Method __init__

baselines.py:26–31

(self, seq, n_fea, node=247)

class LSTM(nn.Module):
    def __init__(self, seq, n_fea, node=247):
        super(LSTM, self).__init__()
        self.nodes = node
        self.encoder = nn.Conv2d(self.nodes, self.nodes, (n_fea, n_fea))  # input.shape: [batch, channel, width, height]
        self.lstm = nn.LSTM(self.nodes, self.nodes, num_layers=2, batch_first=True)
        self.decoder = nn.Linear(seq-n_fea+1, 1)

    def forward(self, occ, prc):  # occ.shape = [batch, node, seq]
        x = torch.stack([occ, prc], dim=3)