Summary:
Fixes CI regression caused by https://github.com/pytorch/pytorch/issues/61119
Unlike Python, `.ini` string lists could not end with trailing comma.
Fixes CI on master
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61333
Reviewed By: bhosmer
Differential Revision: D29578696
Pulled By: malfet
fbshipit-source-id: b81e5f4c0a553299c4d4bee0a9bb73748910795f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61119
This change spilts the clang-tidy CI job into smaller steps and uses a
refactored version of the clang_tidy.py script.
The new folder structure is as follows:
```
tools/linter/clang_tidy
|_ __main__py
|_ requirements.txt
|_ run.py
|_ setup.sh
```
`__main__.py`
This script will run `tools/linter/clang_tidy/setup.sh` if a `build`
directory doesn't exist, mimicing what used to be done as a separate
step in the CI job.
After that, it will invoke `clang-tidy` with default arguments being
declared in the script itself (as opposed to declaring them in
lint.yml).
The reasoning behind this approach is two-fold:
- Make it easier to run `clang-tidy` locally using this script
- De-duplicate the option passing
`requirements.txt`
Contains a list of additional python dependencies needed by the
`clang-tidy` script.
`setup.sh`
If a build directory doesn't exist, this command will run the necessary
codegen and build commands for running `clang-tidy`
Example usage:
```
python3 tools/linter/clang_tidy --parallel
```
Notice that we don't have to put the `.py` at the end of `clang_tidy`.
Test Plan:
Run the following command:
```
python3 tools/linter/clang_tidy --paths torch/csrc/fx --parallel
```
Reviewed By: walterddr, janeyx99
Differential Revision: D29568582
Pulled By: 1ntEgr8
fbshipit-source-id: cd6d11c5cb8ba9f1344a87c35647a1cd8dd45b04
Summary:
Changes including:
- introduced `linter/`, `testing/`, `stats/` folders in `tools/`
- move appropriate scripts into these folders
- change grepped references in the pytorch/pytorch repo
Next step
- introduce `build/` folder for build scripts
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60473
Test Plan:
- CI (this is important b/c pytorch/test-infra also rely on some script reference.
- tools/tests/
Reviewed By: albanD
Differential Revision: D29352716
Pulled By: walterddr
fbshipit-source-id: bad40b5ce130b35dfd9e59b8af34f9025f3285fd
Summary:
During development it is common practice to put `type: ignore` comments on lines that are correct, but `mypy` doesn't recognize this. This often stems from the fact, that the used `mypy` version wasn't able to handle the used pattern.
With every new release `mypy` gets better at handling complex code. In addition to fix all the previously accepted but now failing patterns, we should also revisit all `type: ignore` comments to see if they are still needed or not. Fortunately, we don't need to do it manually: by adding `warn_unused_ignores = True` to the configuration, `mypy` will error out in case it encounters an `type: ignore` that is no longer needed.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60006
Reviewed By: jbschlosser, malfet
Differential Revision: D29133237
Pulled By: albanD
fbshipit-source-id: 41e82edc5cd5affa7ccedad044b59b94dad4425a
Summary:
JUnitXml.__iadd__() is very slow
But since testsuites are flattened anyway in
`convert_junit_to_testcases` concatenate flattened tests right away
As result, parsing test-reports folder with 393 files and 25+ test cases
takes .5 sec instead of 193 sec
Fix typing errors and add script to mypy-strict
Print warning, rather than abort if xml can not be parsed
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57641
Reviewed By: samestep
Differential Revision: D28224401
Pulled By: malfet
fbshipit-source-id: 3efc079c1c0deef8fff5ddf083268885b28418f9
Summary:
Fixes https://github.com/pytorch/pytorch/issues/48141
~Mypy is complaining about a missing arg in a function call.~
```bash
torch/backends/_nnapi/serializer.py:806: error: Too few arguments for "_do_add_binary" [call-arg]
Found 1 error in 1 file (checked 1140 source files)
```
9392137dbe/torch/backends/_nnapi/serializer.py (L804-L806)
~dreiss, would you mind take a look when you have some cycles to spare and see what would be the appropriated value for `fuse_code` here? Thanks :)~
Edit: https://github.com/pytorch/pytorch/issues/48925 got merged a couple of days ago. The blocking part is now unblocked, and I just pushed the changes to make mypy happy again. This PR is ready for review.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48142
Reviewed By: ezyang
Differential Revision: D28006249
Pulled By: walterddr
fbshipit-source-id: 5e43eeba7143512a549efaad31541f86718add7c
Summary:
See https://github.com/pytorch/pytorch/pull/56523#issuecomment-823562134 for context. Basically the idea is that people (including myself) keep assuming that the single-asterisk `*` wildcard means "match in this directory and in its subdirectories", which is _not_ true. Removing the wildcards thus reduces confusion.
