def forward(self, x, hidden=None):
if hidden is None:
hx = torch.zeors_like(x)
cx = torch.zeros_like(x)
else:
hx, cx = hidden
gates = self.x2h(x) + self.h2h(hx)
ingate, forgetgate, cellgate, outgate = torch.split(gates, self.hidden_size, dim=1)
ingate = torch.sigmoid(ingate)
forgetgate = torch.sigmoid(forgetgate)
cellgate = torch.tanh(cellgate)
outgate = torch.sigmoid(outgate)
cy = torch.mul(cx, forgetgate) + torch.mul(ingate, cellgate)
hy = torch.mul(outgate, torch.tanh(cy))
return (hy, cy)
def forward(self, x):
rmask = torch.ge(x.r, torch.zeors_like(x.r)).float()
imask = torch.ge(x.i, torch.zeors_like(x.i)).float()
mask = rmask * imask
out = CPLX(x.r * mask, x.i * mask)
return out