\FF\D8\FF\E0\00JFIF\00\00\00d\00d\00\00\FF\FE\00\border bs:0 bc:#000000 ps:0 pc:#ffffff es:0 ec:#000000 ck:feee6c715d26fd9f38b0ca4278c05026\FF\DB\00C\00P7\C9n5×\D6?\BDê\9Ds\EBp\9F[`8m\B7)o\B5\E8\E6I\99\FE3]]A2\BA\8Cw\D6E\93\\DEv\C8\009\F2\F1NI?uc\\F5\EA\96k\xN<~buv\EA\C8\D7 \8B\84\CEcxI\BBg\AE\9E=\D6+n\EC\80\C8A\8C\AE\EB\CF\D5\DA\E9"2\A4\B9j5\EB\F3W\B63\96\B30Yu\DA\FC8\ED\DF\E7Ms\FB\F1\8E\B3\FA\EA\E8\E6(\883zs\F2_\8DFk\8Bh \00\8C\DCw\D3R\B5+6X\BA\B2\C4j\AB0\B4\FCMw\C2I\8E\9B\E3\A9~9u\FA\D3l\80\C8%p\EE\FDn2€ \00 $\FEj\C4e\A9\DB\~\95\A7\A5\80EK\BB\8DDsP\00@@AD'k\CF\E8\DB\D2(\80\9AK\D3\85\D6lb\F2\BA\8C*\80\00)\95 59\A3R:\F3\CE"\B6\80\88\00\00i1u4ê\E9\F2á\A6\A2\FACM\93WMb*\E0*\00\00\00\00\00(\A8\80\00\00\80\00\00\00\00\00\00\00\00\00\FF\D9 C/// from __future__ import annotations from ._dtypes import ( _real_floating_dtypes, _real_numeric_dtypes, _numeric_dtypes, ) from ._array_object import Array from ._dtypes import float32, float64, complex64, complex128 from typing import TYPE_CHECKING, Optional, Tuple, Union if TYPE_CHECKING: from ._typing import Dtype import numpy as np def max( x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False, ) -> Array: if x.dtype not in _real_numeric_dtypes: raise TypeError("Only real numeric dtypes are allowed in max") return Array._new(np.max(x._array, axis=axis, keepdims=keepdims)) def mean( x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False, ) -> Array: if x.dtype not in _real_floating_dtypes: raise TypeError("Only real floating-point dtypes are allowed in mean") return Array._new(np.mean(x._array, axis=axis, keepdims=keepdims)) def min( x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False, ) -> Array: if x.dtype not in _real_numeric_dtypes: raise TypeError("Only real numeric dtypes are allowed in min") return Array._new(np.min(x._array, axis=axis, keepdims=keepdims)) def prod( x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, dtype: Optional[Dtype] = None, keepdims: bool = False, ) -> Array: if x.dtype not in _numeric_dtypes: raise TypeError("Only numeric dtypes are allowed in prod") # Note: sum() and prod() always upcast for dtype=None. `np.prod` does that # for integers, but not for float32 or complex64, so we need to # special-case it here if dtype is None: if x.dtype == fl