Ideally I would like to remove _all_ of these wildcards and then add a lint to disallow them in the future (and also greatly simplify the pattern-matching logic in `tools/mypy_wrapper.py`; see https://github.com/pytorch/pytorch/issues/55702 for context), but currently this one can't be removed:
```
tools/autograd/*.py,
```
That is because there is a file called `tools/autograd/templates/annotated_fn_args.py` (added in https://github.com/pytorch/pytorch/issues/41575) which is not a valid Python file and thus cannot be checked by `mypy`. ezyang would it be possible to rename that file to use a suffix other than `.py`?
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56645
Test Plan:
```
$ mypy
Success: no issues found in 1317 source files
$ mypy --config=mypy-strict.ini
Success: no issues found in 72 source files
```
The numbers of source files should be the same before and after this PR.
Reviewed By: ezyang
Differential Revision: D27925207
Pulled By: samestep
fbshipit-source-id: c17faf73665a75393d3109346a1138c2af023abb
Summary:
Fixes https://github.com/pytorch/pytorch/issues/54211
This was a little more annoying than expected, because the `exclude = ` key in `mypy.ini` is weird. I'll file an upstream issue about that.
I ignored one file, `torch/distributed/elastic/agent/server/api.py` that had ~8 errors that were hard to figure out. This can be done in a follow-up.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55712
Reviewed By: walterddr
Differential Revision: D27694976
Pulled By: malfet
fbshipit-source-id: 228d8be6af040343ce46595dabaca212e69ccc68
Summary:
Add option to add //NOLINTNEXTLINE for every detected violation
Series of automated huge diffs are coming after this one to make large chunks of code clang-tidy
PR generated by new option: https://github.com/pytorch/pytorch/pull/55628
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55612
Reviewed By: samestep
Differential Revision: D27649473
Pulled By: malfet
fbshipit-source-id: 251a68fcc50bf0fd69c6566293d4a516c0ab24c8
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54299
## Feature
- Check type is a subtype of another type
Prerequisite for DataPipe tying system.
Test Plan: Imported from OSS
Reviewed By: VitalyFedyunin
Differential Revision: D27327235
Pulled By: ejguan
fbshipit-source-id: 8f50a663a86540677c9e132ac7c5216fdac46f70
Summary:
This is a follow-up PR of https://github.com/pytorch/pytorch/issues/52408 and move/convert all files under `test/type_hint_tests/*.py` to use the new test style.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53167
Reviewed By: ejguan
Differential Revision: D27081041
Pulled By: walterddr
fbshipit-source-id: 56508083800a5e12a7af88d095ca26229f0df358
Summary:
This is an initial attempt in refactoring and consolidating our S3 read logic for print_test_stats.py, test_history.py, and run_test.py. This way, boto3 and botocore do not need to be imported in various places throughout the code base, and duplicated logic (such as the many type definitions) can exist in one place: `tools/stat_utils/s3_stat_parser.py`. walterddr contributed to this PR by moving print_test_stats.py to the tools folder and the corresponding tests a subfolder within tools.
**NOTE: this removes those tests from CI as the new `tools/test/test_stats.py` is not in the test/ directory as the other tests in TESTS in run_test.py.**
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53755
Test Plan:
This refactoring change should not break anything, so running the files as before should work as they did previously.
To make sure that print_test_stats.py still functions: run `python tools/test/test_stats.py` and make sure all tests pass.
To make sure that test_history.py works, run the example commands from `tools/test_history.py --help` and check that their output matches that shown. Note that the script will continue printing for a while, so don't be alarmed.
