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?