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Unverified Commit 6d9433b0 authored by Mufei Li's avatar Mufei Li Committed by GitHub
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[Transform] [Doc] Rename transform to transforms and update doc (#3765) 

* Update

* Update

* Update

* Fix

* Update

* Update

* Update

* Fix
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apps/kg/partition.py
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...@@ -97,7 +97,7 @@ def main(): ...@@ -97,7 +97,7 @@ def main():
print('partition graph...') 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 tot_num_inner_edges = 0
for part_id in part_dict: for part_id in part_dict:
......
benchmarks/benchmarks/api/bench_metis_partition.py
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...@@ -15,11 +15,11 @@ def track_time(graph_name, k): ...@@ -15,11 +15,11 @@ def track_time(graph_name, k):
data = utils.process_data(graph_name) data = utils.process_data(graph_name)
graph = data[0] graph = data[0]
# dry run # dry run
gg = dgl.transform.metis_partition(graph, k) gg = dgl.transforms.metis_partition(graph, k)
# timing # timing
with utils.Timer() as t: with utils.Timer() as t:
for i in range(3): 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
docs/source/_static/css/custom.css 0 → 100644
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.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;
}
.wy-table td,
.rst-content table.docutils td,
.rst-content table.field-list td,
.wy-table th,
.rst-content table.docutils th,
.rst-content table.field-list th {
padding: 14px;
}
\ No newline at end of file
docs/source/_templates/classtemplate.rst 0 → 100644
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.. 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
docs/source/api/python/dgl.data.rst
View file @ 6d9433b0
...@@ -6,252 +6,104 @@ dgl.data ...@@ -6,252 +6,104 @@ dgl.data
.. currentmodule:: dgl.data .. currentmodule:: dgl.data
.. automodule:: dgl.data .. automodule:: dgl.data
Quick links: Base Class
---------------------------------------
* `Node Prediction Datasets`_
* `Edge Prediction Datasets`_
* `Graph Prediction Datasets`_
Base Dataset Class
---------------------------
.. autoclass:: DGLDataset
:members: download, save, load, process, has_cache, __getitem__, __len__
CSV Dataset Class .. autosummary::
----------------- :toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
.. autoclass:: CSVDataset DGLDataset
CSVDataset
Node Prediction Datasets Node Prediction Datasets
--------------------------------------- ---------------------------------------
DGL hosted datasets for node classification/regression tasks. 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__
.. 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 Edge Prediction Datasets
--------------------------------------- ---------------------------------------
DGL hosted datasets for edge classification/regression and link prediction tasks. Datasets for edge classification/regression and link prediction
.. _kgdata:
Knowlege graph dataset
```````````````````````````````````
.. autoclass:: FB15k237Dataset
:members: __getitem__, __len__
.. autoclass:: FB15kDataset
:members: __getitem__, __len__
.. autoclass:: WN18Dataset
:members: __getitem__, __len__
.. _bitcoinotcdata:
BitcoinOTC dataset .. autosummary::
``````````````````````````````````` :toctree: ../../generated/
.. autoclass:: BitcoinOTCDataset :nosignatures:
:members: __getitem__, __len__ :template: classtemplate.rst
ICEWS18 dataset
```````````````````````````````````
.. autoclass:: ICEWS18Dataset
:members: __getitem__, __len__
GDELT dataset
```````````````````````````````````
.. autoclass:: GDELTDataset
:members: __getitem__, __len__
FB15k237Dataset
FB15kDataset
WN18Dataset
BitcoinOTCDataset
ICEWS18Dataset
GDELTDataset
Graph Prediction Datasets Graph Prediction Datasets
--------------------------------------- ---------------------------------------
