(self, hidden_dim, device=torch.cuda.device('cuda'))
| 782 | |
| 783 | class Meta_Graph1(nn.Module): |
| 784 | def __init__(self, hidden_dim, device=torch.cuda.device('cuda')): |
| 785 | super().__init__() |
| 786 | |
| 787 | |
| 788 | self.device = device |
| 789 | self.gcn = GraphConvolution(device=device, |
| 790 | hidden_dim=hidden_dim, |
| 791 | sparse_inputs=False, |
| 792 | act=nn.Tanh(), |
| 793 | bias=True, dropout=0.6).to(device=device) |
| 794 | |
| 795 | torch.cuda.empty_cache() |
| 796 | self.apply(self._init_weights) |
| 797 | |
| 798 | def _init_weights(self, m): |
| 799 | if isinstance(m, nn.Linear): |
nothing calls this directly
no test coverage detected