Some next steps:
- Actually coming up with similarities among the three current use cases and further refactoring/consolidating of functions (e.g., combining simplify and get_cases)
- Moving more parsing logic to s3_stat_parser.py to have better abstraction between our files
- Adding tests for s3_stat_parser.py when there is more functionality in it
Reviewed By: agolynski, samestep
Differential Revision: D27030285
Pulled By: janeyx99
fbshipit-source-id: e664781324ef7c0c30943bfd7f17c895075ef7a7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52370
After adding .pyi stubs for torch / caffe2 protos, there were some mypy false positives (https://github.com/pytorch/pytorch/pull/52341). We tell mypy to ignore the offending file here.
Test Plan: Let CI run.
Reviewed By: malfet, dzhulgakov
Differential Revision: D26490302
fbshipit-source-id: 87cdfd7419efdc7abece9ca975a464201732b7a0
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
Summary:
This is a followup to https://github.com/pytorch/pytorch/issues/49190. Vaguely speaking, the goals are to make it easy to identify test time regressions introduced by PRs. Eventually the hope is to use this information to edit Dr CI comments, but this particular PR just does the analysis and prints it to stdout, so a followup PR would be needed to edit the actual comments on GitHub.
**Important:** for uninteresting reasons, this PR moves the `print_test_stats.py` file.
- *Before:* `test/print_test_stats.py`
- *After:* `torch/testing/_internal/print_test_stats.py`
Notes on the approach:
- Just getting the mean and stdev for the total job time of the last _N_ commits isn't sufficient, because e.g. if `master` was broken 5 commits ago, then a lot of those job times will be much shorter, breaking the statistics.
- We use the commit history to make better estimates for the mean and stdev of individual test (and suite) times, but only when the test in that historical commit is present and its status matches that of the base commit.
- We list all the tests that were removed or added, or whose status changed (e.g. skipped to not skipped, or vice versa), along with time (estimate) info for that test case and its containing suite.
- We don't list tests whose time changed a lot if their status didn't change, because there's a lot of noise and it's unclear how to do that well without too many false positives.
- We show a human-readable commit graph that indicates exactly how many commits are in the pool of commits that could be causing regressions (e.g. if a PR has multiple commits in it, or if the base commit on `master` doesn't have a report in S3).
- We don't show an overall estimate of whether the PR increased or decreased the total test job time, because it's noisy and it's a bit tricky to aggregate stdevs up from individual tests to the whole job level. This might change in a followup PR.
- Instead, we simply show a summary at the bottom which says how many tests were removed/added/modified (where "modified" means that the status changed), and our best estimates of the mean times (and stdevs) of those changes.
- Importantly, the summary at the bottom is only for the test cases that were already shown in the more verbose diff report, and does not include any information about tests whose status didn't change but whose running time got much longer.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50171
Test Plan:
To run the unit tests:
```
$ python test/test_testing.py
$ python test/print_test_stats.py
```
To verify that this works, check the [CircleCI logs](https://app.circleci.com/pipelines/github/pytorch/pytorch/258628/workflows/9cfadc34-e042-485e-b3b3-dc251f160307) for a test job run on this PR; for example:
- pytorch_linux_bionic_py3_6_clang9_test
To test locally, use the following steps.
First run an arbitrary test suite (you need to have some XML reports so that `test/print_test_stats.py` runs, but we'll be ignoring them here via the `--use-json` CLI option):
```
$ DATA_DIR=/tmp
$ ARBITRARY_TEST=testing
$ python test/test_$ARBITRARY_TEST.py --save-xml=$DATA_DIR/test/test_$ARBITRARY_TEST
```
Now choose a commit and a test job (it has to be on `master` since we're going to grab the test time data from S3, and [we only upload test times to S3 on the `master`, `nightly`, and `release` branches](https://github.com/pytorch/pytorch/pull/49645)):
```
$ export CIRCLE_SHA1=c39fb9771d89632c5c3a163d3c00af3bef1bd489
$ export CIRCLE_JOB=pytorch_linux_bionic_py3_6_clang9_test
```
Download the `*.json.bz2` file(s) for that commit/job pair:
```
$ aws s3 cp s3://ossci-metrics/test_time/$CIRCLE_SHA1/$CIRCLE_JOB/ $DATA_DIR/ossci-metrics/test_time/$CIRCLE_SHA1/$CIRCLE_JOB --recursive
```
And feed everything into `test/print_test_stats.py`:
```
$ bzip2 -kdc $DATA_DIR/ossci-metrics/test_time/$CIRCLE_SHA1/$CIRCLE_JOB/*Z.json.bz2 | torch/testing/_internal/print_test_stats.py --compare-with-s3 --use-json=/dev/stdin $DATA_DIR/test/test_$ARBITRARY_TEST
```
The first part of the output should be the same as before this PR; here is the new part, at the end of the output:
- https://pastebin.com/Jj1svhAn
Reviewed By: malfet, izdeby
Differential Revision: D26317769
Pulled By: samestep
fbshipit-source-id: 1ba06cec0fafac77f9e7341d57079543052d73db
Summary:
This is a followup to https://github.com/pytorch/pytorch/issues/49190. Vaguely speaking, the goals are to make it easy to identify test time regressions introduced by PRs. Eventually the hope is to use this information to edit Dr CI comments, but this particular PR just does the analysis and prints it to stdout, so a followup PR would be needed to edit the actual comments on GitHub.
