(self, configs)
| 8 | Normalization-Linear |
| 9 | """ |
| 10 | def __init__(self, configs): |
| 11 | super(Model, self).__init__() |
| 12 | self.seq_len = configs.seq_len |
| 13 | self.pred_len = configs.pred_len |
| 14 | self.Linear = nn.Linear(self.seq_len, self.pred_len) |
| 15 | # Use this line if you want to visualize the weights |
| 16 | # self.Linear.weight = nn.Parameter((1/self.seq_len)*torch.ones([self.pred_len,self.seq_len])) |
| 17 | |
| 18 | def forward(self, x): |
| 19 | # x: [Batch, Input length, Channel] |
nothing calls this directly
no outgoing calls
no test coverage detected