From 1efd55efa8cac9afd12d299dcf8912a7a7ac8a68 Mon Sep 17 00:00:00 2001 From: Aaron Meurer Date: Wed, 20 Jan 2021 18:25:20 -0700 Subject: Use _implementation on all functions that have it in the array API submodule That way they only work on actual ndarray inputs, not array-like, which is more inline with the spec. --- numpy/_array_api/_statistical_functions.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) (limited to 'numpy/_array_api/_statistical_functions.py') diff --git a/numpy/_array_api/_statistical_functions.py b/numpy/_array_api/_statistical_functions.py index e62410d01..79bc125dc 100644 --- a/numpy/_array_api/_statistical_functions.py +++ b/numpy/_array_api/_statistical_functions.py @@ -5,24 +5,24 @@ from ._types import Optional, Tuple, Union, array import numpy as np def max(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: - return np.max(x, axis=axis, keepdims=keepdims) + return np.max._implementation(x, axis=axis, keepdims=keepdims) def mean(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: - return np.asarray(np.mean(x, axis=axis, keepdims=keepdims)) + return np.asarray(np.mean._implementation(x, axis=axis, keepdims=keepdims)) def min(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: - return np.min(x, axis=axis, keepdims=keepdims) + return np.min._implementation(x, axis=axis, keepdims=keepdims) def prod(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: - return np.asarray(np.prod(x, axis=axis, keepdims=keepdims)) + return np.asarray(np.prod._implementation(x, axis=axis, keepdims=keepdims)) def std(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, correction: Union[int, float] = 0.0, keepdims: bool = False) -> array: # Note: the keyword argument correction is different here - return np.asarray(np.std(x, axis=axis, ddof=correction, keepdims=keepdims)) + return np.asarray(np.std._implementation(x, axis=axis, ddof=correction, keepdims=keepdims)) def sum(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: - return np.asarray(np.sum(x, axis=axis, keepdims=keepdims)) + return np.asarray(np.sum._implementation(x, axis=axis, keepdims=keepdims)) def var(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, correction: Union[int, float] = 0.0, keepdims: bool = False) -> array: # Note: the keyword argument correction is different here - return np.asarray(np.var(x, axis=axis, ddof=correction, keepdims=keepdims)) + return np.asarray(np.var._implementation(x, axis=axis, ddof=correction, keepdims=keepdims)) -- cgit v1.2.1