So, the revised code example will be as follows:
import torch
import torch.nn as nn

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(3,3, 3)
        K = torch.Tensor([[1 ,0, -1],[2, 0 ,-2], [1, 0 ,-1]])
#        I think I should make the shape/size like this?
        K = torch.unsqueeze(torch.unsqueeze(K,0),0)
        #with torch.no_grad():
        self.conv1.weight.data = self.conv1.weight.data + K

    def forward(self, x):
        x = self.conv1(x)
        return x

net = Net()
net(torch.randn(4,3,10,10))