pytorch: excluding subgraphs from backward

excluding_subrgaphs_from_backward.py

import torch
from torch.autograd import Variable

# requires grad
# If there’s a single input to an operation that requires gradient,
# its output will also require gradient.
x = Variable(torch.randn(5, 5))
y = Variable(torch.randn(5, 5))
z = Variable(torch.randn(5, 5), requires_grad=True)
a = x + y
a.requires_grad  # False
b = a + z
b.requires_grad  # True

# Volatile differs from requires_grad in how the flag propagates.
# If there’s even a single volatile input to an operation,
# its output is also going to be volatile.
x = Variable(torch.randn(5, 5), requires_grad=True)
y = Variable(torch.randn(5, 5), volatile=True)
a = x + y
a.requires_grad  # False