(self, d2, d1, t1, t2)
| 5 | |
| 6 | class TABL_layer(pl.LightningModule): |
| 7 | def __init__(self, d2, d1, t1, t2): |
| 8 | super().__init__() |
| 9 | self.t1 = t1 |
| 10 | |
| 11 | weight = torch.Tensor(d2, d1) |
| 12 | self.W1 = nn.Parameter(weight) |
| 13 | nn.init.kaiming_uniform_(self.W1, nonlinearity='relu') |
| 14 | |
| 15 | weight2 = torch.Tensor(t1, t1) |
| 16 | self.W = nn.Parameter(weight2) |
| 17 | nn.init.constant_(self.W, 1 / t1) |
| 18 | |
| 19 | weight3 = torch.Tensor(t1, t2) |
| 20 | self.W2 = nn.Parameter(weight3) |
| 21 | nn.init.kaiming_uniform_(self.W2, nonlinearity='relu') |
| 22 | |
| 23 | bias1 = torch.Tensor(d2, t2) |
| 24 | self.B = nn.Parameter(bias1) |
| 25 | nn.init.constant_(self.B, 0) |
| 26 | |
| 27 | l = torch.Tensor(1, ) |
| 28 | self.l = nn.Parameter(l) |
| 29 | nn.init.constant_(self.l, 0.5) |
| 30 | |
| 31 | self.activation = nn.ReLU() |
| 32 | |
| 33 | def forward(self, X): |
| 34 |
nothing calls this directly
no outgoing calls
no test coverage detected