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vlad-perevezentsevvlad-perevezentsev
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Remove wildcard imports in dpnp.fft and dpnp.random submodules (#2649)
This PR proposes to remove wildcard imports from `dpnp.fft` and `dpnp.random` submodules and register them as explicit submodules in `dpnp` namespace. It also removes wildcard import of `dpnp.memory` from `dpnp_iface.py`
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10 files changed

+149
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‎CHANGELOG.md‎

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@@ -32,6 +32,7 @@ Also, that release drops support for Python 3.9, making Python 3.10 the minimum
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* Aligned documentation with NumPy and CuPy style by using short function names [#2633](https://github.com/IntelPython/dpnp/pull/2633)
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* Added the missing positional-only and keyword-only parameter markers to bring the ufunc signatures into alignment with NumPy [#2660](https://github.com/IntelPython/dpnp/pull/2660)
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* Redesigned `dpnp.modf` function to be a part of `ufunc` and `vm` pybind11 extensions [#2654](https://github.com/IntelPython/dpnp/pull/2654)
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* Refactored `dpnp.fft` and `dpnp.random` submodules by removing wildcard imports and defining explicit public exports [#2649](https://github.com/IntelPython/dpnp/pull/2649)
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### Deprecated
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‎dpnp/__init__.py‎

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from .dpnp_iface_utils import __all__ as _ifaceutils__all__
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from ._version import get_versions
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from . import exceptions as exceptions
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from . import fft as fft
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from . import linalg as linalg
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from . import random as random
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from . import scipy as scipy
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__all__ = _iface__all__
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__all__ += _ifaceutils__all__
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# add submodules
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__all__ += ["exceptions", "linalg", "scipy"]
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__all__ += ["exceptions", "fft", "linalg", "random", "scipy"]
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__version__ = get_versions()["version"]

‎dpnp/dpnp_array.py‎

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from dpctl.tensor._numpy_helper import AxisError
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import dpnp
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import dpnp.memory as dpm
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from . import memory as dpm
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def _get_unwrapped_index_key(key):

‎dpnp/dpnp_iface.py‎

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import dpnp
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from dpnp.dpnp_algo import *
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from dpnp.dpnp_array import dpnp_array
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from dpnp.fft import *
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from dpnp.memory import *
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from dpnp.random import *
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__all__ = [
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"are_same_logical_tensors",

‎dpnp/fft/__init__.py‎

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"""
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from dpnp.fft.dpnp_iface_fft import *
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from dpnp.fft.dpnp_iface_fft import __all__ as __all__fft
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__all__ = __all__fft
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from .dpnp_iface_fft import (
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fft,
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fft2,
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fftfreq,
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fftn,
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fftshift,
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hfft,
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ifft,
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ifft2,
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ifftn,
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ifftshift,
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ihfft,
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irfft,
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irfft2,
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irfftn,
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rfft,
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rfft2,
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rfftfreq,
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rfftn,
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)
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__all__ = [
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"fft",
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"fft2",
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"fftfreq",
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"fftn",
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"fftshift",
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"hfft",
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"ifft",
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"ifft2",
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"ifftn",
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"ifftshift",
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"ihfft",
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"irfft",
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"irfft2",
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"irfftn",
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"rfft",
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"rfft2",
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"rfftfreq",
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"rfftn",
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]

‎dpnp/fft/dpnp_iface_fft.py‎

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from .dpnp_utils_fft import dpnp_fft, dpnp_fftn, dpnp_fillfreq, swap_direction
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__all__ = [
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"fft",
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"fft2",
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"fftfreq",
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"fftn",
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"fftshift",
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"hfft",
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"ifft",
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"ifft2",
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"ifftn",
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"ifftshift",
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"ihfft",
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"irfft",
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"irfft2",
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"irfftn",
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"rfft",
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"rfft2",
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"rfftfreq",
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"rfftn",
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]
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def fft(a, n=None, axis=-1, norm=None, out=None):
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"""