**Important:** for uninteresting reasons, this PR moves the `print_test_stats.py` file.
- *Before:* `test/print_test_stats.py`
- *After:* `torch/testing/_internal/print_test_stats.py`
Notes on the approach:
- Just getting the mean and stdev for the total job time of the last _N_ commits isn't sufficient, because e.g. if `master` was broken 5 commits ago, then a lot of those job times will be much shorter, breaking the statistics.
- We use the commit history to make better estimates for the mean and stdev of individual test (and suite) times, but only when the test in that historical commit is present and its status matches that of the base commit.
- We list all the tests that were removed or added, or whose status changed (e.g. skipped to not skipped, or vice versa), along with time (estimate) info for that test case and its containing suite.
- We don't list tests whose time changed a lot if their status didn't change, because there's a lot of noise and it's unclear how to do that well without too many false positives.
- We show a human-readable commit graph that indicates exactly how many commits are in the pool of commits that could be causing regressions (e.g. if a PR has multiple commits in it, or if the base commit on `master` doesn't have a report in S3).
- We don't show an overall estimate of whether the PR increased or decreased the total test job time, because it's noisy and it's a bit tricky to aggregate stdevs up from individual tests to the whole job level. This might change in a followup PR.
- Instead, we simply show a summary at the bottom which says how many tests were removed/added/modified (where "modified" means that the status changed), and our best estimates of the mean times (and stdevs) of those changes.
- Importantly, the summary at the bottom is only for the test cases that were already shown in the more verbose diff report, and does not include any information about tests whose status didn't change but whose running time got much longer.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50171
Test Plan:
To run the unit tests:
```
$ python test/test_testing.py
$ python test/print_test_stats.py
```
To verify that this works, check the [CircleCI logs](https://app.circleci.com/pipelines/github/pytorch/pytorch/258628/workflows/9cfadc34-e042-485e-b3b3-dc251f160307) for a test job run on this PR; for example:
- pytorch_linux_bionic_py3_6_clang9_test
To test locally, use the following steps.
First run an arbitrary test suite (you need to have some XML reports so that `test/print_test_stats.py` runs, but we'll be ignoring them here via the `--use-json` CLI option):
```
$ DATA_DIR=/tmp
$ ARBITRARY_TEST=testing
$ python test/test_$ARBITRARY_TEST.py --save-xml=$DATA_DIR/test/test_$ARBITRARY_TEST
```
Now choose a commit and a test job (it has to be on `master` since we're going to grab the test time data from S3, and [we only upload test times to S3 on the `master`, `nightly`, and `release` branches](https://github.com/pytorch/pytorch/pull/49645)):
```
$ export CIRCLE_SHA1=c39fb9771d89632c5c3a163d3c00af3bef1bd489
$ export CIRCLE_JOB=pytorch_linux_bionic_py3_6_clang9_test
```
Download the `*.json.bz2` file(s) for that commit/job pair:
```
$ aws s3 cp s3://ossci-metrics/test_time/$CIRCLE_SHA1/$CIRCLE_JOB/ $DATA_DIR/ossci-metrics/test_time/$CIRCLE_SHA1/$CIRCLE_JOB --recursive
```
And feed everything into `test/print_test_stats.py`:
```
$ bzip2 -kdc $DATA_DIR/ossci-metrics/test_time/$CIRCLE_SHA1/$CIRCLE_JOB/*Z.json.bz2 | torch/testing/_internal/print_test_stats.py --compare-with-s3 --use-json=/dev/stdin $DATA_DIR/test/test_$ARBITRARY_TEST
```
The first part of the output should be the same as before this PR; here is the new part, at the end of the output:
- https://pastebin.com/Jj1svhAn
Reviewed By: walterddr
Differential Revision: D26232345
Pulled By: samestep
fbshipit-source-id: b687b1737519d2eed68fbd591a667e4e029de509
Summary:
Closes https://github.com/pytorch/pytorch/issues/50513 by resolving all four checkboxes. If this PR is merged, I will also modify one or both of the following wiki pages to add instructions on how to use this `mypy` wrapper for VS Code editor integration:
- [Guide for adding type annotations to PyTorch](https://github.com/pytorch/pytorch/wiki/Guide-for-adding-type-annotations-to-PyTorch)
- [Lint as you type](https://github.com/pytorch/pytorch/wiki/Lint-as-you-type)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50826
Test Plan:
Unit tests for globbing function:
```
python test/test_testing.py TestMypyWrapper -v
```
Manual checks:
- Uninstall `mypy` and run `python test/test_type_hints.py` to verify that it still works when `mypy` is absent.
