Thanks a lot for your answer.
This works out for me but I want to implement the discussed Conv2D weights into this simple network:
class CNN(nn.Module):
def __init__(self):
    super(CNN, self).__init__()
    self.features =nn.Conv2d(1, 2, kernel_size=3, stride=1, padding=0)
                           nn.ReLU(),
                           nn.MaxPool2d(kernel_size=2, stride=1)
                                 )
    self.drop_out = torch.nn.Dropout(0.6)

def forward(self, x):
    x=self.features(x)
    x=self.drop_out(x)
    return x

cnn=CNN()
I would be appreciated if give me a hint on this as well
Thanks