vllm/lib/python3.10/site-packages/cupy/__init__.py

import functools as _functools
import sys as _sys

import numpy as _numpy

from cupy import _environment
from cupy import _version


_environment._detect_duplicate_installation()  # NOQA
_environment._setup_win32_dll_directory()  # NOQA
_environment._preload_library('cutensor')  # NOQA


try:
    from cupy import _core  # NOQA
except ImportError as exc:
    raise ImportError(f'''
================================================================
{_environment._diagnose_import_error()}

Original error:
  {type(exc).__name__}: {exc}
================================================================
''') from exc


from cupy import cuda  # NOQA
# Do not make `cupy.cupyx` available because it is confusing.
import cupyx as _cupyx  # NOQA


def is_available():
    return cuda.is_available()


__version__ = _version.__version__


from cupy import fft  # NOQA
from cupy import linalg  # NOQA
from cupy import polynomial  # NOQA
from cupy import random  # NOQA
# `cupy.sparse` is deprecated in v8
from cupy import sparse  # NOQA
from cupy import testing  # NOQA  # NOQA


# import class and function
from cupy._core import ndarray  # NOQA
from cupy._core import ufunc  # NOQA


# =============================================================================
# Constants (borrowed from NumPy)
# =============================================================================
from numpy import e  # NOQA
from numpy import euler_gamma  # NOQA
from numpy import inf  # NOQA
from numpy import nan  # NOQA
from numpy import newaxis  # == None  # NOQA
from numpy import pi  # NOQA

# APIs to be removed in NumPy 2.0.
# Remove these when bumping the baseline API to NumPy 2.0.
# https://github.com/cupy/cupy/pull/7800
PINF = Inf = Infinity = infty = inf  # NOQA
NINF = -inf  # NOQA
NAN = NaN = nan  # NOQA
PZERO = 0.0  # NOQA
NZERO = -0.0  # NOQA

# =============================================================================
# Data types (borrowed from NumPy)
#
# The order of these declarations are borrowed from the NumPy document:
# https://numpy.org/doc/stable/reference/arrays.scalars.html
# =============================================================================

# -----------------------------------------------------------------------------
# Generic types
# -----------------------------------------------------------------------------
from numpy import complexfloating  # NOQA
from numpy import floating  # NOQA
from numpy import generic  # NOQA
from numpy import inexact  # NOQA
from numpy import integer  # NOQA
from numpy import number  # NOQA
from numpy import signedinteger  # NOQA
from numpy import unsignedinteger  # NOQA

# Not supported by CuPy:
# from numpy import flexible
# from numpy import character

# -----------------------------------------------------------------------------
# Booleans
# -----------------------------------------------------------------------------
from numpy import bool_  # NOQA

# -----------------------------------------------------------------------------
# Integers
# -----------------------------------------------------------------------------
from numpy import byte  # NOQA
from numpy import short  # NOQA
from numpy import intc  # NOQA
from numpy import int_  # NOQA
from numpy import longlong  # NOQA
from numpy import intp  # NOQA
from numpy import int8  # NOQA
from numpy import int16  # NOQA
from numpy import int32  # NOQA
from numpy import int64  # NOQA

# -----------------------------------------------------------------------------
# Unsigned integers
# -----------------------------------------------------------------------------
from numpy import ubyte  # NOQA
from numpy import ushort  # NOQA
from numpy import uintc  # NOQA
from numpy import uint  # NOQA
from numpy import ulonglong  # NOQA
from numpy import uintp  # NOQA
from numpy import uint8  # NOQA
from numpy import uint16  # NOQA
from numpy import uint32  # NOQA
from numpy import uint64  # NOQA

# -----------------------------------------------------------------------------
# Floating-point numbers
# -----------------------------------------------------------------------------
from numpy import half  # NOQA
from numpy import single  # NOQA
from numpy import double  # NOQA
from numpy import float64 as float_  # NOQA
# from numpy import longfloat  # NOQA   # XXX
from numpy import float16  # NOQA
from numpy import float32  # NOQA
from numpy import float64  # NOQA

# Not supported by CuPy:
# from numpy import float96
# from numpy import float128

# -----------------------------------------------------------------------------
# Complex floating-point numbers
# -----------------------------------------------------------------------------
from numpy import csingle  # NOQA
from numpy import complex64 as singlecomplex  # NOQA
from numpy import cdouble  # NOQA
from numpy import complex128 as cfloat  # NOQA
from numpy import complex128 as complex_  # NOQA
from numpy import complex64  # NOQA
from numpy import complex128  # NOQA

# Not supported by CuPy:
# from numpy import complex192
# from numpy import complex256
# from numpy import clongfloat

# -----------------------------------------------------------------------------
# Any Python object
# -----------------------------------------------------------------------------

# Not supported by CuPy:
# from numpy import object_
# from numpy import bytes_
# from numpy import unicode_
# from numpy import void