- Reinstall `mypy` and run `python test/test_type_hints.py` to verify that this didn't break the `TestTypeHints` suite.
- Run `python test/test_type_hints.py` again (should finish quickly) to verify that this didn't break `mypy` caching.
- Run `torch/testing/_internal/mypy_wrapper.py` on a few Python files in this repo to verify that it doesn't give any additional warnings when the `TestTypeHints` suite passes. Some examples (compare with the behavior of just running `mypy` on these files):
```sh
torch/testing/_internal/mypy_wrapper.py $PWD/README.md
torch/testing/_internal/mypy_wrapper.py $PWD/tools/fast_nvcc/fast_nvcc.py
torch/testing/_internal/mypy_wrapper.py $PWD/test/test_type_hints.py
torch/testing/_internal/mypy_wrapper.py $PWD/torch/random.py
torch/testing/_internal/mypy_wrapper.py $PWD/torch/testing/_internal/mypy_wrapper.py
```
- Remove type hints from `torch.testing._internal.mypy_wrapper` and verify that running `mypy_wrapper.py` on that file gives type errors.
- Remove the path to `mypy_wrapper.py` from the `files` setting in `mypy-strict.ini` and verify that running it again on itself no longer gives type errors.
- Add `test/test_type_hints.py` to the `files` setting in `mypy-strict.ini` and verify that running the `mypy` wrapper on it again now gives type errors.
- Change a return type in `torch/random.py` and verify that running the `mypy` wrapper on it again now gives type errors.
- Add the suggested JSON from the docstring of `torch.testing._internal.mypy_wrapper.main` to your `.vscode/settings.json` and verify that VS Code gives the same results (inline, while editing any Python file in the repo) as running the `mypy` wrapper on the command line, in all the above cases.
Reviewed By: walterddr
Differential Revision: D26049052
Pulled By: samestep
fbshipit-source-id: 0b35162fc78976452b5ea20d4ab63937b3c7695d
Summary:
Closes https://github.com/pytorch/pytorch/issues/50513 by resolving the first three checkboxes. If this PR is merged, I will also modify one or both of the following wiki pages to add instructions on how to use this `mypy` wrapper for VS Code editor integration:
- [Guide for adding type annotations to PyTorch](https://github.com/pytorch/pytorch/wiki/Guide-for-adding-type-annotations-to-PyTorch)
- [Lint as you type](https://github.com/pytorch/pytorch/wiki/Lint-as-you-type)
The test plan below is fairly manual, so let me know if I should add more automated tests to this PR.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50826
Test Plan:
Unit tests for globbing function:
```
python test/test_testing.py TestMypyWrapper -v
```
Manual checks:
- Uninstall `mypy` and run `python test/test_type_hints.py` to verify that it still works when `mypy` is absent.
- Reinstall `mypy` and run `python test/test_type_hints.py` to verify that this didn't break the `TestTypeHints` suite.
- Run `python test/test_type_hints.py` again (should finish quickly) to verify that this didn't break `mypy` caching.
