8000 Follow our own guidelines of 'everything thats works at a PyTorch lev… · pytorch/pytorch@bc9add5 · GitHub
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Follow our own guidelines of 'everything thats works at a PyTorch level ends in _impl'
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‎torch/_numpy/_funcs.py‎

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@@ -1,7 +1,7 @@
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import inspect
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import itertools
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from . import _funcs_impl, _reductions
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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,
@@ -27,7 +27,7 @@ def is_public_function(f):
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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)
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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)

torch/_numpy/_reductions.py renamed to torch/_numpy/_reductions_impl.py

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