# -----------------------------------------------------------------------------
# Built-in Python types
# -----------------------------------------------------------------------------

# =============================================================================
# Routines
#
# The order of these declarations are borrowed from the NumPy document:
# https://numpy.org/doc/stable/reference/routines.html
# =============================================================================

# -----------------------------------------------------------------------------
# Array creation routines
# -----------------------------------------------------------------------------
from cupy._creation.basic import empty  # NOQA
from cupy._creation.basic import empty_like  # NOQA
from cupy._creation.basic import eye  # NOQA
from cupy._creation.basic import full  # NOQA
from cupy._creation.basic import full_like  # NOQA
from cupy._creation.basic import identity  # NOQA
from cupy._creation.basic import ones  # NOQA
from cupy._creation.basic import ones_like  # NOQA
from cupy._creation.basic import zeros  # NOQA
from cupy._creation.basic import zeros_like  # NOQA

from cupy._creation.from_data import copy  # NOQA
from cupy._creation.from_data import array  # NOQA
from cupy._creation.from_data import asanyarray  # NOQA
from cupy._creation.from_data import asarray  # NOQA
from cupy._creation.from_data import ascontiguousarray  # NOQA
from cupy._creation.from_data import fromfile  # NOQA
from cupy._creation.from_data import fromfunction  # NOQA
from cupy._creation.from_data import fromiter  # NOQA
from cupy._creation.from_data import frombuffer  # NOQA
from cupy._creation.from_data import fromstring  # NOQA
from cupy._creation.from_data import loadtxt  # NOQA
from cupy._creation.from_data import genfromtxt  # NOQA

from cupy._creation.ranges import arange  # NOQA
from cupy._creation.ranges import linspace  # NOQA
from cupy._creation.ranges import logspace  # NOQA
from cupy._creation.ranges import meshgrid  # NOQA
from cupy._creation.ranges import mgrid  # NOQA
from cupy._creation.ranges import ogrid  # NOQA

from cupy._creation.matrix import diag  # NOQA
from cupy._creation.matrix import diagflat  # NOQA
from cupy._creation.matrix import tri  # NOQA
from cupy._creation.matrix import tril  # NOQA
from cupy._creation.matrix import triu  # NOQA
from cupy._creation.matrix import vander  # NOQA

# -----------------------------------------------------------------------------
# Functional routines
# -----------------------------------------------------------------------------
from cupy._functional.piecewise import piecewise  # NOQA
from cupy._functional.vectorize import vectorize  # NOQA
from cupy.lib._shape_base import apply_along_axis  # NOQA

# -----------------------------------------------------------------------------
# Array manipulation routines
# -----------------------------------------------------------------------------
from cupy._manipulation.basic import copyto  # NOQA

from cupy._manipulation.shape import shape  # NOQA
from cupy._manipulation.shape import ravel  # NOQA
from cupy._manipulation.shape import reshape  # NOQA

from cupy._manipulation.transpose import moveaxis  # NOQA
from cupy._manipulation.transpose import rollaxis  # NOQA
from cupy._manipulation.transpose import swapaxes  # NOQA
from cupy._manipulation.transpose import transpose  # NOQA

from cupy._manipulation.dims import atleast_1d  # NOQA
from cupy._manipulation.dims import atleast_2d  # NOQA
from cupy._manipulation.dims import atleast_3d  # NOQA
from cupy._manipulation.dims import broadcast  # NOQA
from cupy._manipulation.dims import broadcast_arrays  # NOQA
from cupy._manipulation.dims import broadcast_to  # NOQA
from cupy._manipulation.dims import expand_dims  # NOQA
from cupy._manipulation.dims import squeeze  # NOQA

from cupy._manipulation.join import column_stack  # NOQA
from cupy._manipulation.join import concatenate  # NOQA
from cupy._manipulation.join import dstack  # NOQA
from cupy._manipulation.join import hstack  # NOQA
from cupy._manipulation.join import stack  # NOQA
from cupy._manipulation.join import vstack  # NOQA
from cupy._manipulation.join import vstack as row_stack  # NOQA

from cupy._manipulation.kind import asarray_chkfinite  # NOQA
from cupy._manipulation.kind import asfarray  # NOQA
from cupy._manipulation.kind import asfortranarray  # NOQA
from cupy._manipulation.kind import require  # NOQA

from cupy._manipulation.split import array_split  # NOQA
from cupy._manipulation.split import dsplit  # NOQA
from cupy._manipulation.split import hsplit  # NOQA
from cupy._manipulation.split import split  # NOQA
from cupy._manipulation.split import vsplit  # NOQA

from cupy._manipulation.tiling import repeat  # NOQA
from cupy._manipulation.tiling import tile  # NOQA

from cupy._manipulation.add_remove import delete  # NOQA
from cupy._manipulation.add_remove import append  # NOQA
from cupy._manipulation.add_remove import resize  # NOQA
from cupy._manipulation.add_remove import unique  # NOQA
from cupy._manipulation.add_remove import trim_zeros  # NOQA

from cupy._manipulation.rearrange import flip  # NOQA
from cupy._manipulation.rearrange import fliplr  # NOQA
from cupy._manipulation.rearrange import flipud  # NOQA
from cupy._manipulation.rearrange import roll  # NOQA
from cupy._manipulation.rearrange import rot90  # NOQA

