Type checking Python is a pain. Here are my learnings:
* The types for heavily polymorphic code is going to be verbose, no way around it. I originally was hoping I could lean on polymorphism with a bounded TypeVar to compactly write signatures for many of the ValueRanges methods, but I ran into some unworkaroundable mypy bugs. Writing out all the types explicitly and using `@overload` liberally works pretty well, so I think I recommend people do that instead of trying to do fancy things.
* Sympy is missing annotations for assumptions, because they are all metaprogrammed. I don't really relish maintaining a typeshed for sympy, so I wrote a small mypy plugin to add them in.
* GADT style refinement is... just not a good idea in practice. Mypy easily gets confused whether or not a return value from a refined section is allowed for the outer return type. So many of these have been replaced with less informative implementation types and more informative external types via overloads. Hopefully this is good for use sites.
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/118870
Approved by: https://github.com/Skylion007, https://github.com/albanD
Summary:
This PR moves the Dockerfile conda dependencies into a requirements-ci.txt (and begins the requirements file for other parts of CI as well). Packages are listed alphabetically in the requirements-ci.txt. Uncommented packages before the mkl package have been tested and confirmed to work on all platforms. Commented out packages before mkl have broken at least one platform and so have been comment out. There appears to be some randomness with certain platforms not passing tests so it might be good to run a number of tests for the same configuration to confirm if it is indeed these commented out packages that cause the errors.
Remaining is to test all commented out packages to ensure they work on all platforms. This will likely involve repeat runs of the same configurations to ensure it is indeed the packages that break the platforms and not random errors.
This PR makes progress on task https://github.com/pytorch/pytorch/issues/72556
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73404
Reviewed By: janeyx99
Differential Revision: D34730797
Pulled By: kstant0725
fbshipit-source-id: 3e4b171720fa33b604cebb9c6101d38ba11f2f8b
(cherry picked from commit 99cc445aadb95f92f6ef040f2d4b7c6c6d5b7f8b)
Summary:
This PR adds a local [`mypy` plugin](https://mypy.readthedocs.io/en/stable/extending_mypy.html#extending-mypy-using-plugins) that warns if you accidentally run `mypy` using a version that doesn't match [the version we install for CI](6045663f39/.circleci/docker/common/install_conda.sh (L117)), since this trips people up sometimes when `mypy` gives errors in some versions (see https://github.com/pytorch/pytorch/issues/51513) but not others.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51799
Test Plan:
To check that this doesn't break our `mypy` test(s) when you have the correct version installed:
```
python test/test_type_hints.py
```
To check that this does indeed warn when you have an incorrect `mypy` version installed, switch to a different version (e.g. 0.782), and run the above command or either of these:
```
mypy
mypy --config-file=mypy-strict.ini
```
You should get the following message on stderr:
```
You are using mypy version 0.782, which is not supported
in the PyTorch repo. Please switch to mypy version 0.770.
For example, if you installed mypy via pip, run this:
pip install mypy==0.770
Or if you installed mypy via conda, run this:
conda install -c conda-forge mypy=0.770
```
Reviewed By: janeyx99
Differential Revision: D26282010
Pulled By: samestep
fbshipit-source-id: 7b423020d0529700dea8972b27afa2d7068e1b12
