Merge Tensor and Variable types. (#28287)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/28287
This PR eliminates the static distinction between
Tensor and Variable. Every Variable is a Tensor, no need to static_cast
or call the Variable constructor.
To do this, I need Tensor to have API parity with Variable. I have already
moved most of the methods I don't want in Tensor off Variable.
These implementations are all placed in Tensor.cpp.
One API difference is that all Variable methods now have const, so we no longer
have faux const-correctness (see https://github.com/zdevito/ATen/issues/27 for
back story)
This diff is BC breaking in a few ways:
- Because torch::autograd::Variable is now just an alias of at::Tensor, ADL for
`torch::autograd` functions no longer works, you have to explicitly qualify
them with `torch::autograd` (examples: `torch/nn/parallel/data_parallel.h`)
- Because Variable and Tensor are now the same type, code which assumes that
they are different types (e.g., for the purposes of templating, or enable_if checks)
will not work until you delete the (now) redundant overload/specialization.
(examples: `torch/nn/modules/container/any.h`, `torch/csrc/utils/pybind.h`)
Some other notes:
- I'm not sure what was going with the old template implementation of `extract_vars`,
but I couldn't get the sfinae version to work. Replacing it with an overloading based version
made it work.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Differential Revision: D18571426
Pulled By: ezyang
fbshipit-source-id: 2ea8151e5f1d8512cdebf1345399642e68b707b8