# Borrowed from NumPy
if hasattr(_numpy, 'broadcast_shapes'):  # NumPy 1.20
    from numpy import broadcast_shapes  # NOQA

# -----------------------------------------------------------------------------
# Binary operations
# -----------------------------------------------------------------------------
from cupy._binary.elementwise import bitwise_and  # NOQA
from cupy._binary.elementwise import bitwise_or  # NOQA
from cupy._binary.elementwise import bitwise_xor  # NOQA
from cupy._binary.elementwise import bitwise_not  # NOQA
from cupy._binary.elementwise import invert  # NOQA
from cupy._binary.elementwise import left_shift  # NOQA
from cupy._binary.elementwise import right_shift  # NOQA

from cupy._binary.packing import packbits  # NOQA
from cupy._binary.packing import unpackbits  # NOQA


def binary_repr(num, width=None):
    """Return the binary representation of the input number as a string.

    .. seealso:: :func:`numpy.binary_repr`
    """
    return _numpy.binary_repr(num, width)


# -----------------------------------------------------------------------------
# Data type routines (mostly borrowed from NumPy)
# -----------------------------------------------------------------------------
def can_cast(from_, to, casting='safe'):
    """Returns True if cast between data types can occur according to the
    casting rule. If from is a scalar or array scalar, also returns True if the
    scalar value can be cast without overflow or truncation to an integer.

    .. seealso:: :func:`numpy.can_cast`
    """
    from_ = from_.dtype if isinstance(from_, ndarray) else from_
    return _numpy.can_cast(from_, to, casting=casting)


def common_type(*arrays):
    """Return a scalar type which is common to the input arrays.

    .. seealso:: :func:`numpy.common_type`
    """
    if len(arrays) == 0:
        return _numpy.float16

    default_float_dtype = _numpy.dtype('float64')
    dtypes = []
    for a in arrays:
        if a.dtype.kind == 'b':
            raise TypeError('can\'t get common type for non-numeric array')
        elif a.dtype.kind in 'iu':
            dtypes.append(default_float_dtype)
        else:
            dtypes.append(a.dtype)

    return _functools.reduce(_numpy.promote_types, dtypes).type


def result_type(*arrays_and_dtypes):
    """Returns the type that results from applying the NumPy type promotion
    rules to the arguments.

    .. seealso:: :func:`numpy.result_type`
    """
    dtypes = [a.dtype if isinstance(a, ndarray)
              else a for a in arrays_and_dtypes]
    return _numpy.result_type(*dtypes)


from cupy._core.core import min_scalar_type  # NOQA

from numpy import promote_types  # NOQA

from numpy import dtype  # NOQA

from numpy import finfo  # NOQA
from numpy import iinfo  # NOQA

from numpy import issubdtype  # NOQA

from numpy import mintypecode  # NOQA
from numpy import typename  # NOQA

# -----------------------------------------------------------------------------
# Optionally Scipy-accelerated routines
# -----------------------------------------------------------------------------
# TODO(beam2d): Implement it

# -----------------------------------------------------------------------------
# Discrete Fourier Transform
# -----------------------------------------------------------------------------
# TODO(beam2d): Implement it

# -----------------------------------------------------------------------------
# Indexing routines
# -----------------------------------------------------------------------------
from cupy._indexing.generate import c_  # NOQA
from cupy._indexing.generate import indices  # NOQA
from cupy._indexing.generate import ix_  # NOQA
from cupy._indexing.generate import mask_indices  # NOQA
from cupy._indexing.generate import tril_indices  # NOQA
from cupy._indexing.generate import tril_indices_from  # NOQA
from cupy._indexing.generate import triu_indices  # NOQA
from cupy._indexing.generate import triu_indices_from  # NOQA
from cupy._indexing.generate import r_  # NOQA
from cupy._indexing.generate import ravel_multi_index  # NOQA
from cupy._indexing.generate import unravel_index  # NOQA

from cupy._indexing.indexing import choose  # NOQA
from cupy._indexing.indexing import compress  # NOQA
from cupy._indexing.indexing import diagonal  # NOQA
from cupy._indexing.indexing import extract  # NOQA
from cupy._indexing.indexing import select  # NOQA
from cupy._indexing.indexing import take  # NOQA
from cupy._indexing.indexing import take_along_axis  # NOQA

from cupy._indexing.insert import place  # NOQA
from cupy._indexing.insert import put  # NOQA
from cupy._indexing.insert import putmask  # NOQA
from cupy._indexing.insert import fill_diagonal  # NOQA
from cupy._indexing.insert import diag_indices  # NOQA
from cupy._indexing.insert import diag_indices_from  # NOQA

