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from __future__ import annotations
from ._types import Tuple, array
import numpy as np
def argmax(x: array, /, *, axis: int = None, keepdims: bool = False) -> array:
"""
Array API compatible wrapper for :py:func:`np.argmax <numpy.argmax>`.
See its docstring for more information.
"""
# Note: this currently fails as np.argmax does not implement keepdims
return np.asarray(np.argmax._implementation(x, axis=axis, keepdims=keepdims))
def argmin(x: array, /, *, axis: int = None, keepdims: bool = False) -> array:
"""
Array API compatible wrapper for :py:func:`np.argmin <numpy.argmin>`.
See its docstring for more information.
"""
# Note: this currently fails as np.argmin does not implement keepdims
return np.asarray(np.argmin._implementation(x, axis=axis, keepdims=keepdims))
def nonzero(x: array, /) -> Tuple[array, ...]:
"""
Array API compatible wrapper for :py:func:`np.nonzero <numpy.nonzero>`.
See its docstring for more information.
"""
return np.nonzero._implementation(x)
def where(condition: array, x1: array, x2: array, /) -> array:
"""
Array API compatible wrapper for :py:func:`np.where <numpy.where>`.
See its docstring for more information.
"""
return np.where._implementation(condition, x1, x2)
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