(self, idx)
| 190 | return len(self.occ) |
| 191 | |
| 192 | def __getitem__(self, idx): # occ: batch, seq, node |
| 193 | # sampling |
| 194 | pseudo_prc = torch.Tensor(self.prc[idx, :, :] * (1+self.prc_chg)) # [node, seq] |
| 195 | pseudo_label = torch.tan(torch.Tensor(self.label[idx, :] * (1+self.label_chg))) # [node, ] |
| 196 | |
| 197 | # to device |
| 198 | output_occ = torch.transpose(self.occ[idx, :, :], 0, 1).to(self.device) |
| 199 | output_prc = torch.transpose(self.prc[idx, :, :], 0, 1).to(self.device) |
| 200 | output_label = self.label[idx, :].to(self.device) |
| 201 | output_pseudo_prc = torch.transpose(pseudo_prc, 0, 1).to(self.device) |
| 202 | output_pseudo_label = pseudo_label.to(self.device) |
| 203 | |
| 204 | return output_occ, output_prc, output_label, output_pseudo_prc, output_pseudo_label |
| 205 | |
| 206 | |
| 207 | def meta_division(data, support_rate, query_rate): |
nothing calls this directly
no outgoing calls
no test coverage detected