from cupy._indexing.iterate import flatiter  # NOQA

# Borrowed from NumPy
from numpy import index_exp  # NOQA
from numpy import ndindex  # NOQA
from numpy import s_  # NOQA

# -----------------------------------------------------------------------------
# Input and output
# -----------------------------------------------------------------------------
from cupy._io.npz import load  # NOQA
from cupy._io.npz import save  # NOQA
from cupy._io.npz import savez  # NOQA
from cupy._io.npz import savez_compressed  # NOQA

from cupy._io.formatting import array_repr  # NOQA
from cupy._io.formatting import array_str  # NOQA
from cupy._io.formatting import array2string  # NOQA
from cupy._io.formatting import format_float_positional  # NOQA
from cupy._io.formatting import format_float_scientific  # NOQA

from cupy._io.text import savetxt  # NOQA


def base_repr(number, base=2, padding=0):  # NOQA (needed to avoid redefinition of `number`)
    """Return a string representation of a number in the given base system.

    .. seealso:: :func:`numpy.base_repr`
    """
    return _numpy.base_repr(number, base, padding)


# Borrowed from NumPy
from numpy import get_printoptions  # NOQA
from numpy import set_printoptions  # NOQA
from numpy import printoptions  # NOQA


# -----------------------------------------------------------------------------
# Linear algebra
# -----------------------------------------------------------------------------
from cupy.linalg._einsum import einsum  # NOQA

from cupy.linalg._product import cross  # NOQA
from cupy.linalg._product import dot  # NOQA
from cupy.linalg._product import inner  # NOQA
from cupy.linalg._product import kron  # NOQA
from cupy.linalg._product import matmul  # NOQA
from cupy.linalg._product import outer  # NOQA
from cupy.linalg._product import tensordot  # NOQA
from cupy.linalg._product import vdot  # NOQA

from cupy.linalg._norms import trace  # NOQA

# -----------------------------------------------------------------------------
# Logic functions
# -----------------------------------------------------------------------------
from cupy._logic.comparison import allclose  # NOQA
from cupy._logic.comparison import array_equal  # NOQA
from cupy._logic.comparison import array_equiv  # NOQA
from cupy._logic.comparison import isclose  # NOQA

from cupy._logic.content import isfinite  # NOQA
from cupy._logic.content import isinf  # NOQA
from cupy._logic.content import isnan  # NOQA
from cupy._logic.content import isneginf  # NOQA
from cupy._logic.content import isposinf  # NOQA

from cupy._logic.truth import in1d  # NOQA
from cupy._logic.truth import isin  # NOQA

from cupy._logic.type_testing import iscomplex  # NOQA
from cupy._logic.type_testing import iscomplexobj  # NOQA
from cupy._logic.type_testing import isfortran  # NOQA
from cupy._logic.type_testing import isreal  # NOQA
from cupy._logic.type_testing import isrealobj  # NOQA

from cupy._logic.truth import in1d  # NOQA
from cupy._logic.truth import intersect1d  # NOQA
from cupy._logic.truth import isin  # NOQA
from cupy._logic.truth import setdiff1d  # NOQA
from cupy._logic.truth import setxor1d  # NOQA
from cupy._logic.truth import union1d  # NOQA


def isscalar(element):
    """Returns True if the type of num is a scalar type.

    .. seealso:: :func:`numpy.isscalar`
    """
    return _numpy.isscalar(element)


from cupy._logic.ops import logical_and  # NOQA
from cupy._logic.ops import logical_not  # NOQA
from cupy._logic.ops import logical_or  # NOQA
from cupy._logic.ops import logical_xor  # NOQA

from cupy._logic.comparison import equal  # NOQA
from cupy._logic.comparison import greater  # NOQA
from cupy._logic.comparison import greater_equal  # NOQA
from cupy._logic.comparison import less  # NOQA
from cupy._logic.comparison import less_equal  # NOQA
from cupy._logic.comparison import not_equal  # NOQA

from cupy._logic.truth import all  # NOQA
from cupy._logic.truth import alltrue  # NOQA
from cupy._logic.truth import any  # NOQA
from cupy._logic.truth import sometrue  # NOQA

# -----------------------------------------------------------------------------
# Polynomial functions
# -----------------------------------------------------------------------------
from cupy.lib._polynomial import poly1d  # NOQA
from cupy.lib._routines_poly import poly  # NOQA
from cupy.lib._routines_poly import polyadd  # NOQA
from cupy.lib._routines_poly import polysub  # NOQA
from cupy.lib._routines_poly import polymul  # NOQA
from cupy.lib._routines_poly import polyfit  # NOQA
from cupy.lib._routines_poly import polyval  # NOQA
from cupy.lib._routines_poly import roots  # NOQA

# Borrowed from NumPy
from cupy.exceptions import RankWarning  # NOQA

# -----------------------------------------------------------------------------
# Mathematical functions
# -----------------------------------------------------------------------------
from cupy._math.trigonometric import arccos  # NOQA
from cupy._math.trigonometric import arcsin  # NOQA
from cupy._math.trigonometric import arctan  # NOQA
from cupy._math.trigonometric import arctan2  # NOQA
from cupy._math.trigonometric import cos  # NOQA
from cupy._math.trigonometric import deg2rad  # NOQA
from cupy._math.trigonometric import degrees  # NOQA
from cupy._math.trigonometric import hypot  # NOQA
from cupy._math.trigonometric import rad2deg  # NOQA
from cupy._math.trigonometric import radians  # NOQA
from cupy._math.trigonometric import sin  # NOQA
from cupy._math.trigonometric import tan  # NOQA
from cupy._math.trigonometric import unwrap  # NOQA

from cupy._math.hyperbolic import arccosh  # NOQA
from cupy._math.hyperbolic import arcsinh  # NOQA
from cupy._math.hyperbolic import arctanh  # NOQA
from cupy._math.hyperbolic import cosh  # NOQA
from cupy._math.hyperbolic import sinh  # NOQA
from cupy._math.hyperbolic import tanh  # NOQA

from cupy._math.rounding import around  # NOQA
from cupy._math.rounding import ceil  # NOQA
from cupy._math.rounding import fix  # NOQA
from cupy._math.rounding import floor  # NOQA
from cupy._math.rounding import rint  # NOQA
from cupy._math.rounding import round  # NOQA
from cupy._math.rounding import round_  # NOQA
from cupy._math.rounding import trunc  # NOQA

from cupy._math.sumprod import prod  # NOQA
from cupy._math.sumprod import product  # NOQA
from cupy._math.sumprod import sum  # NOQA
from cupy._math.sumprod import cumprod  # NOQA
from cupy._math.sumprod import cumproduct  # NOQA
from cupy._math.sumprod import cumsum  # NOQA
from cupy._math.sumprod import ediff1d  # NOQA
from cupy._math.sumprod import nancumprod  # NOQA
from cupy._math.sumprod import nancumsum  # NOQA
from cupy._math.sumprod import nansum  # NOQA
from cupy._math.sumprod import nanprod  # NOQA
from cupy._math.sumprod import diff  # NOQA
from cupy._math.sumprod import gradient  # NOQA
from cupy._math.sumprod import trapz  # NOQA
from cupy._math.window import bartlett  # NOQA
from cupy._math.window import blackman  # NOQA
from cupy._math.window import hamming  # NOQA
from cupy._math.window import hanning  # NOQA
from cupy._math.window import kaiser  # NOQA

from cupy._math.explog import exp  # NOQA
from cupy._math.explog import exp2  # NOQA
from cupy._math.explog import expm1  # NOQA
from cupy._math.explog import log  # NOQA
from cupy._math.explog import log10  # NOQA
from cupy._math.explog import log1p  # NOQA
from cupy._math.explog import log2  # NOQA
from cupy._math.explog import logaddexp  # NOQA
from cupy._math.explog import logaddexp2  # NOQA

from cupy._math.special import i0  # NOQA
from cupy._math.special import sinc  # NOQA

from cupy._math.floating import copysign  # NOQA
from cupy._math.floating import frexp  # NOQA
from cupy._math.floating import ldexp  # NOQA
from cupy._math.floating import nextafter  # NOQA
from cupy._math.floating import signbit  # NOQA

from cupy._math.rational import gcd  # NOQA
from cupy._math.rational import lcm  # NOQA

from cupy._math.arithmetic import add  # NOQA
from cupy._math.arithmetic import divide  # NOQA
from cupy._math.arithmetic import divmod  # NOQA
from cupy._math.arithmetic import floor_divide  # NOQA
from cupy._math.arithmetic import float_power  # NOQA
from cupy._math.arithmetic import fmod  # NOQA
from cupy._math.arithmetic import modf  # NOQA
from cupy._math.arithmetic import multiply  # NOQA
from cupy._math.arithmetic import negative  # NOQA
from cupy._math.arithmetic import positive  # NOQA
from cupy._math.arithmetic import power  # NOQA
from cupy._math.arithmetic import reciprocal  # NOQA
from cupy._math.arithmetic import remainder  # NOQA
from cupy._math.arithmetic import remainder as mod  # NOQA
from cupy._math.arithmetic import subtract  # NOQA
from cupy._math.arithmetic import true_divide  # NOQA

from cupy._math.arithmetic import angle  # NOQA
from cupy._math.arithmetic import conjugate as conj  # NOQA
from cupy._math.arithmetic import conjugate  # NOQA
from cupy._math.arithmetic import imag  # NOQA
from cupy._math.arithmetic import real  # NOQA

from cupy._math.misc import absolute as abs  # NOQA
from cupy._math.misc import absolute  # NOQA
from cupy._math.misc import cbrt  # NOQA
from cupy._math.misc import clip  # NOQA
from cupy._math.misc import fabs  # NOQA
from cupy._math.misc import fmax  # NOQA
from cupy._math.misc import fmin  # NOQA
from cupy._math.misc import interp  # NOQA
from cupy._math.misc import maximum  # NOQA
from cupy._math.misc import minimum  # NOQA
from cupy._math.misc import nan_to_num  # NOQA
from cupy._math.misc import real_if_close  # NOQA
from cupy._math.misc import sign  # NOQA
from cupy._math.misc import heaviside  # NOQA
from cupy._math.misc import sqrt  # NOQA
from cupy._math.misc import square  # NOQA
from cupy._math.misc import convolve  # NOQA