- Run `torch/testing/_internal/mypy_wrapper.py` on a few Python files in this repo to verify that it doesn't give any additional warnings when the `TestTypeHints` suite passes. Some examples (compare with the behavior of just running `mypy` on these files):
```sh
torch/testing/_internal/mypy_wrapper.py README.md
torch/testing/_internal/mypy_wrapper.py tools/fast_nvcc/fast_nvcc.py
torch/testing/_internal/mypy_wrapper.py test/test_type_hints.py
torch/testing/_internal/mypy_wrapper.py torch/random.py
torch/testing/_internal/mypy_wrapper.py torch/testing/_internal/mypy_wrapper.py
```
- Remove type hints from `torch.testing._internal.mypy_wrapper` and verify that running `mypy_wrapper.py` on that file gives type errors.
- Remove the path to `mypy_wrapper.py` from the `files` setting in `mypy-strict.ini` and verify that running it again on itself no longer gives type errors.
- Add `test/test_type_hints.py` to the `files` setting in `mypy-strict.ini` and verify that running the `mypy` wrapper on it again now gives type errors.
- Remove type hints from `torch/random.py` and verify that running the `mypy` wrapper on it again now gives type errors.
- Add the suggested JSON from the docstring of `torch.testing._internal.mypy_wrapper.main` to your `.vscode/settings.json` and verify that VS Code gives the same results (inline, while editing any Python file in the repo) as running the `mypy` wrapper on the command line, in all the above cases.
Reviewed By: glaringlee, walterddr
Differential Revision: D25977352
Pulled By: samestep
fbshipit-source-id: 4b3a5e8a9071fcad65a19f193bf3dc7dc3ba1b96
Summary:
This PR helps with https://github.com/pytorch/pytorch/issues/50513 by reducing the complexity of our `mypy` test suite and making it easier to reproduce on the command line. Previously, to reproduce how `mypy` was actually run on tracked source files (ignoring the doctest typechecking) in CI, you technically needed to run 9 different commands with various arguments:
```
$ mypy --cache-dir=.mypy_cache/normal --check-untyped-defs --follow-imports silent
$ mypy --cache-dir=.mypy_cache/examples --follow-imports silent --check-untyped-defs test/type_hint_tests/module_list.py
$ mypy --cache-dir=.mypy_cache/examples --follow-imports silent --check-untyped-defs test/type_hint_tests/namedtuple.py
$ mypy --cache-dir=.mypy_cache/examples --follow-imports silent --check-untyped-defs test/type_hint_tests/opt_size.py
$ mypy --cache-dir=.mypy_cache/examples --follow-imports silent --check-untyped-defs test/type_hint_tests/size.py
$ mypy --cache-dir=.mypy_cache/examples --follow-imports silent --check-untyped-defs test/type_hint_tests/tensor_copy.py
$ mypy --cache-dir=.mypy_cache/examples --follow-imports silent --check-untyped-defs test/type_hint_tests/torch_cuda_random.py
$ mypy --cache-dir=.mypy_cache/examples --follow-imports silent --check-untyped-defs test/type_hint_tests/torch_optim.py
$ mypy --cache-dir=.mypy_cache/strict --config mypy-strict.ini
```
Now you only have to run 2 much simpler commands:
```
$ mypy
$ mypy --config mypy-strict.ini
```
One reason this is useful is because it will make it easier to integrate PyTorch's `mypy` setup into editors (remaining work on this to be done in a followup PR).
Also, as shown in the test plan, this also reduces the time it takes to run `test/test_type_hints.py` incrementally, by reducing the number of times `mypy` is invoked while still checking the same set of files with the same configs.