‎dpnp/fft/dpnp_utils_fft.py‎

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_standardize_strides_to_nonzero,
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)
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__all__ = ["dpnp_fft", "dpnp_fftn", "dpnp_fillfreq", "swap_direction"]
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def _check_norm(norm):
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if norm not in (None, "ortho", "forward", "backward"):

‎dpnp/random/__init__.py‎

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# THE POSSIBILITY OF SUCH DAMAGE.
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# *****************************************************************************
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from .dpnp_iface_random import *
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from .dpnp_iface_random import __all__ as __all__random
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from .dpnp_random_state import *
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from .dpnp_random_state import __all__ as __all__random_state
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from .dpnp_iface_random import (
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beta,
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binomial,
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bytes,
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chisquare,
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choice,
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dirichlet,
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exponential,
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f,
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gamma,
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geometric,
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gumbel,
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hypergeometric,
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laplace,
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logistic,
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lognormal,
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logseries,
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multinomial,
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multivariate_normal,
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negative_binomial,
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noncentral_chisquare,
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noncentral_f,
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normal,
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pareto,
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permutation,
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poisson,
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power,
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rand,
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randint,
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randn,
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random,
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random_integers,
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random_sample,
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ranf,
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rayleigh,
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sample,
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seed,
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shuffle,
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standard_cauchy,
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standard_exponential,
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standard_gamma,
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standard_normal,
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standard_t,
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triangular,
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uniform,
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vonmises,
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wald,
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weibull,
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zipf,
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)
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from .dpnp_random_state import RandomState
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__all__ = __all__random
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__all__ += __all__random_state
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__all__ = [
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"beta",
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"binomial",
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"bytes",
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"chisquare",
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"choice",
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"dirichlet",
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"exponential",
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"f",
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"gamma",
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"geometric",
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"gumbel",
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"hypergeometric",
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"laplace",
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"logistic",
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"lognormal",
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"logseries",
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"multinomial",
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"multivariate_normal",
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"negative_binomial",
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"normal",
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"noncentral_chisquare",
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"noncentral_f",
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"pareto",
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"permutation",
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"poisson",
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"power",
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"rand",
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"randint",
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"randn",
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"random",
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"random_integers",
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"random_sample",
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"ranf",
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"rayleigh",
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"sample",
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"shuffle",
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"seed",
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"standard_cauchy",
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"standard_exponential",
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"standard_gamma",
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"standard_normal",
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"standard_t",
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"triangular",
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"uniform",
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"vonmises",
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"wald",
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"weibull",
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"zipf",
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"RandomState",
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]

‎dpnp/random/dpnp_iface_random.py‎

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from .dpnp_algo_random import *
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from .dpnp_random_state import RandomState
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__all__ = [
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"beta",
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"binomial",
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"bytes",
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"chisquare",
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"choice",
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"dirichlet",
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"exponential",
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"f",
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"gamma",
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"geometric",
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"gumbel",
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"hypergeometric",
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"laplace",
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"logistic",
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"lognormal",
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"logseries",
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"multinomial",
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"multivariate_normal",
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"negative_binomial",
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"normal",
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"noncentral_chisquare",
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"noncentral_f",
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"pareto",
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"permutation",
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"poisson",
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"power",
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"rand",
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"randint",
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"randn",
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"random",
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"random_integers",
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"random_sample",
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"ranf",
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"rayleigh",
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"sample",
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"shuffle",
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"seed",
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"standard_cauchy",
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"standard_exponential",
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"standard_gamma",
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"standard_normal",
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"standard_t",
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"triangular",
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"uniform",
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"vonmises",
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"wald",
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"weibull",
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"zipf",
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]
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def _get_random_state(device=None, sycl_queue=None):
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global _dpnp_random_states

‎dpnp/random/dpnp_random_state.py‎

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)
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from dpnp.random.dpnp_algo_random import MCG59, MT19937
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__all__ = ["RandomState"]
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class RandomState:
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"""

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