(self, x)
| 175 | self.dropout = nn.Dropout(dropout) |
| 176 | |
| 177 | def forward(self, x): |
| 178 | # do patching |
| 179 | n_vars = x.shape[1] |
| 180 | x = self.padding_patch_layer(x) |
| 181 | x = x.unfold(dimension=-1, size=self.patch_len, step=self.stride) |
| 182 | x = torch.reshape(x, (x.shape[0] * x.shape[1], x.shape[2], x.shape[3])) |
| 183 | # Input encoding |
| 184 | x = self.value_embedding(x) |
| 185 | return self.dropout(x), n_vars |
| 186 | |
| 187 | |
| 188 | class DataEmbedding_wo_time(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected