When you call autograd.grad
function with only_inputs=False
, does it fill in the .grad
member for all of the variables in the graph, or only the variables that are needed to do reach the inputs
. Is this behavior well-defined ? Is there a way to have autograd compute the grad of everything that is not before a certain variables (for instance to implement lazy truncated BPTT in an RNN).
1 Like
only_inputs=False for torch.autograd.grad now seems to be deprecated (although it is still described as a feature in the master docs for version 0.4.0). When used it issues a warning (see torch/autograd/init.py):
“only_inputs argument is deprecated and is ignored now (defaults to True). To accumulate gradient for other parts of the graph, please use torch.autograd.backward.”