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from __future__ import annotations
import cupy as cp
from ..common import _aliases, _helpers
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
bool = cp.bool_
# Basic renames
acos = cp.arccos
acosh = cp.arccosh
asin = cp.arcsin
asinh = cp.arcsinh
atan = cp.arctan
atan2 = cp.arctan2
atanh = cp.arctanh
bitwise_left_shift = cp.left_shift
bitwise_invert = cp.invert
bitwise_right_shift = cp.right_shift
concat = cp.concatenate
pow = cp.power
arange = get_xp(cp)(_aliases.arange)
empty = get_xp(cp)(_aliases.empty)
empty_like = get_xp(cp)(_aliases.empty_like)
eye = get_xp(cp)(_aliases.eye)
full = get_xp(cp)(_aliases.full)
full_like = get_xp(cp)(_aliases.full_like)
linspace = get_xp(cp)(_aliases.linspace)
ones = get_xp(cp)(_aliases.ones)
ones_like = get_xp(cp)(_aliases.ones_like)
zeros = get_xp(cp)(_aliases.zeros)
zeros_like = get_xp(cp)(_aliases.zeros_like)
UniqueAllResult = get_xp(cp)(_aliases.UniqueAllResult)
UniqueCountsResult = get_xp(cp)(_aliases.UniqueCountsResult)
UniqueInverseResult = get_xp(cp)(_aliases.UniqueInverseResult)
unique_all = get_xp(cp)(_aliases.unique_all)
unique_counts = get_xp(cp)(_aliases.unique_counts)
unique_inverse = get_xp(cp)(_aliases.unique_inverse)
unique_values = get_xp(cp)(_aliases.unique_values)
std = get_xp(cp)(_aliases.std)
var = get_xp(cp)(_aliases.var)
cumulative_sum = get_xp(cp)(_aliases.cumulative_sum)
cumulative_prod = get_xp(cp)(_aliases.cumulative_prod)
clip = get_xp(cp)(_aliases.clip)
permute_dims = get_xp(cp)(_aliases.permute_dims)
reshape = get_xp(cp)(_aliases.reshape)
argsort = get_xp(cp)(_aliases.argsort)
sort = get_xp(cp)(_aliases.sort)
nonzero = get_xp(cp)(_aliases.nonzero)
ceil = get_xp(cp)(_aliases.ceil)
floor = get_xp(cp)(_aliases.floor)
trunc = get_xp(cp)(_aliases.trunc)
matmul = get_xp(cp)(_aliases.matmul)
matrix_transpose = get_xp(cp)(_aliases.matrix_transpose)
tensordot = get_xp(cp)(_aliases.tensordot)
sign = get_xp(cp)(_aliases.sign)
_copy_default = object()
# asarray also adds the copy keyword, which is not present in numpy 1.0.
def asarray(
obj: Union[
ndarray,
bool,
int,
float,
NestedSequence[bool | int | float],
SupportsBufferProtocol,
],
/,
*,
dtype: Optional[Dtype] = None,
device: Optional[Device] = None,
copy: Optional[bool] = _copy_default,
**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.
"""
with cp.cuda.Device(device):
# cupy is like NumPy 1.26 (except without _CopyMode). See the comments
# in asarray in numpy/_aliases.py.
if copy is not _copy_default:
# A future version of CuPy will change the meaning of copy=False
# to mean no-copy. We don't know for certain what version it will
# be yet, so to avoid breaking that version, we use a different
# default value for copy so asarray(obj) with no copy kwarg will
# always do the copy-if-needed behavior.
# This will still need to be updated to remove the
# NotImplementedError for copy=False, but at least this won't
# break the default or existing behavior.
if copy is None:
copy = False
elif copy is False:
raise NotImplementedError("asarray(copy=False) is not yet supported in cupy")
kwargs['copy'] = copy
return cp.array(obj, dtype=dtype, **kwargs)
def astype(
x: ndarray,
dtype: Dtype,
/,
*,
copy: bool = True,
device: Optional[Device] = None,
) -> ndarray:
if device is None:
return x.astype(dtype=dtype, copy=copy)
out = _helpers.to_device(x.astype(dtype=dtype, copy=False), device)
return out.copy() if copy and out is x else out
# cupy.count_nonzero does not have keepdims
def count_nonzero(
x: ndarray,
axis=None,
keepdims=False
) -> ndarray:
result = cp.count_nonzero(x, axis)
if keepdims:
if axis is None:
return cp.reshape(result, [1]*x.ndim)
return cp.expand_dims(result, axis)
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(cp, 'vecdot'):
vecdot = cp.vecdot
else:
vecdot = get_xp(cp)(_aliases.vecdot)
if hasattr(cp, 'isdtype'):
isdtype = cp.isdtype
else:
isdtype = get_xp(cp)(_aliases.isdtype)
if hasattr(cp, 'unstack'):
unstack = cp.unstack
else:
unstack = get_xp(cp)(_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', 'sign']
_all_ignore = ['cp', 'get_xp']
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