# -----------------------------------------------------------------------------
# Miscellaneous routines
# -----------------------------------------------------------------------------
from cupy._misc.byte_bounds import byte_bounds  # NOQA
from cupy._misc.memory_ranges import may_share_memory  # NOQA
from cupy._misc.memory_ranges import shares_memory  # NOQA
from cupy._misc.who import who  # NOQA

# Borrowed from NumPy
from numpy import iterable  # NOQA
from cupy.exceptions import AxisError  # NOQA


# -----------------------------------------------------------------------------
# Padding
# -----------------------------------------------------------------------------
from cupy._padding.pad import pad  # NOQA


# -----------------------------------------------------------------------------
# Sorting, searching, and counting
# -----------------------------------------------------------------------------
from cupy._sorting.count import count_nonzero  # NOQA

from cupy._sorting.search import argmax  # NOQA
from cupy._sorting.search import argmin  # NOQA
from cupy._sorting.search import argwhere  # NOQA
from cupy._sorting.search import flatnonzero  # NOQA
from cupy._sorting.search import nanargmax  # NOQA
from cupy._sorting.search import nanargmin  # NOQA
from cupy._sorting.search import nonzero  # NOQA
from cupy._sorting.search import searchsorted  # NOQA
from cupy._sorting.search import where  # NOQA

from cupy._sorting.sort import argpartition  # NOQA
from cupy._sorting.sort import argsort  # NOQA
from cupy._sorting.sort import lexsort  # NOQA
from cupy._sorting.sort import msort  # NOQA
from cupy._sorting.sort import sort_complex  # NOQA
from cupy._sorting.sort import partition  # NOQA
from cupy._sorting.sort import sort  # NOQA

# -----------------------------------------------------------------------------
# Statistics
# -----------------------------------------------------------------------------
from cupy._statistics.correlation import corrcoef  # NOQA
from cupy._statistics.correlation import cov  # NOQA
from cupy._statistics.correlation import correlate  # NOQA

from cupy._statistics.order import amax  # NOQA
from cupy._statistics.order import amax as max  # NOQA
from cupy._statistics.order import amin  # NOQA
from cupy._statistics.order import amin as min  # NOQA
from cupy._statistics.order import nanmax  # NOQA
from cupy._statistics.order import nanmin  # NOQA
from cupy._statistics.order import percentile  # NOQA
from cupy._statistics.order import ptp  # NOQA
from cupy._statistics.order import quantile  # NOQA

from cupy._statistics.meanvar import median  # NOQA
from cupy._statistics.meanvar import average  # NOQA
from cupy._statistics.meanvar import mean  # NOQA
from cupy._statistics.meanvar import std  # NOQA
from cupy._statistics.meanvar import var  # NOQA
from cupy._statistics.meanvar import nanmedian  # NOQA
from cupy._statistics.meanvar import nanmean  # NOQA
from cupy._statistics.meanvar import nanstd  # NOQA
from cupy._statistics.meanvar import nanvar  # NOQA

from cupy._statistics.histogram import bincount  # NOQA
from cupy._statistics.histogram import digitize  # NOQA
from cupy._statistics.histogram import histogram  # NOQA
from cupy._statistics.histogram import histogram2d  # NOQA
from cupy._statistics.histogram import histogramdd  # NOQA

# -----------------------------------------------------------------------------
# Classes without their own docs
# -----------------------------------------------------------------------------
from cupy.exceptions import ComplexWarning  # NOQA
from cupy.exceptions import ModuleDeprecationWarning  # NOQA
from cupy.exceptions import TooHardError  # NOQA
from cupy.exceptions import VisibleDeprecationWarning  # NOQA


# -----------------------------------------------------------------------------
# Undocumented functions
# -----------------------------------------------------------------------------
from cupy._core import size  # NOQA


def ndim(a):
    """Returns the number of dimensions of an array.

    Args:
        a (array-like): If it is not already an `cupy.ndarray`, a conversion
            via :func:`numpy.asarray` is attempted.

    Returns:
        (int): The number of dimensions in `a`.