DGL hosted datasets for graph classification/regression tasks. Datasets for graph classification/regression tasks
.. _qm7bdata:
QM7b dataset
```````````````````````````````````
.. autoclass:: QM7bDataset
:members: __getitem__, __len__
.. _qm9data:
QM9 dataset
```````````````````````````````````
.. autoclass:: QM9Dataset
:members: __getitem__, __len__
.. _qm9edgedata: .. autosummary::
:toctree: ../../generated/
QM9Edge dataset :nosignatures:
``````````````````````````````````` :template: classtemplate.rst
.. autoclass:: QM9EdgeDataset
:members: __getitem__, __len__ QM7bDataset
QM9Dataset
.. _minigcdataset: QM9EdgeDataset
MiniGCDataset
Mini graph classification dataset TUDataset
````````````````````````````````` LegacyTUDataset
.. autoclass:: MiniGCDataset GINDataset
:members: __getitem__, __len__ FakeNewsDataset
AsNodePredDataset
.. _tudata: AsEdgePredDataset
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__
Dataset adapters Dataset adapters
------------------- -------------------
Node prediction adapter .. autosummary::
``````````````````````` :toctree: ../../generated/
:nosignatures:
.. autoclass:: AsNodePredDataset :template: classtemplate.rst
:members: __getitem__, __len__
Link prediction adapter
```````````````````````
.. autoclass:: AsLinkPredDataset
:members: __getitem__, __len__
AsNodePredDataset
AsLinkPredDataset
Utilities Utilities
----------------- -----------------
.. autosummary:: .. autosummary::
:toctree: ../../generated/ :toctree: ../../generated/
:nosignatures:
:template: classtemplate.rst
utils.get_download_dir utils.get_download_dir
utils.download utils.download
...@@ -262,6 +114,4 @@ Utilities ...@@ -262,6 +114,4 @@ Utilities
utils.save_info utils.save_info
utils.load_info utils.load_info
utils.add_nodepred_split utils.add_nodepred_split
utils.Subset
.. autoclass:: dgl.data.utils.Subset
:members: __getitem__, __len__
docs/source/api/python/index.rst
View file @ 6d9433b0
...@@ -15,4 +15,4 @@ API Reference ...@@ -15,4 +15,4 @@ API Reference
dgl.sampling dgl.sampling
dgl.contrib.UnifiedTensor dgl.contrib.UnifiedTensor
udf udf
transform transforms
docs/source/api/python/nn.mxnet.rst deleted 100644 → 0
View file @ ccaa0bf2
.. _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:
docs/source/api/python/nn.pytorch.rst deleted 100644 → 0
View file @ ccaa0bf2
.. _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:
docs/source/api/python/nn.rst
View file @ 6d9433b0
...@@ -3,10 +3,255 @@ ...@@ -3,10 +3,255 @@
dgl.nn dgl.nn
========== ==========
.. automodule:: dgl.nn PyTorch
----------------------------------------
.. toctree:: Conv Layers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
nn.pytorch .. currentmodule:: dgl.nn.pytorch.conv
nn.mxnet .. automodule:: dgl.nn.pytorch.conv
nn.tensorflow
.. 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
docs/source/api/python/nn.tensorflow.rst deleted 100644 → 0
View file @ ccaa0bf2
.. _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:
docs/source/api/python/transform.rst deleted 100644 → 0
View file @ ccaa0bf2
.. _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:
docs/source/api/python/transforms.rst 0 → 100644
View file @ 6d9433b0
.. _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
docs/source/conf.py
View file @ 6d9433b0
...@@ -94,6 +94,7 @@ html_theme = 'sphinx_rtd_theme' ...@@ -94,6 +94,7 @@ html_theme = 'sphinx_rtd_theme'
# relative to this directory. They are copied after the builtin static files, # relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css". # so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static'] html_static_path = ['_static']
html_css_files = ['css/custom.css']
# Custom sidebar templates, must be a dictionary that maps document names # Custom sidebar templates, must be a dictionary that maps document names
# to template names. # to template names.
......
docs/source/guide/data-loadcsv.rst
View file @ 6d9433b0
...@@ -115,7 +115,7 @@ After loaded, the dataset has one graph without any features: ...@@ -115,7 +115,7 @@ After loaded, the dataset has one graph without any features:
.. note:: .. note::
Edges are always directed. To have both directions, add reversed edges in the edge 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 A graph without any feature is often of less interest. In the next example, we will show
......
docs/source/index.rst
View file @ 6d9433b0
...@@ -51,7 +51,7 @@ Welcome to Deep Graph Library Tutorials and Documentation ...@@ -51,7 +51,7 @@ Welcome to Deep Graph Library Tutorials and Documentation
api/python/dgl.sampling api/python/dgl.sampling
api/python/dgl.multiprocessing api/python/dgl.multiprocessing
api/python/dgl.contrib.UnifiedTensor api/python/dgl.contrib.UnifiedTensor
api/python/transform api/python/transforms
api/python/udf api/python/udf
.. toctree:: .. toctree::
......
examples/pytorch/cluster_gcn/partition_utils.py
View file @ 6d9433b0
...@@ -4,7 +4,7 @@ import numpy as np ...@@ -4,7 +4,7 @@ import numpy as np
from utils import arg_list from utils import arg_list
from dgl.transform import metis_partition from dgl.transforms import metis_partition
from dgl import backend as F from dgl import backend as F
import dgl import dgl
......
examples/pytorch/ogb/cluster-gat/partition_utils.py
View file @ 6d9433b0
...@@ -3,7 +3,7 @@ from time import time ...@@ -3,7 +3,7 @@ from time import time
import numpy as np import numpy as np
import dgl import dgl
from dgl.transform import metis_partition from dgl.transforms import metis_partition
from dgl import backend as F from dgl import backend as F
def get_partition_list(g, psize): def get_partition_list(g, psize):
......
examples/pytorch/ogb/cluster-sage/partition_utils.py
View file @ 6d9433b0
...@@ -3,7 +3,7 @@ from time import time ...@@ -3,7 +3,7 @@ from time import time
import numpy as np import numpy as np
import dgl import dgl
from dgl.transform import metis_partition from dgl.transforms import metis_partition
from dgl import backend as F from dgl import backend as F
def get_partition_list(g, psize): def get_partition_list(g, psize):
......
examples/pytorch/tgn/dataloading.py
View file @ 6d9433b0
...@@ -19,7 +19,7 @@ class TemporalSampler(BlockSampler): ...@@ -19,7 +19,7 @@ class TemporalSampler(BlockSampler):
""" Temporal Sampler builds computational and temporal dependency of node representations via """ Temporal Sampler builds computational and temporal dependency of node representations via
temporal neighbors selection and screening. 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 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 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. a fixed number of neighbor edges using random or topk sampling.
...@@ -187,7 +187,7 @@ class TemporalEdgeCollator(EdgeCollator): ...@@ -187,7 +187,7 @@ class TemporalEdgeCollator(EdgeCollator):
neg_pair_graph = dgl.heterograph( neg_pair_graph = dgl.heterograph(
neg_edges, {ntype: self.g.number_of_nodes(ntype) for ntype in self.g.ntypes}) 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]) [pair_graph, neg_pair_graph])
# Need to remap id # Need to remap id
pair_graph.ndata[dgl.NID] = self.g.nodes()[pair_graph.ndata[dgl.NID]] pair_graph.ndata[dgl.NID] = self.g.nodes()[pair_graph.ndata[dgl.NID]]
...@@ -315,7 +315,7 @@ class FastTemporalSampler(BlockSampler): ...@@ -315,7 +315,7 @@ class FastTemporalSampler(BlockSampler):
device : str device : str
indication str which represent where the data will be stored indication str which represent where the data will be stored
'cpu' store the intermediate data on cpu memory '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 Example
---------- ----------
...@@ -459,7 +459,7 @@ class FastTemporalSampler(BlockSampler): ...@@ -459,7 +459,7 @@ class FastTemporalSampler(BlockSampler):
This method is useful run the test dataset with new node, This method is useful run the test dataset with new node,
when test new node dataset the lookup table's state should 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 Parameters
---------- ----------
