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-rw-r--r--numpy/array_api/_statistical_functions.py30
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diff --git a/numpy/array_api/_statistical_functions.py b/numpy/array_api/_statistical_functions.py
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+++ b/numpy/array_api/_statistical_functions.py
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+from __future__ import annotations
+
+from ._array_object import Array
+
+from typing import Optional, Tuple, Union
+
+import numpy as np
+
+def max(x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> Array:
+ 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:
+ return Array._new(np.asarray(np.mean(x._array, axis=axis, keepdims=keepdims)))
+
+def min(x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> Array:
+ return Array._new(np.min(x._array, axis=axis, keepdims=keepdims))
+
+def prod(x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> Array:
+ return Array._new(np.asarray(np.prod(x._array, 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 Array._new(np.asarray(np.std(x._array, axis=axis, ddof=correction, keepdims=keepdims)))
+
+def sum(x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> Array:
+ return Array._new(np.asarray(np.sum(x._array, 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 Array._new(np.asarray(np.var(x._array, axis=axis, ddof=correction, keepdims=keepdims)))