    """
    try:
        return a.ndim
    except AttributeError:
        return _numpy.ndim(a)


# -----------------------------------------------------------------------------
# CuPy specific functions
# -----------------------------------------------------------------------------

from cupy._util import clear_memo  # NOQA
from cupy._util import memoize  # NOQA

from cupy._core import ElementwiseKernel  # NOQA
from cupy._core import RawKernel  # NOQA
from cupy._core import RawModule  # NOQA
from cupy._core._reduction import ReductionKernel  # NOQA

# -----------------------------------------------------------------------------
# DLPack
# -----------------------------------------------------------------------------

from cupy._core import fromDlpack  # NOQA
from cupy._core import from_dlpack  # NOQA


def asnumpy(a, stream=None, order='C', out=None, *, blocking=True):
    """Returns an array on the host memory from an arbitrary source array.

    Args:
        a: Arbitrary object that can be converted to :class:`numpy.ndarray`.
        stream (cupy.cuda.Stream): CUDA stream object. If given, the
            stream is used to perform the copy. Otherwise, the current
            stream is used. Note that if ``a`` is not a :class:`cupy.ndarray`
            object, then this argument has no effect.
        order ({'C', 'F', 'A'}): The desired memory layout of the host
            array. When ``order`` is 'A', it uses 'F' if the array is
            fortran-contiguous and 'C' otherwise. The ``order`` will be
            ignored if ``out`` is specified.
        out (numpy.ndarray): The output array to be written to. It must have
            compatible shape and dtype with those of ``a``'s.
        blocking (bool): If set to ``False``, the copy runs asynchronously
            on the given (if given) or current stream, and users are
            responsible for ensuring the stream order. Default is ``True``,
            so the copy is synchronous (with respect to the host).

    Returns:
        numpy.ndarray: Converted array on the host memory.

    """
    if isinstance(a, ndarray):
        return a.get(stream=stream, order=order, out=out, blocking=blocking)
    elif hasattr(a, "__cuda_array_interface__"):
        return array(a).get(
            stream=stream, order=order, out=out, blocking=blocking)
    else:
        temp = _numpy.asarray(a, order=order)
        if out is not None:
            out[...] = temp
        else:
            out = temp
        return out


_cupy = _sys.modules[__name__]


def get_array_module(*args):
    """Returns the array module for arguments.

    This function is used to implement CPU/GPU generic code. If at least one of
    the arguments is a :class:`cupy.ndarray` object, the :mod:`cupy` module is
    returned.

    Args:
        args: Values to determine whether NumPy or CuPy should be used.

    Returns:
        module: :mod:`cupy` or :mod:`numpy` is returned based on the types of
        the arguments.

    .. admonition:: Example

       A NumPy/CuPy generic function can be written as follows

       >>> def softplus(x):
       ...     xp = cupy.get_array_module(x)
       ...     return xp.maximum(0, x) + xp.log1p(xp.exp(-abs(x)))

    """
    for arg in args:
        if isinstance(arg, (ndarray, _cupyx.scipy.sparse.spmatrix,
                            _core.fusion._FusionVarArray,
                            _core.new_fusion._ArrayProxy)):
            return _cupy
    return _numpy


fuse = _core.fusion.fuse

disable_experimental_feature_warning = False


# set default allocator
_default_memory_pool = cuda.MemoryPool()
_default_pinned_memory_pool = cuda.PinnedMemoryPool()

cuda.set_allocator(_default_memory_pool.malloc)
cuda.set_pinned_memory_allocator(_default_pinned_memory_pool.malloc)


def get_default_memory_pool():
    """Returns CuPy default memory pool for GPU memory.

    Returns:
        cupy.cuda.MemoryPool: The memory pool object.

    .. note::
       If you want to disable memory pool, please use the following code.

       >>> cupy.cuda.set_allocator(None)

    """
    return _default_memory_pool


def get_default_pinned_memory_pool():
    """Returns CuPy default memory pool for pinned memory.

    Returns:
        cupy.cuda.PinnedMemoryPool: The memory pool object.

    .. note::
       If you want to disable memory pool, please use the following code.

       >>> cupy.cuda.set_pinned_memory_allocator(None)

    """
    return _default_pinned_memory_pool


def show_config(*, _full=False):
    """Prints the current runtime configuration to standard output."""
    _sys.stdout.write(str(_cupyx.get_runtime_info(full=_full)))
    _sys.stdout.flush()


_deprecated_apis = [
    'int0',
    'uint0',
    'bool8',
]


# np 2.0: XXX shims for things removed in np 2.0

# https://github.com/numpy/numpy/blob/v1.26.4/numpy/core/numerictypes.py#L283-L322   # NOQA
def issubclass_(arg1, arg2):
    try:
        return issubclass(arg1, arg2)
    except TypeError:
        return False

# https://github.com/numpy/numpy/blob/v1.26.0/numpy/core/numerictypes.py#L229-L280   # NOQA


def obj2sctype(rep, default=None):
    """
    Return the scalar dtype or NumPy equivalent of Python type of an object.

    Parameters
    ----------
    rep : any
        The object of which the type is returned.
    default : any, optional
        If given, this is returned for objects whose types can not be
        determined. If not given, None is returned for those objects.

