConv
:members: forward
:show-inheritance:
NNConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.NNConv
:members: forward
:show-inheritance:
Dense Conv Layers
----------------------------------------
DenseGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.DenseGraphConv
:members: forward
:show-inheritance:
DenseSAGEConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.DenseSAGEConv
:members: forward
:show-inheritance:
DenseChebConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.conv.DenseChebConv
:members: forward
:show-inheritance:
Global Pooling Layers
----------------------------------------
.. automodule:: dgl.nn.mxnet.glob
SumPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.glob.SumPooling
:members:
:show-inheritance:
AvgPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.glob.AvgPooling
:members:
:show-inheritance:
MaxPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.glob.MaxPooling
:members:
:show-inheritance:
SortPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.glob.SortPooling
:members:
:show-inheritance:
GlobalAttentionPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.glob.GlobalAttentionPooling
:members:
:show-inheritance:
Set2Set
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.glob.Set2Set
:members:
:show-inheritance:
Heterogeneous Graph Convolution Module
----------------------------------------
HeteroGraphConv
~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.HeteroGraphConv
:members:
:show-inheritance:
Utility Modules
----------------------------------------
Sequential
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.mxnet.utils.Sequential
:members:
:show-inheritance:
.. _apinn-pytorch:
NN Modules (PyTorch)
====================
.. _apinn-pytorch-conv:
Conv Layers
----------------------------------------
.. automodule:: dgl.nn.pytorch.conv
GraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.GraphConv
:members: weight, bias, forward, reset_parameters
:show-inheritance:
EdgeWeightNorm
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.EdgeWeightNorm
:members: forward
:show-inheritance:
RelGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.RelGraphConv
:members: forward
:show-inheritance:
TAGConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.TAGConv
:members: forward
:show-inheritance:
GATConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.GATConv
:members: forward
:show-inheritance:
GATv2Conv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.GATv2Conv
:members: forward
:show-inheritance:
EGATConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.EGATConv
:members: forward
:show-inheritance:
EdgeConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.EdgeConv
:members: forward
:show-inheritance:
SAGEConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.SAGEConv
:members: forward
:show-inheritance:
SGConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.SGConv
:members: forward
:show-inheritance:
APPNPConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.APPNPConv
:members: forward
:show-inheritance:
GINConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.GINConv
:members: forward
:show-inheritance:
GatedGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.GatedGraphConv
:members: forward
:show-inheritance:
GMMConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.GMMConv
:members: forward
:show-inheritance:
ChebConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.ChebConv
:members: forward
:show-inheritance:
AGNNConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.AGNNConv
:members: forward
:show-inheritance:
NNConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.NNConv
:members: forward
:show-inheritance:
AtomicConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.AtomicConv
:members: forward
:show-inheritance:
CFConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.CFConv
:members: forward
:show-inheritance:
DotGatConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.DotGatConv
:members: forward
:show-inheritance:
TWIRLSConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.TWIRLSConv
:members: forward
:show-inheritance:
TWIRLSUnfoldingAndAttention
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.TWIRLSUnfoldingAndAttention
:members: forward
:show-inheritance:
GCN2Conv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.GCN2Conv
:members: forward
:show-inheritance:
.. _apinn-pytorch-dense-conv:
Dense Conv Layers
----------------------------------------
DenseGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.DenseGraphConv
:members: forward
:show-inheritance:
DenseSAGEConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.DenseSAGEConv
:members: forward
:show-inheritance:
DenseChebConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.conv.DenseChebConv
:members: forward
:show-inheritance:
.. _apinn-pytorch-pooling:
Global Pooling Layers
----------------------------------------
.. automodule:: dgl.nn.pytorch.glob
SumPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.SumPooling
:members:
:show-inheritance:
AvgPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.AvgPooling
:members:
:show-inheritance:
MaxPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.MaxPooling
:members:
:show-inheritance:
SortPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.SortPooling
:members:
:show-inheritance:
WeightAndSum
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.WeightAndSum
:members:
:show-inheritance:
GlobalAttentionPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.GlobalAttentionPooling
:members:
:show-inheritance:
Set2Set
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.Set2Set
:members: forward
:show-inheritance:
SetTransformerEncoder
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.SetTransformerEncoder