(Because this PR merges `test_type_hint_examples` (added in https://github.com/pytorch/pytorch/issues/34595) into `test_run_mypy` (added in https://github.com/pytorch/pytorch/issues/36584), I've added some people involved in those PRs as reviewers, in case there's a specific reason they weren't combined in the first place.)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50631
Test Plan:
Run this twice (the first time is to warm the cache):
```
$ python test/test_type_hints.py -v
```
- *Before:*
```
test_doc_examples (__main__.TestTypeHints)
Run documentation examples through mypy. ... ok
test_run_mypy (__main__.TestTypeHints)
Runs mypy over all files specified in mypy.ini ... ok
test_run_mypy_strict (__main__.TestTypeHints)
Runs mypy over all files specified in mypy-strict.ini ... ok
test_type_hint_examples (__main__.TestTypeHints)
Runs mypy over all the test examples present in ... ok
----------------------------------------------------------------------
Ran 4 tests in 5.090s
OK
```
You can also just run `mypy` to see how many files it checks:
```
$ mypy --cache-dir=.mypy_cache/normal --check-untyped-defs --follow-imports silent
Success: no issues found in 1192 source files
```
- *After:*
```
test_doc_examples (__main__.TestTypeHints)
Run documentation examples through mypy. ... ok
test_run_mypy (__main__.TestTypeHints)
Runs mypy over all files specified in mypy.ini ... ok
test_run_mypy_strict (__main__.TestTypeHints)
Runs mypy over all files specified in mypy-strict.ini ... ok
----------------------------------------------------------------------
Ran 3 tests in 2.404s
OK
```
Now `mypy` checks 7 more files, which is the number in `test/type_hint_tests`:
```
$ mypy
Success: no issues found in 1199 source files
```
Reviewed By: zou3519
Differential Revision: D25932660
Pulled By: samestep
fbshipit-source-id: 26c6f00f338e7b44954e5ed89522ce24e2fdc5f0
Summary:
Fixes https://github.com/pytorch/pytorch/issues/49034
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49035
Test Plan:
Imported from GitHub, without a `Test Plan:` line.
Force rebased to deal with merge conflicts
Reviewed By: zhangguanheng66
Differential Revision: D25767065
Pulled By: walterddr
fbshipit-source-id: ffb904e449f137825824e3f43f3775a55e9b011b
Summary:
_resubmission of gh-49654, which was reverted due to a cross-merge conflict_
This caught one incorrect annotation in `cpp_extension.load`.
xref gh-16574.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50278
Reviewed By: walterddr
Differential Revision: D25865278
Pulled By: ezyang
fbshipit-source-id: 25489191628af5cf9468136db36f5a0f72d9d54d
Summary:
Improves one annotation for `augment_model_with_bundled_inputs`
Also add a comment to not work on caffe2 type annotations, that's not worth the effort - those ignores can stay as they are.
xref gh-16574
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49658
Reviewed By: heitorschueroff
Differential Revision: D25757721
Pulled By: ezyang
fbshipit-source-id: 44c396d8da9ef3f41b97f9c46a528f0431c4b463
Summary:
Fixes https://github.com/pytorch/pytorch/issues/45215
Still need to resolve a few mypy issues before a review. In special, there is an error which I don't know how to solve, see:
```python
torch/onnx/utils.py:437: error: Name 'is_originally_training' is not defined [name-defined]
if training is None or training == TrainingMode.EVAL or (training == TrainingMode.PRESERVE and not is_originally_training):
```
`is_originally_training` is used but never defined/imported on [`torch/onnx/utils.py`](ab5cc97fb0/torch/onnx/utils.py (L437)),
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45258
Reviewed By: zhangguanheng66
Differential Revision: D25254920
Pulled By: ezyang
fbshipit-source-id: dc9dc036da43dd56b23bd6141e3ab92e1a16e3b8
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48331
Enables mypy to not ignore type errors in FX quantization files. Fixes the easy
typing errors inline, and comments out the harder errors to be fixed at a later time.
After this PR, mypy runs without errors on `torch/quantization`.
Test Plan:
```
> mypy torch/quantization/
Success: no issues found in 25 source files
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D25133348
fbshipit-source-id: 0568ef9405b292b80b3857eae300450108843e80
Summary:
Adds a standalone script which can be used to test different BLAS libraries. Right now I've deliberately kept it limited (only a couple BLAS libs and only GEMM and GEMV). It's easy enough to expand later.
CC ngimel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47058
Reviewed By: zhangguanheng66
Differential Revision: D25078946
Pulled By: robieta
fbshipit-source-id: b5f7f7ec289d59c16c5370b7a6636c10a496b3ac
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47531
This is part of a stack of PRs that fixes mypy typing errors in the torch.distributed.* directory.
Test Plan:
python test_type_hints.py -v TestTypeHints.test_run_mypy
Imported from OSS
Reviewed By: walterddr
Differential Revision: D24952499
fbshipit-source-id: b193171e28c2211a71d28a544fa44770bf938a1e
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/46780
This is in prototype status, but pretty functional. There are two major
parts.
