@ptrblck Running this with device=‘cpu’ will trigger that error, but it is fine with cuda (torch 1.8.1)
from torch import nn
import torch

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        kernel_size = 3
        self.norm_conv = nn.Conv2d(2, 2, kernel_size)
        with torch.no_grad():
            self.norm_conv.weight = nn.Parameter(torch.ones((1, 1, kernel_size, kernel_size)).expand(2, 2, kernel_size, kernel_size), requires_grad=False)

    def forward(self, x):
        return self.norm_conv(x)

device = 'cpu'

model = Net().to(device)
torch.save(model.state_dict(), 'checkpoint.pth')

model2 = Net()
model.eval()
param_dict = torch.load('checkpoint.pth', map_location=device)
model.load_state_dict(param_dict)