(self, x)
| 62 | adjoint=adjoint, perturb=perturb) |
| 63 | |
| 64 | def forward(self, x): |
| 65 | x = x[..., -self.intermediate_seq_len:] |
| 66 | for tconv in self.inception_1.tconv: |
| 67 | tconv.dilation = (1, self.new_dilation) |
| 68 | for tconv in self.inception_2.tconv: |
| 69 | tconv.dilation = (1, self.new_dilation) |
| 70 | |
| 71 | filter = self.inception_1(x) |
| 72 | filter = torch.tanh(filter) |
| 73 | gate = self.inception_2(x) |
| 74 | gate = torch.sigmoid(gate) |
| 75 | x = filter * gate |
| 76 | |
| 77 | self.new_dilation *= self.dilation_factor |
| 78 | self.intermediate_seq_len = x.size(3) |
| 79 | |
| 80 | x = F.dropout(x, self.dropout, training=self.training) |
| 81 | |
| 82 | x = self.gconv_1(x, self.graph) + self.gconv_2(x, self.graph.transpose(1, 0)) |
| 83 | |
| 84 | x = nn.functional.pad(x, (self.receptive_field - x.size(3), 0)) |
| 85 | |
| 86 | return x |
| 87 | |
| 88 | def setGraph(self, graph): |
| 89 | self.graph = graph |
nothing calls this directly
no outgoing calls
no test coverage detected