Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53424
Fixes https://github.com/pytorch/pytorch/issues/24807 and supersedes the stale https://github.com/pytorch/pytorch/issues/25093 (Cc Microsheep). If you now run the reproduction
```python
import torch
if __name__ == "__main__":
t = torch.tensor([1, 2, 3], dtype=torch.float64)
```
with `pylint==2.6.0`, you get the following output
```
test_pylint.py:1:0: C0114: Missing module docstring (missing-module-docstring)
test_pylint.py:4:8: E1101: Module 'torch' has no 'tensor' member; maybe 'Tensor'? (no-
member)
test_pylint.py:4:38: E1101: Module 'torch' has no 'float64' member (no-member)
```
Now `pylint` doesn't recognize `torch.tensor` at all, but it is promoted in the stub. Given that it also doesn't recognize `torch.float64`, I think fixing this is out of scope of this PR.
---
## TL;DR
This BC-breaking only for users that rely on unintended behavior. Since `torch/__init__.py` loaded `torch/tensor.py` it was populated in `sys.modules`. `torch/__init__.py` then overwrote `torch.tensor` with the actual function. With this `import torch.tensor as tensor` does not fail, but returns the function rather than the module. Users that rely on this import need to change it to `from torch import tensor`.
Reviewed By: zou3519
Differential Revision: D26223815
Pulled By: bdhirsh
fbshipit-source-id: 125b9ff3d276e84a645cd7521e8d6160b1ca1c21
Summary:
# What's this
Just a small bug fix related to typing stubs.
I haven't open an issue. I will do so if I must open it, but this PR is very small (only 6 lines diff).
## What I encountered
pytorch 1.5.0 with mypy 0.770 behaves odd. The code is following:
```python
import torch
def f() -> int: # Mypy says: `error: Missing return statement`
with torch.no_grad():
return 1
```
No mypy error is expected, but actually mypy 0.770 warns about `Missing return statement`.
## This is because
`mypy >= 0.730` with `--warn-unreachable` says it's unreachable because `torch.no_grad()` may "swallows" the error in the return statement.
http://mypy-lang.blogspot.com/2019/09/mypy-730-released.html
Here is a small "swallowing" example:
```python
from typing import Generator
from contextlib import contextmanager
contextmanager
def swallow_zerodiv() -> Generator[None, None, None]:
try:
yield None
except ZeroDivisionError:
pass
finally:
pass
def div(a: int, b: int) -> float: # This function seems `(int, int) -> float` but actually `(int, int) -> Optional[float]` because ` return a / b` may be swallowed
with swallow_zerodiv():
return a / b
if __name__ == '__main__':
result = div(1, 0)
print(result, type(result)) # None <class 'NoneType'>
```
To supress this behavior, one can tell mypy not to swallow any exceptions, with returning `Literal[False]` or `None` in `__exit__` method of the context manager.
# What I did
Return `None` instead of `bool` to tell mypy that "I never swallow your exception".
I chose `None` because I cannot interpret `Literal[False]` without typing_extensions in `python <=3.7`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/39324
Differential Revision: D21833651
Pulled By: albanD
fbshipit-source-id: d5cad2e5e19068bd68dc773e997bf13f7e60f4de
Summary:
These warning's goal is to show the user where to be careful in their code. So make them point to the user's code.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/39143
Differential Revision: D21764201
Pulled By: albanD
fbshipit-source-id: f1369d1b0e71d93af892ad3b7b1b3030e6699c59
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38080
Originally, my plan was to just delete the torch.autograd stub, but
this triggered a bunch of downstream errors relating to non-existent
to _C modules, and so instead of ignoring those files, I decided to
add a minimal _C type stubs, where it was easy (cases which were
codegened I ignored).
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Differential Revision: D21487841
Pulled By: ezyang
fbshipit-source-id: cfcc467ff1c146d242cb9ff33a46ba26b33b8213