:members:
:show-inheritance:
SetTransformerDecoder
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.glob.SetTransformerDecoder
:members:
:show-inheritance:
.. _apinn-pytorch-link
Predictor and Score Functions for Link Prediction
-------------------------------------------------
.. automodule:: dgl.nn.pytorch.link
EdgePredictor
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.link.EdgePredictor
:members: forward, reset_parameters
:show-inheritance:
TransE
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.link.TransE
:members: rel_emb, forward, reset_parameters
:show-inheritance:
TransR
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.link.TransR
:members: rel_emb, rel_project, forward, reset_parameters
:show-inheritance:
Heterogeneous Learning Module
----------------------------------------
HeteroGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.HeteroGraphConv
:members:
:show-inheritance:
HeteroLinear
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.HeteroLinear
:members:
:show-inheritance:
HeteroEmbedding
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.HeteroEmbedding
:members:
:show-inheritance:
.. _apinn-pytorch-util:
Utility Modules
----------------------------------------
TypedLinear
----------------------------------------
.. autoclass:: dgl.nn.pytorch.TypedLinear
:members: forward
:show-inheritance:
Sequential
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.utils.Sequential
:members:
:show-inheritance:
WeightBasis
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.utils.WeightBasis
:members:
:show-inheritance:
KNNGraph
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.factory.KNNGraph
:members:
:show-inheritance:
SegmentedKNNGraph
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.factory.SegmentedKNNGraph
:members:
:show-inheritance:
JumpingKnowledge
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.utils.JumpingKnowledge
:members: forward, reset_parameters
:show-inheritance:
NodeEmbedding Module
----------------------------------------
NodeEmbedding
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.sparse_emb.NodeEmbedding
:members:
:show-inheritance:
Explainability Models
----------------------------------------
.. automodule:: dgl.nn.pytorch.explain
GNNExplainer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.pytorch.explain.GNNExplainer
:members: explain_node, explain_graph
:show-inheritance:
......@@ -3,10 +3,255 @@
dgl.nn
==========
.. automodule:: dgl.nn
PyTorch
----------------------------------------
.. toctree::
Conv Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
nn.pytorch
nn.mxnet
nn.tensorflow
.. currentmodule:: dgl.nn.pytorch.conv
.. automodule:: dgl.nn.pytorch.conv
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
GraphConv
EdgeWeightNorm
RelGraphConv
TAGConv
GATConv
GATv2Conv
EGATConv
EdgeConv
SAGEConv
SGConv
APPNPConv
GINConv
GatedGraphConv
GMMConv
ChebConv
AGNNConv
NNConv
AtomicConv
CFConv
DotGatConv
TWIRLSConv
TWIRLSUnfoldingAndAttention
GCN2Conv
Dense Conv Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
DenseGraphConv
DenseSAGEConv
DenseChebConv
Global Pooling Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.pytorch.glob
.. automodule:: dgl.nn.pytorch.glob
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
SumPooling
AvgPooling
MaxPooling
SortPooling
WeightAndSum
GlobalAttentionPooling
Set2Set
SetTransformerEncoder
SetTransformerDecoder
Score Modules for Link Prediction and Knowledge Graph Completion
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.pytorch.link
.. automodule:: dgl.nn.pytorch.link
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
EdgePredictor
TransE
TransR
Heterogeneous Learning Modules
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.pytorch
.. automodule:: dgl.nn.pytorch
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
HeteroGraphConv
HeteroLinear
HeteroEmbedding
TypedLinear
Utility Modules
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
~utils.Sequential
~utils.WeightBasis
~factory.KNNGraph
~factory.SegmentedKNNGraph
~utils.JumpingKnowledge
~sparse_emb.NodeEmbedding
~explain.GNNExplainer
TensorFlow
----------------------------------------
Conv Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.tensorflow.conv
.. automodule:: dgl.nn.tensorflow.conv
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
GraphConv
RelGraphConv
GATConv
SAGEConv
ChebConv
SGConv
APPNPConv
GINConv
Global Pooling Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.tensorflow.glob
.. automodule:: dgl.nn.tensorflow.glob
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
SumPooling
AvgPooling
MaxPooling
SortPooling
GlobalAttentionPooling
Heterogeneous Learning Modules
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.tensorflow
.. automodule:: dgl.nn.tensorflow
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
HeteroGraphConv
MXNet
----------------------------------------
Conv Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.mxnet.conv
.. automodule:: dgl.nn.mxnet.conv
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
GraphConv
RelGraphConv
TAGConv
GATConv
EdgeConv
SAGEConv
SGConv
APPNPConv
GINConv
GatedGraphConv
GMMConv
ChebConv
AGNNConv
NNConv
Dense Conv Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
DenseGraphConv
DenseSAGEConv
DenseChebConv
Global Pooling Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.mxnet.glob
.. automodule:: dgl.nn.mxnet.glob
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
SumPooling
AvgPooling
MaxPooling
SortPooling
GlobalAttentionPooling
Set2Set
Heterogeneous Learning Modules
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. currentmodule:: dgl.nn.mxnet
.. automodule:: dgl.nn.mxnet
