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Merge pull request #1586 from IntelPython/implement_tile
Implemented dpnp.tile function.
2 parents a73d959 + aae4cff commit 4850e53

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‎dpnp/dpnp_iface_manipulation.py

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@@ -73,6 +73,7 @@
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"squeeze",
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"stack",
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"swapaxes",
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"tile",
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"transpose",
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"unique",
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"vstack",
@@ -945,7 +946,7 @@ def reshape(a, /, newshape, order="C", copy=None):
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Parameters
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----------
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a : {dpnp_array, usm_ndarray}
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a : {dpnp.ndarray, usm_ndarray}
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Array to be reshaped.
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newshape : int or tuple of ints
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The new shape should be compatible with the original shape. If
@@ -1387,6 +1388,84 @@ def swapaxes(a, axis1, axis2):
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)
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def tile(A, reps):
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"""
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Construct an array by repeating `A` the number of times given by reps.
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If `reps` has length ``d``, the result will have dimension of
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``max(d, A.ndim)``.
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If ``A.ndim < d``, `A` is promoted to be d-dimensional by prepending new
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axes. So a shape (3,) array is promoted to (1, 3) for 2-D replication,
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or shape (1, 1, 3) for 3-D replication. If this is not the desired
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behavior, promote `A` to d-dimensions manually before calling this
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function.
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If ``A.ndim > d``, `reps` is promoted to `A`.ndim by prepending 1's to it.
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Thus for an `A` of shape (2, 3, 4, 5), a `reps` of (2, 2) is treated as
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(1, 1, 2, 2).
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Note : Although tile may be used for broadcasting, it is strongly
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recommended to use dpnp's broadcasting operations and functions.
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For full documentation refer to :obj:`numpy.tile`.
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Parameters
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----------
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A : dpnp.ndarray
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The input array.
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reps : array_like
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The number of repetitions of `A` along each axis.
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Returns
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-------
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c : dpnp.ndarray
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The tiled output array.
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See Also
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--------
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:obj:`dpnp.repeat` : Repeat elements of an array.
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:obj:`dpnp.broadcast_to` : Broadcast an array to a new shape
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Examples
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--------
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>>> import dpnp as np
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>>> a = np.array([0, 1, 2])
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>>> np.tile(a, 2)
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array([0, 1, 2, 0, 1, 2])
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>>> np.tile(a, (2, 2))
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array([[0, 1, 2, 0, 1, 2],
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[0, 1, 2, 0, 1, 2]])
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>>> np.tile(a, (2, 1, 2))
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array([[[0, 1, 2, 0, 1, 2]],
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[[0, 1, 2, 0, 1, 2]]])
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>>> b = np.array([[1, 2], [3, 4]])
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>>> np.tile(b, 2)
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array([[1, 2, 1, 2],
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[3, 4, 3, 4]])
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>>> np.tile(b, (2, 1))
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array([[1, 2],
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[3, 4],
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[1, 2],
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[3, 4]])
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>>> c = np.array([1, 2, 3, 4])
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>>> np.tile(c, (4, 1))
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array([[1, 2, 3, 4],
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[1, 2, 3, 4],
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[1, 2, 3, 4],
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[1, 2, 3, 4]])
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"""
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dpt_array = dpnp.get_usm_ndarray(A)
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return dpnp_array._create_from_usm_ndarray(dpt.tile(dpt_array, reps))
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def transpose(a, axes=None):
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"""
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Returns an array with axes transposed.

‎tests/skipped_tests.tbl

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@@ -468,14 +468,6 @@ tests/third_party/cupy/manipulation_tests/test_shape.py::TestReshape::test_resha
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestRepeatRepeatsNdarray::test_func
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestRepeatRepeatsNdarray::test_method
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTileFailure_param_0_{reps=-1}::test_tile_failure
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTileFailure_param_1_{reps=(-1, -2)}::test_tile_failure
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_0_{reps=0}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_1_{reps=1}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_2_{reps=2}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_3_{reps=(0, 1)}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_4_{reps=(2, 3)}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_5_{reps=(2, 3, 4, 5)}::test_array_tile
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tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_457_{arg1=array([[1, 2, 3], [4, 5, 6]], dtype=int32), arg2=array([[0, 1, 2], [3, 4, 5]], dtype=int32), dtype=float64, name='fmod', use_dtype=False}::test_binary
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tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_465_{arg1=array([[1, 2, 3], [4, 5, 6]], dtype=int32), arg2=array([[0, 1, 2], [3, 4, 5]]), dtype=float64, name='fmod', use_dtype=False}::test_binary
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tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_537_{arg1=array([[1, 2, 3], [4, 5, 6]]), arg2=array([[0, 1, 2], [3, 4, 5]], dtype=int32), dtype=float64, name='fmod', use_dtype=False}::test_binary

‎tests/skipped_tests_gpu.tbl

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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestRepeatRepeatsNdarray::test_func
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestRepeatRepeatsNdarray::test_method
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTileFailure_param_0_{reps=-1}::test_tile_failure
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTileFailure_param_1_{reps=(-1, -2)}::test_tile_failure
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_0_{reps=0}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_1_{reps=1}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_2_{reps=2}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_3_{reps=(0, 1)}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_4_{reps=(2, 3)}::test_array_tile
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tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_5_{reps=(2, 3, 4, 5)}::test_array_tile
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tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticRaisesWithNumpyInput_param_3_{name='angle', nargs=1}::test_raises_with_numpy_input
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