Hello,
Suppose I have the following network:
    class Net3(torch.nn.Module): # Initiate the network
        def __init__(self):
            super(Net3,self).__init__()
            self.fc1 = torch.nn.Linear(1,neurons,bias=True)
            self.fc2 = torch.nn.Linear(neurons,1,bias=False)
            self.relu = torch.nn.ReLU()
        
        def forward(self,x):
            x = self.relu(self.fc1(x))
            return self.fc2(x)
            
    model = Net3()

I have two questions:

How can I set myself the weights and bias of the layer fc1 instead of random initialization?
How can I prevent the model to optimize the weights and bias of the layer fc1?