(self, configs)
| 21 | |
| 22 | class Model(torch.nn.Module): |
| 23 | def __init__(self, configs): |
| 24 | super(Model, self).__init__() |
| 25 | out_channels= configs.d_model * 2 |
| 26 | self.pred_len = configs.pred_len |
| 27 | |
| 28 | self.l_x1 = torch.nn.Linear(configs.seq_len, out_channels) |
| 29 | self.l_m1 = torch.nn.Linear(1, out_channels//4) |
| 30 | self.l_s1 = torch.nn.Linear(1, out_channels//4) |
| 31 | |
| 32 | self.l_x2 = torch.nn.Linear(out_channels, configs.pred_len) |
| 33 | self.l_m2 = torch.nn.Linear(out_channels//4, 1) |
| 34 | self.l_s2 = torch.nn.Linear(out_channels//4, 1) |
| 35 | |
| 36 | self.l_o1 = torch.nn.Linear(configs.pred_len, out_channels) |
| 37 | self.l_o2 = torch.nn.Linear(out_channels, configs.pred_len) |
| 38 | |
| 39 | |
| 40 | self.L1 = torch.nn.L1Loss() |
| 41 | self.L2 = torch.nn.MSELoss() |
| 42 | |
| 43 | print("L_Decom ...") |
| 44 | |
| 45 | def forward(self, x, edge_indexs=None, edge_weights=None, y=None): |
| 46 |
nothing calls this directly
no outgoing calls
no test coverage detected