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# pyright: reportPrivateUsage=false
from __future__ import annotations
from builtins import bool as py_bool
from typing import TYPE_CHECKING, Any, Literal, TypeAlias, cast
import numpy as np
from .._internal import get_xp
from ..common import _aliases, _helpers
from ..common._typing import NestedSequence, SupportsBufferProtocol
from ._info import __array_namespace_info__
from ._typing import Array, Device, DType
if TYPE_CHECKING:
from typing_extensions import Buffer, TypeIs
# The values of the `_CopyMode` enum can be either `False`, `True`, or `2`:
# https://github.com/numpy/numpy/blob/5a8a6a79d9c2fff8f07dcab5d41e14f8508d673f/numpy/_globals.pyi#L7-L10
_Copy: TypeAlias = py_bool | Literal[2] | np._CopyMode
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)
finfo = get_xp(np)(_aliases.finfo)
iinfo = get_xp(np)(_aliases.iinfo)
def _supports_buffer_protocol(obj: object) -> TypeIs[Buffer]: # pyright: ignore[reportUnusedFunction]
try:
memoryview(obj) # pyright: ignore[reportArgumentType]
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: Array | complex | NestedSequence[complex] | SupportsBufferProtocol,
/,
*,
dtype: DType | None = None,
device: Device | None = None,
copy: _Copy | None = None,
**kwargs: Any,
) -> Array:
"""
Array API compatibility wrapper for asarray().
See the corresponding documentation in the array library and/or the array API
specification for more details.
"""
_helpers._check_device(np, device)
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
return np.array(obj, copy=copy, dtype=dtype, **kwargs) # pyright: ignore
def astype(
x: Array,
dtype: DType,
/,
*,
copy: py_bool = True,
device: Device | None = None,
) -> Array:
_helpers._check_device(np, device)
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: Array,
axis: int | tuple[int, ...] | None = None,
keepdims: py_bool = False,
) -> Array:
# NOTE: this is currently incorrectly typed in numpy, but will be fixed in
# numpy 2.2.5 and 2.3.0: https://github.com/numpy/numpy/pull/28750
result = cast("Any", np.count_nonzero(x, axis=axis, keepdims=keepdims)) # pyright: ignore[reportArgumentType, reportCallIssue]
if axis is None and not keepdims:
return np.asarray(result)
return result
# take_along_axis: axis defaults to -1 but in numpy axis is a required arg
def take_along_axis(x: Array, indices: Array, /, *, axis: int = -1):
return np.take_along_axis(x, indices, axis=axis)
# 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__ = [
"__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",
"take_along_axis"
]
__all__ += _aliases.__all__
_all_ignore = ["np", "get_xp"]
def __dir__() -> list[str]:
return __all__
|
