8000 API: Add device and to_device to ndarray · numpy/numpy@dc7848e · GitHub
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API: Add device and to_device to ndarray
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‎doc/release/upcoming_changes/25233.new_feature.rst

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``ndarray.device`` and ``ndarray.to_device``
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--------------------------------------------
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``ndarray.device`` attribute and ``ndarray.to_device`` function were
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added to `numpy.ndarray` class for Array API compatibility.
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Additionally, ``device`` keyword-only arguments were added to:
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`numpy.asarray`, `numpy.arange`, `numpy.empty`, `numpy.empty_like`,
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`numpy.eye`, `numpy.full`, `numpy.full_like`, `numpy.linspace`,
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`numpy.ones`, `numpy.ones_like`, `numpy.zeros`, and `numpy.zeros_like`.

‎doc/source/reference/array_api.rst

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@@ -517,12 +517,6 @@ Creation functions differences
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* - ``copy`` keyword argument to ``asarray``
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- **Compatible**
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-
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* - New ``device`` keyword argument to all array creation functions
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(``asarray``, ``arange``, ``empty``, ``empty_like``, ``eye``, ``full``,
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``full_like``, ``linspace``, ``ones``, ``ones_like``, ``zeros``, and
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``zeros_like``).
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- **Compatible**
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- ``device`` would effectively do nothing, since NumPy is CPU only.
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Elementwise functions differences
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---------------------------------

‎numpy/__init__.pyi

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@@ -2470,6 +2470,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]):
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def __array_namespace__(self, *, api_version: str = ...) -> Any: ...
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def to_device(self, device: L["cpu"], /, *, stream: None | int | Any = ...) -> NDArray[Any]: ...
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@property
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def device(self) -> L["cpu"]: ...
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def bitwise_count(
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self,
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out: None | NDArray[Any] = ...,

‎numpy/_core/_add_newdocs.py

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@@ -912,7 +912,7 @@
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add_newdoc('numpy._core.multiarray', 'asarray',
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"""
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asarray(a, dtype=None, order=None, *, like=None)
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asarray(a, dtype=None, order=None, *, device=None, like=None)
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Convert the input to an array.
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'A' (any) means 'F' if `a` is Fortran contiguous, 'C' otherwise
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'K' (keep) preserve input order
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Defaults to 'K'.
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device : str, optional
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The device on which to place the created array. Default: None.
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.. note::
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Only the ``"cpu"`` device is supported by NumPy.
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.. versionadded:: 2.0.0
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${ARRAY_FUNCTION_LIKE}
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.. versionadded:: 1.20.0
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add_newdoc('numpy._core.multiarray', 'empty',
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"""
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empty(shape, dtype=float, order='C', *, like=None)
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empty(shape, dtype=float, order='C', *, device=None, like=None)
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Return a new array of given shape and type, without initializing entries.
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Whether to store multi-dimensional data in row-major
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(C-style) or column-major (Fortran-style) order in
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memory.
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device : str, optional
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The device on which to place the created array. Default: None.
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.. note::
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Only the ``"cpu"`` device is supported by NumPy.
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.. versionadded:: 2.0.0
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${ARRAY_FUNCTION_LIKE}
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.. versionadded:: 1.20.0
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add_newdoc('numpy._core.multiarray', 'arange',
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"""
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arange([start,] stop[, step,], dtype=None, *, like=None)
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arange([start,] stop[, step,], dtype=None, *, device=None, like=None)
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Return evenly spaced values within a given interval.
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dtype : dtype, optional
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The type of the output array. If `dtype` is not given, infer the data
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type from the other input arguments.
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device : str, optional
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The device on which to place the created array. Default: None.
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.. note::
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Only the ``"cpu"`` device is supported by NumPy.
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.. versionadded:: 2.0.0
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${ARRAY_FUNCTION_LIKE}
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.. versionadded:: 1.20.0

‎numpy/_core/function_base.py

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def _linspace_dispatcher(start, stop, num=None, endpoint=None, retstep=None,
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dtype=None, axis=None):
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dtype=None, axis=None, *, device=None):
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return (start, stop)
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@array_function_dispatch(_linspace_dispatcher)
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def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None,
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axis=0):
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axis=0, *, device=None):
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"""
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Return evenly spaced numbers over a specified interval.
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array of integers.
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.. versionadded:: 1.9.0
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axis : int, optional
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The axis in the result to store the samples. Relevant only if start
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or stop are array-like. By default (0), the samples will be along a
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new axis inserted at the beginning. Use -1 to get an axis at the end.
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.. versionadded:: 1.16.0
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device : str, optional
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The device on which to place the created array. Default: None.
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.. note::
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Only the ``"cpu"`` device is supported by NumPy.
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.. versionadded:: 2.0.0
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Returns
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-------
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>>> plt.show()
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"""
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if device not in ["cpu", None]:
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raise ValueError(
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f"Unsupported device: {device}. Only \"cpu\" is allowed."
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)
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num = operator.index(num)
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if num < 0:
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raise ValueError(

‎numpy/_core/function_base.pyi

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@@ -28,6 +28,8 @@ def linspace(
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retstep: L[False] = ...,
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dtype: None = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> NDArray[floating[Any]]: ...
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@overload
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def linspace(
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retstep: L[False] = ...,
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dtype: None = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> NDArray[complexfloating[Any, Any]]: ...
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@overload
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def linspace(
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retstep: L[False] = ...,
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dtype: _DTypeLike[_SCT] = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def linspace(
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retstep: L[False] = ...,
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dtype: DTypeLike = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> NDArray[Any]: ...
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@overload
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def linspace(
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retstep: L[True] = ...,
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dtype: None = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> tuple[NDArray[floating[Any]], floating[Any]]: ...
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@overload
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def linspace(
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retstep: L[True] = ...,
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dtype: None = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> tuple[NDArray[complexfloating[Any, Any]], complexfloating[Any, Any]]: ...
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@overload
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def linspace(
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retstep: L[True] = ...,
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dtype: _DTypeLike[_SCT] = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> tuple[NDArray[_SCT], _SCT]: ...
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@overload
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def linspace(
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retstep: L[True] = ...,
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dtype: DTypeLike = ...,
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axis: SupportsIndex = ...,
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*,
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device: None | L["cpu"] = ...,
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) -> tuple[NDArray[Any], Any]: ...
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@overload

‎numpy/_core/include/numpy/ndarraytypes.h

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NPY_BUSDAY_RAISE
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/* Device enum for Array API compatibility */
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typedef enum {
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NPY_DEVICE_CPU = 0,
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} NPY_DEVICE;
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/************************************************************
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* NumPy Auxiliary Data for inner loops, sort functions, etc.
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************************************************************/

‎numpy/_core/multiarray.py

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@array_function_from_c_func_and_dispatcher(_multiarray_umath.empty_like)
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def empty_like(prototype, dtype=None, order=None, subok=None, shape=None):
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def empty_like(
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prototype, dtype=None, order=None, subok=None, shape=None, *, device=None
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):
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"""
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empty_like(prototype, dtype=None, order='K', subok=True, shape=None)
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empty_like(prototype, dtype=None, order='K', subok=True, shape=None,
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shape=None, *, device=None)
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Return a new array with the same shape and type as a given array.
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order='C' is implied.
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.. versionadded:: 1.17.0
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device : str, optional
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The device on which to place the created array. Default: None.
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.. note::
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Only the ``"cpu"`` device is supported by NumPy.
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.. versionadded:: 2.0.0
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Returns
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-------

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