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| # mypy: ignore-errors | |
| import inspect | |
| import itertools | |
| from . import _funcs_impl, _reductions_impl | |
| from ._normalizations import normalizer | |
| # _funcs_impl.py contains functions which mimic NumPy's eponymous equivalents, | |
| # and consume/return PyTorch tensors/dtypes. | |
| # They are also type annotated. | |
| # Pull these functions from _funcs_impl and decorate them with @normalizer, which | |
| # - Converts any input `np.ndarray`, `torch._numpy.ndarray`, list of lists, Python scalars, etc into a `torch.Tensor`. | |
| # - Maps NumPy dtypes to PyTorch dtypes | |
| # - If the input to the `axis` kwarg is an ndarray, it maps it into a tuple | |
| # - Implements the semantics for the `out=` arg | |
| # - Wraps back the outputs into `torch._numpy.ndarrays` | |
| def _public_functions(mod): | |
| def is_public_function(f): | |
| return inspect.isfunction(f) and not f.__name__.startswith("_") | |
| return inspect.getmembers(mod, is_public_function) | |
| # We fill in __all__ in the loop below | |
| __all__ = [] | |
| # decorate implementer functions with argument normalizers and export to the top namespace | |
| for name, func in itertools.chain( | |
| _public_functions(_funcs_impl), _public_functions(_reductions_impl) | |
| ): | |
| if name in ["percentile", "quantile", "median"]: | |
| decorated = normalizer(func, promote_scalar_result=True) | |
| elif name == "einsum": | |
| # normalized manually | |
| decorated = func | |
| else: | |
| decorated = normalizer(func) | |
| decorated.__qualname__ = name | |
| decorated.__name__ = name | |
| vars()[name] = decorated | |
| __all__.append(name) | |
| """ | |
| Vendored objects from numpy.lib.index_tricks | |
| """ | |
| class IndexExpression: | |
| """ | |
| Written by Konrad Hinsen <[email protected]> | |
| last revision: 1999-7-23 | |
| Cosmetic changes by T. Oliphant 2001 | |
| """ | |
| def __init__(self, maketuple): | |
| self.maketuple = maketuple | |
| def __getitem__(self, item): | |
| if self.maketuple and not isinstance(item, tuple): | |
| return (item,) | |
| else: | |
| return item | |
| index_exp = IndexExpression(maketuple=True) | |
| s_ = IndexExpression(maketuple=False) | |
| __all__ += ["index_exp", "s_"] | |