Hello!

I’ve encountered with some problems with PyTorch and wrote the minimal example, which didn’t work.

If to launch this code in jupyter notebook, kernel dies:

```
import torch
from torch.autograd import Variable, Function
# I've removed all computations from this class:
class Some_class(Function):
@staticmethod
def forward(ctx, A, X):
ctx.A = A
return torch.ones(A.shape[0], X.shape[1]).double()
@staticmethod
def backward(ctx, g):
return Variable(torch.ones_like(ctx.A).double(), requires_grad=False), None
f = Some_class.apply
n, l = 7, 1
A = Variable(torch.rand(n, 3).double(), requires_grad=True)
U = Variable(torch.rand(n, l).double())
b = Variable(torch.rand(n, l).double())
Z = b - f(A, U)
Y = f(A, Z)
res = torch.norm(Y)
res.backward()
```

But if to run it from terminal, everything is OK.

Could you tell me is it a common bug with Jupyter?