Method forward

LDPS_Graph/layers/PatchTST_backbone.py:159–176

(self, x, 
                edge_index: torch.LongTensor,
                edge_weight: torch.FloatTensor)

        
    def forward(self, x, 
                edge_index: torch.LongTensor,
                edge_weight: torch.FloatTensor) -> Tensor:                                              # x: [bs x nvars x patch_len x patch_num]
        
        n_vars = x.shape[1]
        # Input encoding
        x = x.permute(0,1,3,2)                                                   # x: [bs x nvars x patch_num x patch_len]
        x = self.W_P(x)                                                          # x: [bs x nvars x patch_num x d_model]

        u = torch.reshape(x, (x.shape[0]*x.shape[1],x.shape[2],x.shape[3]))      # u: [bs * nvars x patch_num x d_model]
        u = self.dropout(u + self.W_pos)                                         # u: [bs * nvars x patch_num x d_model]

        # Encoder
        z = self.encoder(u, edge_index, edge_weight)                                                      # z: [bs * nvars x patch_num x d_model]
        z = torch.reshape(z, (-1,n_vars,z.shape[-2],z.shape[-1]))                # z: [bs x nvars x patch_num x d_model]
        z = z.permute(0,1,3,2)                                                   # z: [bs x nvars x d_model x patch_num]
        
        return z