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class Model(nn.Module):
    def __init__(self, args, data):
        super(Model, self).__init__()
        self.use_cuda = args.cuda
        self.P = args.window;
        self.m = 12
        self.hidR = args.hidRNN;
        self.hidC = args.hidCNN;
        self.hidS = args.hidSkip;
        self.Ck = args.CNN_kernel;
        self.skip = args.skip;
        self.pt = (self.P - self.Ck) / self.skip
        self.hw = args.highway_window
        self.conv1 = nn.Conv2d(1, self.hidC, kernel_size=(self.Ck, self.m));
        self.GRU1 = nn.GRU(self.hidC, self.hidR);
        self.dropout = nn.Dropout(p=args.dropout);
        if self.skip > 0:
            self.GRUskip = nn.GRU(self.hidC, self.hidS);
            self.linear1 = nn.Linear(self.hidR + self.skip * self.hidS, self.m);
        else:
            self.linear1 = nn.Linear(self.hidR, self.m);
        if self.hw > 0:
            self.highway = nn.Linear(self.hw, 1);
        self.output = None;
        if (args.output_fun == 'sigmoid'):
            self.output = F.sigmoid;
        if (args.output_fun == 'tanh'):
            self.output = F.tanh;

    def forward(self, x):
        batch_size = x.size(0);

        # CNN
        c = x.view(-1, 1, self.P, self.m);
        c = F.relu(self.conv1(c));
        c = self.dropout(c);
        c = torch.squeeze(c, 3);

        # RNN
        r = c.permute(2, 0, 1).contiguous();
        _, r = self.GRU1(r);
        r = self.dropout(torch.squeeze(r, 0));

        # skip-rnn

        if self.skip > 0:
            s = c[:, :, int(-self.pt * self.skip):].contiguous();
            s = s.view(batch_size, self.hidC, int(self.pt), self.skip)
            s = s.permute(2, 0, 3, 1).contiguous();
            s = s.view(int(self.pt), batch_size * self.skip, self.hidC)
            _, s = self.GRUskip(s);
            s = s.view(batch_size, self.skip * self.hidS);
            s = self.dropout(s);
            r = torch.cat((r, s), 1);

        res = self.linear1(r);

        # highway
        if self.hw > 0:
            z = x[:, -self.hw:, :];
            z = z.permute(0, 2, 1).contiguous().view(-1, self.hw);
            z = self.highway(z);
            z = z.view(-1, self.m);
            res = res + z;

        if self.output:
            res = self.output(res);
        return res;