pgl
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Introduction
Paddle Graph Learning (PGL)
Quick Start
Quick Start Instructions
Quick Start with HeterGraph
Examples
Graph Isomorphism Network (GIN)
GCN: Graph Convolutional Networks
GAT: Graph Attention Networks
RGCN: Modeling Relational Data with Graph Convolutional Networks
Easy Paper Reproduction for Citation Network ( Cora / Pubmed / Citeseer )
GraphSAGE: Inductive Representation Learning on Large Graphs
API Reference
API Reference
The Team
The Team
pgl
Docs
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Index
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Index
A
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B
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C
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D
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E
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F
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G
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I
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L
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M
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N
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O
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P
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R
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S
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T
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V
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Y
A
adj_dst_index() (pgl.graph.Graph property)
adj_src_index() (pgl.graph.Graph property)
APPNP (class in pgl.nn.conv)
ArXivDataset (class in pgl.dataset)
B
batch() (pgl.graph.Graph static method)
BlogCatalogDataset (class in pgl.dataset)
C
CitationDataset (class in pgl.dataset)
CoraDataset (class in pgl.dataset)
D
degree_norm() (in module pgl.nn.functional.graph_op)
disjoint() (pgl.graph.Graph class method)
dump() (pgl.graph.Graph method)
E
edge_expand() (pgl.message.Message method)
edge_feat() (pgl.graph.Graph property)
edges() (pgl.graph.Graph property)
F
forward() (pgl.nn.conv.APPNP method)
(pgl.nn.conv.GATConv method)
(pgl.nn.conv.GCNConv method)
(pgl.nn.conv.GCNII method)
(pgl.nn.conv.GINConv method)
(pgl.nn.conv.GraphSageConv method)
(pgl.nn.conv.PinSageConv method)
(pgl.nn.conv.TransformerConv method)
(pgl.nn.pool.GraphPool method)
G
GATConv (class in pgl.nn.conv)
GCNConv (class in pgl.nn.conv)
GCNII (class in pgl.nn.conv)
GINConv (class in pgl.nn.conv)
Graph (class in pgl.graph)
graph (pgl.dataset.ArXivDataset attribute)
(pgl.dataset.BlogCatalogDataset attribute)
(pgl.dataset.CitationDataset attribute)
(pgl.dataset.CoraDataset attribute)
graph_edge_id() (pgl.graph.Graph property)
graph_node_id() (pgl.graph.Graph property)
GraphPool (class in pgl.nn.pool)
graphsage_sample() (in module pgl.sampling)
GraphSageConv (class in pgl.nn.conv)
I
indegree() (pgl.graph.Graph method)
is_tensor() (pgl.graph.Graph method)
L
load() (pgl.graph.Graph class method)
M
Message (class in pgl.message)
N
node_batch_iter() (pgl.graph.Graph method)
node_feat() (pgl.graph.Graph property)
nodes() (pgl.graph.Graph property)
num_classes (pgl.dataset.CitationDataset attribute)
(pgl.dataset.CoraDataset attribute)
num_edges() (pgl.graph.Graph property)
num_graph() (pgl.graph.Graph property)
num_groups (pgl.dataset.BlogCatalogDataset attribute)
num_nodes() (pgl.graph.Graph property)
numpy() (pgl.graph.Graph method)
O
outdegree() (pgl.graph.Graph method)
P
pgl.dataset (module)
pgl.graph (module)
pgl.message (module)
pgl.nn.conv (module)
pgl.nn.functional.graph_op (module)
pgl.nn.pool (module)
pgl.sampling (module)
PinSageConv (class in pgl.nn.conv)
predecessor() (pgl.graph.Graph method)
R
random_walk() (in module pgl.sampling)
recv() (pgl.graph.Graph method)
RedditDataset (class in pgl.dataset)
reduce() (pgl.message.Message method)
reduce_attention() (pgl.nn.conv.TransformerConv method)
reduce_max() (pgl.message.Message method)
reduce_mean() (pgl.message.Message method)
reduce_min() (pgl.message.Message method)
reduce_softmax() (pgl.message.Message method)
reduce_sum() (pgl.message.Message method)
S
sample_predecessor() (pgl.graph.Graph method)
sample_successor() (pgl.graph.Graph method)
send() (pgl.graph.Graph method)
send_attention() (pgl.nn.conv.TransformerConv method)
send_recv() (pgl.graph.Graph method)
(pgl.nn.conv.TransformerConv method)
sorted_edges() (pgl.graph.Graph method)
subgraph() (in module pgl.sampling)
successor() (pgl.graph.Graph method)
T
tensor() (pgl.graph.Graph method)
test_index (pgl.dataset.BlogCatalogDataset attribute)
(pgl.dataset.CitationDataset attribute)
(pgl.dataset.CoraDataset attribute)
to_mmap() (pgl.graph.Graph method)
train_index (pgl.dataset.BlogCatalogDataset attribute)
(pgl.dataset.CitationDataset attribute)
(pgl.dataset.CoraDataset attribute)
TransformerConv (class in pgl.nn.conv)
V
val_index (pgl.dataset.CitationDataset attribute)
(pgl.dataset.CoraDataset attribute)
Y
y (pgl.dataset.CitationDataset attribute)
(pgl.dataset.CoraDataset attribute)
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