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
HeteroGraphConv
Utility Modules
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
~utils.Sequential
.. _apinn-tensorflow:
NN Modules (Tensorflow)
====================================
.. _apinn-tensorflow-conv:
Conv Layers
----------------------------------------
.. automodule:: dgl.nn.tensorflow.conv
GraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.GraphConv
:members: weight, bias, forward, reset_parameters
:show-inheritance:
RelGraphConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.RelGraphConv
:members: forward
:show-inheritance:
GATConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.GATConv
:members: forward
:show-inheritance:
SAGEConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.SAGEConv
:members: forward
:show-inheritance:
ChebConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.ChebConv
:members: forward
:show-inheritance:
SGConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.SGConv
:members: forward
:show-inheritance:
APPNPConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.APPNPConv
:members: forward
:show-inheritance:
GINConv
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.conv.GINConv
:members: forward
:show-inheritance:
Global Pooling Layers
----------------------------------------
.. automodule:: dgl.nn.tensorflow.glob
SumPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.glob.SumPooling
:members:
:show-inheritance:
AvgPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.glob.AvgPooling
:members:
:show-inheritance:
MaxPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.glob.MaxPooling
:members:
:show-inheritance:
SortPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.glob.SortPooling
:members:
:show-inheritance:
GlobalAttentionPooling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.glob.GlobalAttentionPooling
:members:
:show-inheritance:
Heterogeneous Graph Convolution Module
----------------------------------------
HeteroGraphConv
~~~~~~~~~~~~~~~
.. autoclass:: dgl.nn.tensorflow.HeteroGraphConv
:members:
:show-inheritance:
.. _apitransform-namespace:
dgl.transform
=============
.. currentmodule:: dgl.transform
.. automodule:: dgl.transform
BaseTransform
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: BaseTransform
:members: __call__, __repr__
:show-inheritance:
Compose
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: Compose
:show-inheritance:
AddSelfLoop
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: AddSelfLoop
:show-inheritance:
RemoveSelfLoop
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: RemoveSelfLoop
:show-inheritance:
AddReverse
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: AddReverse
:show-inheritance:
ToSimple
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: ToSimple
:show-inheritance:
LineGraph
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: LineGraph
:show-inheritance:
KHopGraph
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: KHopGraph
:show-inheritance:
AddMetaPaths
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: AddMetaPaths
:show-inheritance:
GCNNorm
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: GCNNorm
:show-inheritance:
PPR
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: PPR
:show-inheritance:
HeatKernel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: HeatKernel
:show-inheritance:
GDC
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: GDC
:show-inheritance:
NodeShuffle
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: NodeShuffle
:show-inheritance:
DropNode
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: DropNode
:show-inheritance:
DropEdge
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: DropEdge
:show-inheritance:
AddEdge
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: AddEdge
:show-inheritance:
.. _apitransform-namespace:
dgl.transforms
==============
.. currentmodule:: dgl.transforms
.. automodule:: dgl.transforms
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
BaseTransform
Compose
AddSelfLoop
RemoveSelfLoop
AddReverse
ToSimple
LineGraph
KHopGraph
AddMetaPaths
GCNNorm
PPR
HeatKernel
GDC
NodeShuffle
DropNode
DropEdge
AddEdge
......@@ -94,6 +94,7 @@ html_theme = 'sphinx_rtd_theme'
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
html_css_files = ['css/custom.css']
# Custom sidebar templates, must be a dictionary that maps document names
# to template names.
......
......@@ -115,7 +115,7 @@ After loaded, the dataset has one graph without any features:
.. note::
Edges are always directed. To have both directions, add reversed edges in the edge
CSV file or use :class:`~dgl.transform.AddReverse` to transform the loaded graph.
CSV file or use :class:`~dgl.transforms.AddReverse` to transform the loaded graph.
A graph without any feature is often of less interest. In the next example, we will show
......
......@@ -51,7 +51,7 @@ Welcome to Deep Graph Library Tutorials and Documentation
api/python/dgl.sampling
api/python/dgl.multiprocessing
api/python/dgl.contrib.UnifiedTensor
api/python/transform
api/python/transforms
api/python/udf
.. toctree::
......
......@@ -4,7 +4,7 @@ import numpy as np
from utils import arg_list
from dgl.transform import metis_partition
from dgl.transforms import metis_partition
from dgl import backend as F
import dgl
......
......@@ -3,7 +3,7 @@ from time import time
import numpy as np
import dgl
from dgl.transform import metis_partition
from dgl.transforms import metis_partition
from dgl import backend as F
def get_partition_list(g, psize):
......
......@@ -3,7 +3,7 @@ from time import time
import numpy as np
import dgl
from dgl.transform import metis_partition
from dgl.transforms import metis_partition
from dgl import backend as F
def get_partition_list(g, psize):
......
