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import numpy |
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from cupy import cuda |
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from cupy._creation.basic import _new_like_order_and_strides |
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from cupy._core import internal |
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def _update_shape(a, shape): |
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if shape is None and a is not None: |
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shape = a.shape |
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elif isinstance(shape, int): |
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shape = (shape,) |
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else: |
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shape = tuple(shape) |
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return shape |
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def empty_pinned(shape, dtype=float, order='C'): |
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"""Returns a new, uninitialized NumPy array with the given shape |
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and dtype. |
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This is a convenience function which is just :func:`numpy.empty`, |
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except that the underlying memory is pinned/pagelocked. |
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Args: |
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shape (int or tuple of ints): Dimensionalities of the array. |
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dtype: Data type specifier. |
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order ({'C', 'F'}): Row-major (C-style) or column-major |
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(Fortran-style) order. |
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Returns: |
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numpy.ndarray: A new array with elements not initialized. |
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.. seealso:: :func:`numpy.empty` |
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""" |
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shape = _update_shape(None, shape) |
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nbytes = internal.prod(shape) * numpy.dtype(dtype).itemsize |
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mem = cuda.alloc_pinned_memory(nbytes) |
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out = numpy.ndarray(shape, dtype=dtype, buffer=mem, order=order) |
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return out |
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def empty_like_pinned(a, dtype=None, order='K', subok=None, shape=None): |
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"""Returns a new, uninitialized NumPy array with the same shape and dtype |
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as those of the given array. |
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This is a convenience function which is just :func:`numpy.empty_like`, |
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except that the underlying memory is pinned/pagelocked. |
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This function currently does not support ``subok`` option. |
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Args: |
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a (numpy.ndarray or cupy.ndarray): Base array. |
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dtype: Data type specifier. The data type of ``a`` is used by default. |
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order ({'C', 'F', 'A', or 'K'}): Overrides the memory layout of the |
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result. ``'C'`` means C-order, ``'F'`` means F-order, ``'A'`` means |
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``'F'`` if ``a`` is Fortran contiguous, ``'C'`` otherwise. |
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``'K'`` means match the layout of ``a`` as closely as possible. |
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subok: Not supported yet, must be None. |
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shape (int or tuple of ints): Overrides the shape of the result. If |
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``order='K'`` and the number of dimensions is unchanged, will try |
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to keep order, otherwise, ``order='C'`` is implied. |
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Returns: |
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numpy.ndarray: A new array with same shape and dtype of ``a`` with |
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elements not initialized. |
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.. seealso:: :func:`numpy.empty_like` |
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""" |
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if subok is not None: |
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raise TypeError('subok is not supported yet') |
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if dtype is None: |
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dtype = a.dtype |
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shape = _update_shape(a, shape) |
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order, strides, _ = _new_like_order_and_strides( |
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a, dtype, order, shape, get_memptr=False) |
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nbytes = internal.prod(shape) * numpy.dtype(dtype).itemsize |
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mem = cuda.alloc_pinned_memory(nbytes) |
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out = numpy.ndarray(shape, dtype=dtype, buffer=mem, |
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strides=strides, order=order) |
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return out |
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def zeros_pinned(shape, dtype=float, order='C'): |
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"""Returns a new, zero-initialized NumPy array with the given shape |
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and dtype. |
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This is a convenience function which is just :func:`numpy.zeros`, |
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except that the underlying memory is pinned/pagelocked. |
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Args: |
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shape (int or tuple of ints): Dimensionalities of the array. |
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dtype: Data type specifier. |
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order ({'C', 'F'}): Row-major (C-style) or column-major |
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(Fortran-style) order. |
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Returns: |
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numpy.ndarray: An array filled with zeros. |
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.. seealso:: :func:`numpy.zeros` |
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""" |
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out = empty_pinned(shape, dtype, order) |
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numpy.copyto(out, 0, casting='unsafe') |
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return out |
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def zeros_like_pinned(a, dtype=None, order='K', subok=None, shape=None): |
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"""Returns a new, zero-initialized NumPy array with the same shape and dtype |
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as those of the given array. |
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This is a convenience function which is just :func:`numpy.zeros_like`, |
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except that the underlying memory is pinned/pagelocked. |
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This function currently does not support ``subok`` option. |
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Args: |
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a (numpy.ndarray or cupy.ndarray): Base array. |
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dtype: Data type specifier. The dtype of ``a`` is used by default. |
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order ({'C', 'F', 'A', or 'K'}): Overrides the memory layout of the |
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result. ``'C'`` means C-order, ``'F'`` means F-order, ``'A'`` means |
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``'F'`` if ``a`` is Fortran contiguous, ``'C'`` otherwise. |
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``'K'`` means match the layout of ``a`` as closely as possible. |
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subok: Not supported yet, must be None. |
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shape (int or tuple of ints): Overrides the shape of the result. If |
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``order='K'`` and the number of dimensions is unchanged, will try |
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to keep order, otherwise, ``order='C'`` is implied. |
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Returns: |
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numpy.ndarray: An array filled with zeros. |
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.. seealso:: :func:`numpy.zeros_like` |
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""" |
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out = empty_like_pinned(a, dtype, order, subok, shape) |
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numpy.copyto(out, 0, casting='unsafe') |
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return out |
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