...@@ -563,7 +563,7 @@ class FastTemporalEdgeCollator(EdgeCollator): ...@@ -563,7 +563,7 @@ class FastTemporalEdgeCollator(EdgeCollator):
neg_pair_graph = dgl.heterograph( neg_pair_graph = dgl.heterograph(
neg_edges, {ntype: self.g.number_of_nodes(ntype) for ntype in self.g.ntypes}) 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]) [pair_graph, neg_pair_graph])
# Need to remap id # Need to remap id
...@@ -602,21 +602,21 @@ class FastTemporalEdgeCollator(EdgeCollator): ...@@ -602,21 +602,21 @@ class FastTemporalEdgeCollator(EdgeCollator):
class SimpleTemporalSampler(dgl.dataloading.BlockSampler): 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. And then the sampler uses the simplest static graph neighborhood sampling methods.
Parameters Parameters
---------- ----------
fanouts : [int, ..., int] int list fanouts : [int, ..., int] int list
The neighbors sampling strategy The neighbors sampling strategy
''' '''
def __init__(self, g, fanouts, return_eids=False): def __init__(self, g, fanouts, return_eids=False):
super().__init__(len(fanouts), return_eids) super().__init__(len(fanouts), return_eids)
self.fanouts = fanouts self.fanouts = fanouts
self.ts = 0 self.ts = 0
self.frontiers = [None for _ in range(len(fanouts))] self.frontiers = [None for _ in range(len(fanouts))]
...@@ -626,7 +626,7 @@ class SimpleTemporalSampler(dgl.dataloading.BlockSampler): ...@@ -626,7 +626,7 @@ class SimpleTemporalSampler(dgl.dataloading.BlockSampler):
''' '''
fanout = self.fanouts[block_id] fanout = self.fanouts[block_id]
# List of neighbors to sample per edge type for each GNN layer, starting from the first layer. # 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 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 if fanout is None: # full neighborhood sampling
...@@ -641,7 +641,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator): ...@@ -641,7 +641,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator):
''' '''
Temporal Edge collator merge the edges specified by eid: items Temporal Edge collator merge the edges specified by eid: items
Parameters Parameters
---------- ----------
...@@ -711,7 +711,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator): ...@@ -711,7 +711,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator):
g_sampling, exclude, reverse_eids, reverse_etypes, negative_sampler) g_sampling, exclude, reverse_eids, reverse_etypes, negative_sampler)
self.n_layer = len(self.graph_sampler.fanouts) self.n_layer = len(self.graph_sampler.fanouts)
def collate(self,items): def collate(self,items):
''' '''
items: edge id in graph g. items: edge id in graph g.
We sample iteratively k-times and batch them into one single subgraph. We sample iteratively k-times and batch them into one single subgraph.
...@@ -732,7 +732,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator): ...@@ -732,7 +732,7 @@ class SimpleTemporalEdgeCollator(dgl.dataloading.EdgeCollator):
frontier = self.graph_sampler.frontiers[0] frontier = self.graph_sampler.frontiers[0]
# computing node last-update timestamp # computing node last-update timestamp
frontier.update_all(fn.copy_e('timestamp','ts'), fn.max('ts','timestamp')) frontier.update_all(fn.copy_e('timestamp','ts'), fn.max('ts','timestamp'))
return input_nodes, pair_graph, neg_pair_graph, [frontier] return input_nodes, pair_graph, neg_pair_graph, [frontier]
......
python/dgl/__init__.py
View file @ 6d9433b0
...@@ -41,7 +41,7 @@ from .heterograph import DGLHeteroGraph as DGLGraph # pylint: disable=reimporte ...@@ -41,7 +41,7 @@ from .heterograph import DGLHeteroGraph as DGLGraph # pylint: disable=reimporte
from .merge import * from .merge import *
from .subgraph import * from .subgraph import *
from .traversal import * from .traversal import *
from .transform import * from .transforms import *
from .propagate import * from .propagate import *
from .random import * from .random import *
from .data.utils import save_graphs, load_graphs from .data.utils import save_graphs, load_graphs
......
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