Hello,
I’m a little confused on what the grad_fn property of a tensor actually means.
I have a tensor that before I take the mean of it has
grad_fn = <StackBackward>

after I take the mean of it, this becomes
grad_fn = <MeanBackward0>

It’s just not clear to me what this actually means for my network.  The tensor in question is my loss, which immediately afterwards I have
loss.backward()

And I’m just looking for clarification on what this changing grad_fn means for my loss function and the backward function here.
Thanks!