The Tensor and Variable classes are being merged.
autograd.Function.forward is now called on Variables, but with "no-grad"
mode (torch.no_grad()) enabled.
One benefit is that we no longer have to explicitly track shared
storages.
This removes volatile from Variable. The functionality is mostly
replaced by a global (thread-local) flag, which is controlled by
torch.set_grad_enabled() and the context manager torch.no_grad().
In C++, the flag is exposed through GradMode::is_enabled() and GradMode::set_enabled()
Fixes#3627
The API works on either functions or models, taking an extra parameter argument
so that functions can pass in additional variables to trace.
Other behavior is folded into boolean options:
time - collect stats for our own perf debugging
verify - run the original code, and check it is within threshold
optimize - run optimization (currently off until fusiongroups pr is accepted).
enabled - flag to turn off tracing so you can check timing of stuff that cannot be traced.
* A pile of misc doc fixes.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
* Handle @apaszke review comments.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
* Initial csrc documentation.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
We were keying hooks by RemovableHandle id. However, we don't hold onto
handles and ids of dead objects can be reused. This replaces id(handle)
with a global counter.
The core autograd Variable, Function, and Engine no longer depend on the
Python API. This let's us implement functions in C++. In the future, we
can also multithread engine and release the GIL for most of the
non-Python backwards.
Here's the command I used to invoke autopep8 (in parallel!):
git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i
Several rules are ignored in setup.cfg. The goal is to let autopep8
handle everything which it can handle safely, and to disable any rules
which are tricky or controversial to address. We may want to come back
and re-enable some of these rules later, but I'm trying to make this
patch as safe as possible.
Also configures flake8 to match pep8's behavior.
Also configures TravisCI to check the whole project for lint.
The register hook calls now return an object that can be used to remove
the hook. For example,
>>> h = module.register_forward_hook(callback)
>>> h.remove() # removes hook
Or as a context manager:
>>> with module.register_forward_hook(callback):
... pass
This makes it easier for libraries to use hooks without worrying about
name collisions.
Prior to this change, there was a circular reference between Leaf and
Variable. This means that the objects (and referenced Tensors) are not
collected as soon as they go out of scope, which lead to higher memory
usage and out-of-memory errors.
* _forward is renamed forward since users should override it
* some __call__ overrides are changed to forward
* function which return a single variable are changed to return that
variable instead of a one-element tuple
