@albanD
related question. Why aren’t cloned vectors leaf nodes (specially if they are clones of leaf nodes):
import torch
​
w = torch.tensor([2.0], requires_grad=True)
w1 = torch.tensor([2.0], requires_grad=False)
w_clone = w.clone()
​
print(w)
print(w.is_leaf)
print(w1.is_leaf)
print(w_clone)
print(w_clone is w)
print(w_clone == w)
print(w_clone.is_leaf)
tensor([2.], requires_grad=True)
'''
output:
'''
True
True
tensor([2.], grad_fn=<CloneBackward>)
False
tensor([True])
False

what does it even mean to do a backward pass/differentiation of a cloned operation?