    Returns
    -------
    dtype : dtype or Python type
        The data type of `rep`.

    """
    # prevent abstract classes being upcast
    if isinstance(rep, type) and issubclass(rep, _numpy.generic):
        return rep
    # extract dtype from arrays
    if isinstance(rep, _numpy.ndarray):
        return rep.dtype.type
    # fall back on dtype to convert
    try:
        res = _numpy.dtype(rep)
    except Exception:
        return default
    else:
        return res.type


# https://github.com/numpy/numpy/blob/v1.26.0/numpy/core/numerictypes.py#L326C1-L355C1  # NOQA
def issubsctype(arg1, arg2):
    """
    Determine if the first argument is a subclass of the second argument.

    Parameters
    ----------
    arg1, arg2 : dtype or dtype specifier
        Data-types.

    Returns
    -------
    out : bool
        The result.

    """
    return issubclass(obj2sctype(arg1), obj2sctype(arg2))


# https://github.com/numpy/numpy/blob/v1.26.0/numpy/core/numerictypes.py#L457  # NOQA
def sctype2char(sctype):
    """
    Return the string representation of a scalar dtype.

    Parameters
    ----------
    sctype : scalar dtype or object
        If a scalar dtype, the corresponding string character is
        returned. If an object, `sctype2char` tries to infer its scalar type
        and then return the corresponding string character.

    Returns
    -------
    typechar : str
        The string character corresponding to the scalar type.

    Raises
    ------
    ValueError
        If `sctype` is an object for which the type can not be inferred.

    """
    sctype = obj2sctype(sctype)
    if sctype is None:
        raise ValueError("unrecognized type")
    return _numpy.dtype(sctype).char


# https://github.com/numpy/numpy/blob/v1.26.0/numpy/core/numerictypes.py#L184  # NOQA
def issctype(rep):
    """
    Determines whether the given object represents a scalar data-type.

    Parameters
    ----------
    rep : any
        If `rep` is an instance of a scalar dtype, True is returned. If not,
        False is returned.

    Returns
    -------
    out : bool
        Boolean result of check whether `rep` is a scalar dtype.

    """
    if not isinstance(rep, (type, _numpy.dtype)):
        return False
    try:
        res = obj2sctype(rep)
        if res and res != _numpy.object_:
            return True
        return False
    except Exception:
        return False


# np 2.0: XXX shims for things moved in np 2.0
if _numpy.__version__ < "2":
    from numpy import format_parser  # NOQA
    from numpy import DataSource     # NOQA
else:
    from numpy.rec import format_parser   # type: ignore [no-redef]  # NOQA
    from numpy.lib.npyio import DataSource  # NOQA


# np 2.0: XXX shims for things removed without replacement
if _numpy.__version__ < "2":
    from numpy import find_common_type   # NOQA
    from numpy import set_string_function  # NOQA
    from numpy import get_array_wrap  # NOQA
    from numpy import disp  # NOQA
    from numpy import safe_eval  # NOQA
else:

    _template = '''\
''This function has been removed in NumPy v2.
Use {recommendation} instead.

CuPy has been providing this function as an alias to the NumPy
implementation, so it cannot be used in environments with NumPy
v2 installed. If you rely on this function and you cannot modify
the code to use {recommendation}, please downgrade NumPy to v1.26
or earlier.
'''

    def find_common_type(*args, **kwds):
        mesg = _template.format(
            recommendation='`promote_types` or `result_type`'
        )
        raise RuntimeError(mesg)

    def set_string_function(*args, **kwds):   # type: ignore [misc]
        mesg = _template.format(recommendation='`np.set_printoptions`')
        raise RuntimeError(mesg)

    def get_array_wrap(*args, **kwds):       # type: ignore [no-redef]
        mesg = _template.format(recommendation="<no replacement>")
        raise RuntimeError(mesg)

    def disp(*args, **kwds):   # type: ignore [misc]
        mesg = _template.format(recommendation="your own print function")
        raise RuntimeError(mesg)

    def safe_eval(*args, **kwds):  # type: ignore [misc]
        mesg = _template.format(recommendation="`ast.literal_eval`")
        raise RuntimeError(mesg)


def __getattr__(name):
    if name in _deprecated_apis:
        return getattr(_numpy, name)

    raise AttributeError(f"module 'cupy' has no attribute {name!r}")


def _embed_signatures(dirs):
    for name, value in dirs.items():
        if isinstance(value, ufunc):
            from cupy._core._kernel import _ufunc_doc_signature_formatter
            value.__doc__ = (
                _ufunc_doc_signature_formatter(value, name) +
                '\n\n' + value._doc
            )


_embed_signatures(globals())
_embed_signatures(fft.__dict__)
_embed_signatures(linalg.__dict__)
_embed_signatures(random.__dict__)
_embed_signatures(sparse.__dict__)
_embed_signatures(testing.__dict__)