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