This PR re-lands
- [Typing] Fix PEP 484 Violation (#105022)
- Update mypy to 1.4.1 (#91983)
That were reverted due to the conflict with internal source repo.
Mostly fixes for PEP-484 violation (i.e. when default arg is set to None, but type is not annotated as optional)
Plus few real fixes:
- Add missing `_get_upgraders_entry_map` to `torch/_C/__init__.pyi`
- Add missing return statement to `torch._export. deserialize_graph`
- Fix error message in `torch.ao.ns.fx.weight_utils.get_lstm_mod_weights`
- Add assert it `torch/optim/optimizer.py` that Optional list is not None
TODO (in followup PR):
- Fix erroneous `isinstance` check in `torch/ao/quantization/_pt2e/qat_utils.py`
Unrelated, to bypass CI failures due to the gcc9 dependency update in Ubuntu-18.04:
- Add hack to squash older libstdc++ from conda environment in favor one from OS to `.ci/docker/install_conda.sh`
- Update bazel cuda builds to focal, as with libstdc++-6.0.32 bazel builds loose the ability to catch exceptions (probably because they link with cupti statically, but I could not found where it is done)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/105227
Approved by: https://github.com/atalman, https://github.com/albanD, https://github.com/Skylion007
This PR re-lands
- [Typing] Fix PEP 484 Violation (#105022)
- Update mypy to 1.4.1 (#91983)
That were reverted due to the conflict with internal source repo.
Mostly fixes for PEP-484 violation (i.e. when default arg is set to None, but type is not annotated as optional)
Plus few real fixes:
- Add missing `_get_upgraders_entry_map` to `torch/_C/__init__.pyi`
- Add missing return statement to `torch._export. deserialize_graph`
- Fix error message in `torch.ao.ns.fx.weight_utils.get_lstm_mod_weights`
- Add assert it `torch/optim/optimizer.py` that Optional list is not None
TODO (in followup PR):
- Fix erroneous `isinstance` check in `torch/ao/quantization/_pt2e/qat_utils.py`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/105227
Approved by: https://github.com/atalman, https://github.com/albanD, https://github.com/Skylion007
Summary:
X-link: https://github.com/pytorch/data/pull/368
This is PR aims to expose the right data-relate API.
There are two more changes made in this PR to convert public api to private api
`check_lambda_fn` -> `_check_lambda_fn`
`deprecation_warning` -> `_deprecation_warning`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76143
Reviewed By: albanD, NivekT
Differential Revision: D35798311
Pulled By: ejguan
fbshipit-source-id: b13fded5c88a533c706702fb2070c918c839dca4
(cherry picked from commit 0b534b829a2e90e1e533951c6d334fdeaa9358b9)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73396
Separating DataPipes from Dataset into different files. This makes the code more maintainable and simplifies some of the code generation.
I have also tried to move `datapipe.py` into `torch.utils.data.datapipes`, but that will lead to circular import and rewriting many import statements. Should I put more time and go down that path some more?
Fixes https://github.com/pytorch/data/issues/213
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D34481962
Pulled By: NivekT
fbshipit-source-id: 42fb26fe7fc334636852cfd8719fc807bdaa7912
(cherry picked from commit 81e76a64e297cb5c58caa951c554e49526173936)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70249
IMO, the `unbatch_level` argument is not needed here since users can simply can `.unbatch` before calling `.groupby` if needed. One small step closer to an unified API with other libraries.
Note that we may rename the functional name from `.groupby` to `.group` in the future. TBD.
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D33259104
Pulled By: NivekT
fbshipit-source-id: 490e3b6f5927f9ebe8772d5a5e4fbabe9665dfdf
