Hi Peter!



 ptrblck:

In 0.3 you would use Variable(torch.tensor(...), volatile=True) to avoid creating the computation graph.
Let me know, if that works for you.


Thank you for your reply.
To clarify in my concrete case:
The output of running the forward pass, for training, of my model
is a torch.autograd.variable.Variable.  Should I retrieve its
FloatTensor by using its data property, wrap that tensor in a
volatile Variable, a la:
torch.autograd.variable.Variable (preds.data, volatile = True)

and then use this volatile Variable for any additional calculations?
Thanks.
K. Frank