(self, X)
| 1542 | self.model = nn.Sequential(self.layer1, self.act_fn) |
| 1543 | |
| 1544 | def forward(self, X): |
| 1545 | self.X = X |
| 1546 | if not isinstance(X, torch.Tensor): |
| 1547 | self.X = torchify(X) |
| 1548 | |
| 1549 | self.z1 = self.layer1(self.X) |
| 1550 | self.z1.retain_grad() |
| 1551 | |
| 1552 | self.out1 = self.act_fn(self.z1) |
| 1553 | self.out1.retain_grad() |
| 1554 | |
| 1555 | def extract_grads(self, X): |
| 1556 | self.forward(X) |
no test coverage detected