......@@ -19,7 +19,7 @@ class TemporalSampler(BlockSampler):
""" Temporal Sampler builds computational and temporal dependency of node representations via
temporal neighbors selection and screening.
The sampler expects input node to have same time stamps, in the case of TGN, it should be
The sampler expects input node to have same time stamps, in the case of TGN, it should be
either positive [src,dst] pair or negative samples. It will first take in-subgraph of seed
nodes and then screening out edges which happen after that timestamp. Finally it will sample
a fixed number of neighbor edges using random or topk sampling.
......@@ -187,7 +187,7 @@ class TemporalEdgeCollator(EdgeCollator):
neg_pair_graph = dgl.heterograph(
neg_edges, {ntype: self.g.number_of_nodes(ntype) for ntype in self.g.ntypes})
pair_graph, neg_pair_graph = dgl.transform.compact_graphs(
pair_graph, neg_pair_graph = dgl.transforms.compact_graphs(
[pair_graph, neg_pair_graph])
# Need to remap id
pair_graph.ndata[dgl.NID] = self.g.nodes()[pair_graph.ndata[dgl.NID]]
......@@ -315,7 +315,7 @@ class FastTemporalSampler(BlockSampler):
device : str
indication str which represent where the data will be stored
'cpu' store the intermediate data on cpu memory
'cuda' store the intermediate data on gpu memory
'cuda' store the intermediate data on gpu memory
Example
----------
......@@ -459,7 +459,7 @@ class FastTemporalSampler(BlockSampler):
This method is useful run the test dataset with new node,
when test new node dataset the lookup table's state should
be restored from the sampler just after validation
be restored from the sampler just after validation
Parameters
----------
......@@ -563,7 +563,7 @@ class FastTemporalEdgeCollator(EdgeCollator):
neg_pair_graph = dgl.heterograph(
neg_edges, {ntype: self.g.number_of_nodes(ntype) for ntype in self.g.ntypes})
pair_graph, neg_pair_graph = dgl.transform.compact_graphs(
pair_graph, neg_pair_graph = dgl.transforms.compact_graphs(
[pair_graph, neg_pair_graph])
# Need to remap id
......@@ -602,21 +602,21 @@ class FastTemporalEdgeCollator(EdgeCollator):
class SimpleTemporalSampler(dgl.dataloading.BlockSampler):
'''
Simple Temporal Sampler just choose the edges that happen before the current timestamp, to build the subgraph of the corresponding nodes.
Simple Temporal Sampler just choose the edges that happen before the current timestamp, to build the subgraph of the corresponding nodes.
And then the sampler uses the simplest static graph neighborhood sampling methods.
Parameters
----------
fanouts : [int, ..., int] int list
The neighbors sampling strategy
The neighbors sampling strategy
'''
def __init__(self, g, fanouts, return_eids=False):
super().__init__(len(fanouts), return_eids)
self.fanouts = fanouts
self.fanouts = fanouts
self.ts = 0
self.frontiers = [None for _ in range(len(fanouts))]
......@@ -626,7 +626,7 @@ class SimpleTemporalSampler(dgl.dataloading.BlockSampler):
'''
fanout = self.fanouts[block_id]
# List of neighbors to sample per edge type for each GNN layer, starting from the first layer.
g = dgl.in_subgraph(g, seed_nodes)
g = dgl.in_subgraph(g, seed_nodes)
g.remove_edges(torch.where(g.edata['timestamp'] > self.ts)[0]) # Deleting the the edges that happen after the current timestamp
if fanout is None: # full neighborhood sampling
......@@ -641,7 +641,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator):
'''
Temporal Edge collator merge the edges specified by eid: items
Parameters
----------
......@@ -711,7 +711,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator):
g_sampling, exclude, reverse_eids, reverse_etypes, negative_sampler)
self.n_layer = len(self.graph_sampler.fanouts)
def collate(self,items):
def collate(self,items):
'''
items: edge id in graph g.
We sample iteratively k-times and batch them into one single subgraph.
......@@ -732,7 +732,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator):
frontier = self.graph_sampler.frontiers[0]
# computing node last-update timestamp
frontier.update_all(fn.copy_e('timestamp','ts'), fn.max('ts','timestamp'))
return input_nodes, pair_graph, neg_pair_graph, [frontier]
......
......@@ -41,7 +41,7 @@ from .heterograph import DGLHeteroGraph as DGLGraph # pylint: disable=reimporte
from .merge import *
from .subgraph import *
from .traversal import *
from .transform import *
from .transforms import *
from .propagate import *
from .random import *
from .data.utils import save_graphs, load_graphs
......
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