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Method __init__

python/lbann/modules/graph/sparse/GatedGraphConv.py:18–61  ·  view source on GitHub ↗

Initialize GatedGraph layer Args: input_channels (int): The size of the input node features output_channels (int): The output size of the node features num_nodes (int): Number of vertices in the graph num_layers (int): Number of passes through

(self,
                 input_channels,
                 output_channels,
                 num_nodes,
                 num_layers = 1,
                 name = None)

Source from the content-addressed store, hash-verified

16 """
17 global_count = 0
18 def __init__(self,
19 input_channels,
20 output_channels,
21 num_nodes,
22 num_layers = 1,
23 name = None):
24 """Initialize GatedGraph layer
25 Args:
26 input_channels (int): The size of the input node features
27 output_channels (int): The output size of the node features
28 num_nodes (int): Number of vertices in the graph
29 num_layers (int): Number of passes through the GRU (default: 1)
30 name (str): Name of the layers and prefix to use for the layers.
31 data_layout (str): Data layout (default: data parallel)
32 """
33 super().__init__()
34
35 ## Add Name for the components for the layer
36 GatedGraphConv.global_count +=1
37 self.name = (name
38 if name
39 else 'GatedGraphConv_{}'.format(GatedGraphConv.global_count))
40
41
42 ## Add variables
43 self.output_channel_size = output_channels
44 self.input_channel_size = input_channels
45 self.num_nodes = num_nodes
46
47 self.rnn = lbann.modules.ChannelwiseGRU(num_nodes, output_channels)
48
49 self.num_layers = num_layers
50 self.nns = []
51
52 for i in range(num_layers):
53
54 weights = lbann.Weights(initializer = lbann.UniformInitializer(min =-1/(math.sqrt(output_channels)),
55 max = 1/(math.sqrt(output_channels))))
56 nn = \
57 ChannelwiseFullyConnectedModule(self.output_channel_size,
58 bias=False,
59 weights=[weights],
60 name=f"{self.name}_nn_{i}")
61 self.nns.append(nn)
62
63
64 def forward(self, node_feature_mat, source_indices, target_indices):

Callers

nothing calls this directly

Calls 2

sqrtMethod · 0.80

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