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from __future__ import annotations
from ..common import _aliases
from .._internal import get_xp
from ._info import __array_namespace_info__
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from typing import Optional, Union
from ._typing import ndarray, Device, Dtype, NestedSequence, SupportsBufferProtocol
import numpy as np
bool = np.bool_
# Basic renames
acos = np.arccos
acosh = np.arccosh
asin = np.arcsin
asinh = np.arcsinh
atan = np.arctan
atan2 = np.arctan2
atanh = np.arctanh
bitwise_left_shift = np.left_shift
bitwise_invert = np.invert
bitwise_right_shift = np.right_shift
concat = np.concatenate
pow = np.power
arange = get_xp(np)(_aliases.arange)
empty = get_xp(np)(_aliases.empty)
empty_like = get_xp(np)(_aliases.empty_like)
eye = get_xp(np)(_aliases.eye)
full = get_xp(np)(_aliases.full)
full_like = get_xp(np)(_aliases.full_like)
linspace = get_xp(np)(_aliases.linspace)
ones = get_xp(np)(_aliases.ones)
ones_like = get_xp(np)(_aliases.ones_like)
zeros = get_xp(np)(_aliases.zeros)
zeros_like = get_xp(np)(_aliases.zeros_like)
UniqueAllResult = get_xp(np)(_aliases.UniqueAllResult)
UniqueCountsResult = get_xp(np)(_aliases.UniqueCountsResult)
UniqueInverseResult = get_xp(np)(_aliases.UniqueInverseResult)
unique_all = get_xp(np)(_aliases.unique_all)
unique_counts = get_xp(np)(_aliases.unique_counts)
unique_inverse = get_xp(np)(_aliases.unique_inverse)
unique_values = get_xp(np)(_aliases.unique_values)
std = get_xp(np)(_aliases.std)
var = get_xp(np)(_aliases.var)
cumulative_sum = get_xp(np)(_aliases.cumulative_sum)
cumulative_prod = get_xp(np)(_aliases.cumulative_prod)
clip = get_xp(np)(_aliases.clip)
permute_dims = get_xp(np)(_aliases.permute_dims)
reshape = get_xp(np)(_aliases.reshape)
argsort = get_xp(np)(_aliases.argsort)
sort = get_xp(np)(_aliases.sort)
nonzero = get_xp(np)(_aliases.nonzero)
ceil = get_xp(np)(_aliases.ceil)
floor = get_xp(np)(_aliases.floor)
trunc = get_xp(np)(_aliases.trunc)
matmul = get_xp(np)(_aliases.matmul)
matrix_transpose = get_xp(np)(_aliases.matrix_transpose)
tensordot = get_xp(np)(_aliases.tensordot)
sign = get_xp(np)(_aliases.sign)
def _supports_buffer_protocol(obj):
try:
memoryview(obj)
except TypeError:
return False
return True
# asarray also adds the copy keyword, which is not present in numpy 1.0.
# asarray() is different enough between numpy, cupy, and dask, the logic
# complicated enough that it's easier to define it separately for each module
# rather than trying to combine everything into one function in common/
def asarray(
obj: Union[
ndarray,
bool,
int,
float,
NestedSequence[bool | int | float],
SupportsBufferProtocol,
],
/,
*,
dtype: Optional[Dtype] = None,
device: Optional[Device] = None,
copy: "Optional[Union[bool, np._CopyMode]]" = None,
**kwargs,
) -> ndarray:
"""
Array API compatibility wrapper for asarray().
See the corresponding documentation in the array library and/or the array API
specification for more details.
"""
if device not in ["cpu", None]:
raise ValueError(f"Unsupported device for NumPy: {device!r}")
if hasattr(np, '_CopyMode'):
if copy is None:
copy = np._CopyMode.IF_NEEDED
elif copy is False:
copy = np._CopyMode.NEVER
elif copy is True:
copy = np._CopyMode.ALWAYS
else:
# Not present in older NumPys. In this case, we cannot really support
# copy=False.
if copy is False:
raise NotImplementedError("asarray(copy=False) requires a newer version of NumPy.")
return np.array(obj, copy=copy, dtype=dtype, **kwargs)
def astype(
x: ndarray,
dtype: Dtype,
/,
*,
copy: bool = True,
device: Optional[Device] = None,
) -> ndarray:
return x.astype(dtype=dtype, copy=copy)
# count_nonzero returns a python int for axis=None and keepdims=False
# https://github.com/numpy/numpy/issues/17562
def count_nonzero(
x : ndarray,
axis=None,
keepdims=False
) -> ndarray:
result = np.count_nonzero(x, axis=axis, keepdims=keepdims)
if axis is None and not keepdims:
return np.asarray(result)
return result
# These functions are completely new here. If the library already has them
# (i.e., numpy 2.0), use the library version instead of our wrapper.
if hasattr(np, 'vecdot'):
vecdot = np.vecdot
else:
vecdot = get_xp(np)(_aliases.vecdot)
if hasattr(np, 'isdtype'):
isdtype = np.isdtype
else:
isdtype = get_xp(np)(_aliases.isdtype)
if hasattr(np, 'unstack'):
unstack = np.unstack
else:
unstack = get_xp(np)(_aliases.unstack)
__all__ = _aliases.__all__ + ['__array_namespace_info__', 'asarray', 'astype',
'acos', 'acosh', 'asin', 'asinh', 'atan',
'atan2', 'atanh', 'bitwise_left_shift',
'bitwise_invert', 'bitwise_right_shift',
'bool', 'concat', 'count_nonzero', 'pow']
_all_ignore = ['np', 'get_xp']
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