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This is a lot of files changed! Don't panic! Here's how it works: * Previously, we set `follow_imports = silent` for our mypy.ini configuration. Per https://mypy.readthedocs.io/en/stable/running_mypy.html#follow-imports, what this does is whenever we have an import to a module which is not listed as a file to be typechecked in mypy, we typecheck it as normal but suppress all errors that occurred in that file. * When mypy is run inside lintrunner, the list of files is precisely the files covered by the glob in lintrunner.toml, but with files in excludes excluded. * The top-level directive `# mypy: ignore-errors` instructs mypy to typecheck the file as normal, but ignore all errors. * Therefore, it should be equivalent to set `follow_imports = normal`, if we put `# mypy: ignore-errors` on all files that were previously excluded from the file list. * Having done this, we can remove the exclude list from .lintrunner.toml, since excluding a file from typechecking is baked into the files themselves. * torch/_dynamo and torch/_inductor were previously in the exclude list, because they were covered by MYPYINDUCTOR. It is not OK to mark these as `# mypy: ignore-errors` as this will impede typechecking on the alternate configuration. So they are temporarily being checked twice, but I am suppressing the errors in these files as the configurations are not quite the same. I plan to unify the configurations so this is only a temporary state. * There were some straggler type errors after these changes somehow, so I fixed them as needed. There weren't that many. In the future, to start type checking a file, just remove the ignore-errors directive from the top of the file. The codemod was done with this script authored by GPT-4: ``` import glob exclude_patterns = [ ... ] for pattern in exclude_patterns: for filepath in glob.glob(pattern, recursive=True): if filepath.endswith('.py'): with open(filepath, 'r+') as f: content = f.read() f.seek(0, 0) f.write('# mypy: ignore-errors\n\n' + content) ``` Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/118414 Approved by: https://github.com/thiagocrepaldi, https://github.com/albanD
76 lines
2.0 KiB
Python
76 lines
2.0 KiB
Python
# mypy: ignore-errors
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import inspect
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import itertools
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from . import _funcs_impl, _reductions_impl
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from ._normalizations import normalizer
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# _funcs_impl.py contains functions which mimic NumPy's eponymous equivalents,
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# and consume/return PyTorch tensors/dtypes.
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# They are also type annotated.
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# Pull these functions from _funcs_impl and decorate them with @normalizer, which
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# - Converts any input `np.ndarray`, `torch._numpy.ndarray`, list of lists, Python scalars, etc into a `torch.Tensor`.
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# - Maps NumPy dtypes to PyTorch dtypes
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# - If the input to the `axis` kwarg is an ndarray, it maps it into a tuple
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# - Implements the semantics for the `out=` arg
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# - Wraps back the outputs into `torch._numpy.ndarrays`
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def _public_functions(mod):
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def is_public_function(f):
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return inspect.isfunction(f) and not f.__name__.startswith("_")
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return inspect.getmembers(mod, is_public_function)
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# We fill in __all__ in the loop below
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__all__ = []
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# decorate implementer functions with argument normalizers and export to the top namespace
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for name, func in itertools.chain(
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_public_functions(_funcs_impl), _public_functions(_reductions_impl)
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):
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if name in ["percentile", "quantile", "median"]:
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decorated = normalizer(func, promote_scalar_result=True)
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elif name == "einsum":
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# normalized manually
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decorated = func
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else:
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decorated = normalizer(func)
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decorated.__qualname__ = name
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decorated.__name__ = name
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vars()[name] = decorated
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__all__.append(name)
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"""
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Vendored objects from numpy.lib.index_tricks
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"""
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class IndexExpression:
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"""
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Written by Konrad Hinsen <hinsen@cnrs-orleans.fr>
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last revision: 1999-7-23
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Cosmetic changes by T. Oliphant 2001
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"""
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def __init__(self, maketuple):
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self.maketuple = maketuple
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def __getitem__(self, item):
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if self.maketuple and not isinstance(item, tuple):
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return (item,)
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else:
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return item
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index_exp = IndexExpression(maketuple=True)
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s_ = IndexExpression(maketuple=False)
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__all__ += ["index_exp", "s_"]
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