For example,there are 3 two-dimensional matrices. And it’s shape is [3,2,2]
Of course, i could calculate their 2-norm by this way:
x = torch.randn(3, 2, 2)
for i in range(x.shape[0]):
print(torch.norm(x[i], 2))
and it’s output is
tensor(2.2709)
tensor(1.4141)
tensor(2.7118)
This is a solution. Well, as we all know the for-looping is inefficientis. and could pytorch calculate their 2-norm without using for-looping?