- Model converter. This is a pure Python component that consumes a
model in TorchScript format, converts the operations into NNAPI
semantics, and serializes the model in a custom format. It then wraps
the result in a new TorchScript model that can invoke NNAPI under the
hood.
- Runtime. This is a TorchBind object that deserializes the model and
sends the result to NNAPI. This is fairly simple since the serialized
format is basically just a list of NNAPI calls to make, so most of the
code is spent on bounds checking.
A few notes on the design.
- Currently, all tensor sizes need to be fixed, and those fixed sizes
are burned directly into the serialized model. This will probably
need to change. NNAPI supports variable-sized tensors, but the
important hardware backends do not. However, we're seeing use cases
crop up where the input size is not known until around the time that
the model is loaded (for example, it might depend on the camera aspect
ratio). I think the proper fix here is to remove the code in the
converter that eagerly calculates the sizes of the intermediate
tensors and replace it with a code generator that will generate some
TorchScript code that will perform those calculations at model load
time. This way, we will be able to support models that have
variable-sized inputs while still only showing fixed-sized operands to
NNAPI.
- The important hardware backends want operands to be in NHWC order, but
PyTorch natively represents all tensors and NCHW. The strategy for
this is to keep NCHW during most of the conversion process, but track
and additional value per operand representing the "dimension order".
The dimension order gets propagated through convolutions and pointwise
ops. When we're ready to serialize the model, we reorder the
dimensions for "channels last" operands to NHWC.
Test Plan:
Some local testing with FB prod models. I'll need to add some examples
and automated tests.
Reviewed By: iseeyuan
Differential Revision: D24574040
Pulled By: dreiss
fbshipit-source-id: 6adc8571b234877ee3666ec0c0de24da35c38a1f
Summary:
Fix `torch._C._autocast_*_nesting` declarations in __init__.pyi
Fix iterable constructor logic: not every iterable can be constructed using `type(val)(val)` trick, for example it would not work for `val=range(10)` although `isinstance(val, Iterable)` is True
Change optional resolution logic to meet mypy expectations
Fixes https://github.com/pytorch/pytorch/issues/45436
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45480
Reviewed By: walterddr
Differential Revision: D23982822
Pulled By: malfet
fbshipit-source-id: 6418a28d04ece1b2427dcde4b71effb67856a872
Summary:
This is a sub-task for addressing: https://github.com/pytorch/pytorch/issues/42969. We re-enable type check for `autocast_test_lists `.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45107
Test Plan:
`python test/test_type_hints.py` passed:
```
(pytorch) bash-5.0$ with-proxy python test/test_type_hints.py
....
----------------------------------------------------------------------
Ran 4 tests in 103.871s
OK
```
Reviewed By: walterddr
Differential Revision: D23842884
Pulled By: Hangjun
fbshipit-source-id: a39f3810e3abebc6b4c1cb996b06312f6d42ffd6
Summary:
Fixes a subtask of https://github.com/pytorch/pytorch/issues/42969
Tested the following and no warnings were seen.
python test/test_type_hints.py
....
----------------------------------------------------------------------
Ran 4 tests in 180.759s
OK
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44971
Reviewed By: walterddr
Differential Revision: D23822274
Pulled By: visweshfb
fbshipit-source-id: e3485021e348ee0a8508a9d128f04bad721795ef
Summary:
Enabled type checking in common_distributed by using tensors of ints
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44821
Test Plan: Run python test/test_type_hints.py, errors are no longer ingnored by mypy.ini
Reviewed By: walterddr
Differential Revision: D23747466
Pulled By: alanadakotashine
fbshipit-source-id: 820fd502d7ff715728470fbef0be90ae7f128dd6
Summary:
To help with further typing, move dynamically added native contributions from `torch.autograd` to `torch._C._autograd`
Fix invalid error handling pattern in
89ac30afb8/torch/csrc/autograd/init.cpp (L13-L15)
`PyImport_ImportModule` already raises Python exception and nullptr should be returned to properly propagate the to Python runtime.
And all native methods/types in `torch/autograd/__init.py` after `torch._C._init_autograd()` has been called
Use f-strings instead of `.format` in test_type_hints.py
Fixes https://github.com/pytorch/pytorch/issues/44450
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44451
Reviewed By: ezyang
Differential Revision: D23618261
Pulled By: malfet
fbshipit-source-id: fa5f739d7cff8410641128b55b810318c5f636ae
