Hi,
I initialized a model weight and bias parameter in init to learn while training but during training these weights are not moved to device cuda on performing .to(device) while the rest of the parameters moved. Please see sample code snipped
class myModule(nn.Module):
	def __init__(self,in_dim,hid_dim,out_dim):
		super(myModule,self).__init__()
		self.encoder=nn.Sequential(
			nn.Linear(in_dim,hid_dim),
            nn.ReLU(),
            nn.Linear(hid_dim,hid_dim//2),
			nn.BatchNorm1d(hid_dim//2),
			nn.ReLU(),
			nn.Dropout(p=0.2),
            nn.Linear(hid_dim//2,hid_dim//3),
			nn.BatchNorm1d(hid_dim//3),
			nn.ReLU(),
			nn.Dropout(p=0.2),
			nn.Linear(hid_dim//3,out_dim)
			)
		# self.linear=nn.Linear(out_dim,1,bias=False)
		self.S=torch.randn((out_dim,out_dim),requires_grad=True)
		self.b=torch.randn(1,requires_grad=True)

	def forward(self,inp1,inp2):
		x=self.encoder(inp1)
		y=self.encoder(inp2)
		# out=torch.pow((out1-out2),2)
		out=torch.matmul(x,y.T).diag() - torch.matmul(torch.matmul(x,self.S),x.T).diag()-torch.matmul(torch.matmul(y,self.S),y.T).diag()+self.b
		return out


In the above module, I am getting error at out = torch.matmul line saying self.S and self.b are not on device cude.
Shouldn’t doing model.to(device) transfer all model parameters to cuda?
Thanks for your help