Hi!
How can I use a scalar as a weight on pytorch and use state_dict for saving the model?
For example, I just want to multiply the whole tensor by w1
and then save it on my state_dict.
If I do as follows, the state_dict will be empty
import torch
from torch import nn
class Network(nn.Module):
def __init__(self):
super().__init__()
self.w1 = torch.rand([1])
def forward(self, x):
x = self.w1 * x
return x
model = Network()
print(model.state_dict())
What is the correct way for doing it?