Not only is this change usually shorter and more readable, it also can yield better performance. size() is not always a constant time operation (such as on LinkedLists), but empty() always is.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/93236
Approved by: https://github.com/malfet
As we live in C++17 world
This is a functional no-op, just
- `s/namespace at { namespace native {/namespace at::native {/`
- `s/namespace torch { namespace jit {/namespace torch::jit {/`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/92100
Approved by: https://github.com/izaitsevfb
We define specializations for pybind11 defined templates
(in particular, PYBIND11_DECLARE_HOLDER_TYPE) and consequently
it is important that these specializations *always* be #include'd
when making use of pybind11 templates whose behavior depends on
these specializations, otherwise we can cause an ODR violation.
The easiest way to ensure that all the specializations are always
loaded is to designate a header (in this case, torch/csrc/util/pybind.h)
that ensures the specializations are defined, and then add a lint
to ensure this header is included whenever pybind11 headers are
included.
The existing grep linter didn't have enough knobs to do this
conveniently, so I added some features. I'm open to suggestions
for how to structure the features better. The main changes:
- Added an --allowlist-pattern flag, which turns off the grep lint
if some other line exists. This is used to stop the grep
lint from complaining about pybind11 includes if the util
include already exists.
- Added --match-first-only flag, which lets grep only match against
the first matching line. This is because, even if there are multiple
includes that are problematic, I only need to fix one of them.
We don't /really/ need this, but when I was running lintrunner -a
to fixup the preexisting codebase it was annoying without this,
as the lintrunner overall driver fails if there are multiple edits
on the same file.
I excluded any files that didn't otherwise have a dependency on
torch/ATen, this was mostly caffe2 and the valgrind wrapper compat
bindings.
Note the grep replacement is kind of crappy, but clang-tidy lint
cleaned it up in most cases.
See also https://github.com/pybind/pybind11/issues/4099
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82552
Approved by: https://github.com/albanD
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52659
**Summary**
This commit adds `torch._C.ScriptDict`, a dictionary type that has reference
semantics across the Python/TorchScript boundary. That is, modifications
made to instances of `torch._C.ScriptDict` in TorchScript are visible in
Python even when it is not returned from the function. Instances can be
constructed by passing an instance of a Python dictionary to
`torch.jit.script`. In the case of an empty dictionary, its type is
assumed to be `Dict[str, Tensor]` to be consistent with the handling of
empty dictionaries in TorchScript source code.
`torch._C.ScriptDict` is implemented using a modified version of pybind's `stl_bind.h`-style bindings attached to `ScriptDict`, `ScriptDictIterator` and `ScriptDictKeyIterator`, wrapper classes around `c10::impl::GenericDict` and `c10::impl::GenericDict::iterator`. These bindings allow instances of `torch._C.ScriptDict` to be used as if it were a regular `dict` Python. Reference semantics are achieved by simply retrieving the `IValue` contained in `ScriptDict` in `toIValue` (invoked when converting Python arguments to `IValues` before calling TorchScript code).
**Test Plan**
This commit adds `TestScriptDict` to `test_list_dict.py`, a set of tests
that check that all of the common dictionary operations are supported
and that instances have reference semantics across the
Python/TorchScript boundary.
Differential Revision:
D27211605
D27211605
Test Plan: Imported from OSS
Reviewed By: gmagogsfm
Pulled By: SplitInfinity
fbshipit-source-id: 446d4e5328375791aa73eb9e8b04dfe3465af960
