කෝරාදත්ත කට්ටලය මත ප්රස්තාරය අවධානය ජාලය v2 (GATV2) පුහුණු

13import torch
14from torch import nn
15
16from labml import experiment
17from labml.configs import option
18from labml_helpers.module import Module
19from labml_nn.graphs.gat.experiment import Configs as GATConfigs
20from labml_nn.graphs.gatv2 import GraphAttentionV2Layer

23class GATv2(Module):

30    def __init__(self, in_features: int, n_hidden: int, n_classes: int, n_heads: int, dropout: float,
31                 share_weights: bool = True):

40        super().__init__()

43        self.layer1 = GraphAttentionV2Layer(in_features, n_hidden, n_heads,
44                                            is_concat=True, dropout=dropout, share_weights=share_weights)

46        self.activation = nn.ELU()

48        self.output = GraphAttentionV2Layer(n_hidden, n_classes, 1,
49                                            is_concat=False, dropout=dropout, share_weights=share_weights)

51        self.dropout = nn.Dropout(dropout)

53    def forward(self, x: torch.Tensor, adj_mat: torch.Tensor):

60        x = self.dropout(x)

62        x = self.layer1(x, adj_mat)

64        x = self.activation(x)

66        x = self.dropout(x)

68        return self.output(x, adj_mat)

71class Configs(GATConfigs):

80    share_weights: bool = False

82    model: GATv2 = 'gat_v2_model'

85@option(Configs.model)
86def gat_v2_model(c: Configs):

90    return GATv2(c.in_features, c.n_hidden, c.n_classes, c.n_heads, c.dropout, c.share_weights).to(c.device)

93def main():

95    conf = Configs()

97    experiment.create(name='gatv2')

99    experiment.configs(conf, {

101        'optimizer.optimizer': 'Adam',
102        'optimizer.learning_rate': 5e-3,
103        'optimizer.weight_decay': 5e-4,
104
105        'dropout': 0.7,
106    })

109    with experiment.start():

111        conf.run()

115if __name__ == '__main__':
116    main()