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test_1276_cuda_num.py
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# BSD 3-Clause License; see https://github.com/scikit-hep/awkward/blob/main/LICENSE
from __future__ import annotations
import cupy as cp # noqa: F401
import numpy as np
import pytest
import awkward as ak
try:
ak.numba.register_and_check()
except ImportError:
pytest.skip(reason="too old Numba version", allow_module_level=True)
def test_num_1():
content = ak.Array(
["one", "two", "three", "four", "five", "six", "seven", "eight", "nine"]
).layout
bitmask = ak.index.IndexU8(np.array([40, 34], dtype=np.uint8))
array = ak.Array(
ak.contents.bitmaskedarray.BitMaskedArray(bitmask, content, False, 9, False)
)
cuda_array = ak.to_backend(array, "cuda")
assert ak.num(cuda_array, 0) == ak.num(array, 0)
def test_num_2():
content = ak.Array(
["one", "two", "three", "four", "five", "six", "seven", "eight", "nine"]
).layout
bytemask = ak.index.Index8(np.array([False, True, False], dtype=bool))
array = ak.Array(
ak.contents.bytemaskedarray.ByteMaskedArray(bytemask, content, True)
)
cuda_array = ak.to_backend(array, "cuda")
assert ak.num(cuda_array, 0) == ak.num(array, 0)
def test_num_3():
array = ak.Array(
ak.contents.numpyarray.NumpyArray(np.array([0.0, 1.1, 2.2, 3.3, 4.4, 5.5]))
)
cuda_array = ak.to_backend(array, "cuda")
assert ak.num(cuda_array, 0) == ak.num(array, 0)
def test_num_4():
array = ak.Array(
ak.contents.numpyarray.NumpyArray(
np.array([[0.0, 1.1], [2.2, 3.3], [4.4, 5.5]])
)
)
cuda_array = ak.to_backend(array, "cuda")
assert ak.num(cuda_array, 0) == ak.num(array, 0)
assert ak.num(cuda_array, 1).tolist() == ak.num(array, 1).tolist()
def test_num_5():
array = ak.Array(ak.contents.EmptyArray())
cuda_array = ak.to_backend(array, "cuda")
assert ak.num(cuda_array, 0) == ak.num(array, 0)
def test_num_6():
content = ak.contents.numpyarray.NumpyArray(
np.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
)
offsets = ak.index.Index64(np.array([0, 3, 3, 5, 6, 9]))
array = ak.Array(ak.contents.listoffsetarray.ListOffsetArray(offsets, content))
cuda_array = ak.to_backend(array, "cuda")
assert ak.num(cuda_array, 0) == ak.num(array, 0)
assert ak.num(cuda_array, 1).tolist() == ak.num(array, 1).tolist()
def test_num_7():
content = ak.contents.numpyarray.NumpyArray(
np.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
)
offsets = ak.index.IndexU32(np.array([0, 3, 3, 5, 6, 9]))
array = ak.Array(ak.contents.listoffsetarray.ListOffsetArray(offsets, content))
cuda_array = ak.to_backend(array, "cuda")
assert ak.num(cuda_array, 0) == ak.num(array, 0)
assert ak.num(cuda_array, 1).tolist() == ak.num(array, 1).tolist()
def test_num_8():
content = ak.contents.numpyarray.NumpyArray(
np.array([0.0, 1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9, 10.10])
)
offsets = ak.index.Index64(np.array([0, 3, 3, 5, 6, 10, 10]))
listoffsetarray = ak.contents.listoffsetarray.ListOffsetArray(offsets, content)
regulararray = ak.contents.regulararray.RegularArray(listoffsetarray, 2)
starts = ak.index.Index64(np.array([0, 1]))
stops = ak.index.Index64(np.array([2, 3]))
listarray = ak.contents.listarray.ListArray(starts, stops, regulararray)
cuda_listoffsetarray = ak.to_backend(listoffsetarray, "cuda")
assert ak.num(cuda_listoffsetarray, 0) == ak.num(ak.Array(listoffsetarray), 0)
assert (
ak.num(cuda_listoffsetarray, 1).tolist()
== ak.num(ak.Array(listoffsetarray), 1).tolist()
)
cuda_regulararray = ak.to_backend(regulararray, "cuda")
assert ak.num(cuda_regulararray, 0) == ak.num(ak.Array(regulararray), 0)
assert (
ak.num(cuda_regulararray, 1).tolist()
== ak.num(ak.Array(regulararray), 1).tolist()
)
cuda_listarray = ak.to_backend(listarray, "cuda")
assert ak.num(cuda_listarray, 0) == ak.num(ak.Array(listarray), 0)
assert ak.num(cuda_listarray, 1).tolist() == ak.num(ak.Array(listarray), 1).tolist()
content1 = ak.contents.numpyarray.NumpyArray(np.array([1, 2, 3, 4, 5]))
content2 = ak.contents.numpyarray.NumpyArray(
np.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
)
offsets = ak.index.Index32(np.array([0, 3, 3, 5, 6, 9]))
recordarray = ak.Array(
ak.contents.recordarray.RecordArray(
[content1, listoffsetarray, content2, content1],
fields=["one", "two", "2", "wonky"],
)
)
cuda_recordarray = ak.to_backend(recordarray, "cuda")
assert ak.num(cuda_recordarray, 0) == ak.num(recordarray, 0)
content0 = ak.Array([[1.1, 2.2, 3.3], [], [4.4, 5.5]]).layout
content1 = ak.Array(
["one", "two", "three", "four", "five", "six", "seven", "eight", "nine"]
).layout
tags = ak.index.Index8(np.array([1, 1, 0, 0, 1, 0, 1, 1], dtype=np.int8))
index = ak.index.Index32(np.array([0, 1, 0, 1, 2, 2, 4, 3], dtype=np.int32))
unionarray = ak.Array(
ak.contents.unionarray.UnionArray(tags, index, [content0, content1])
)
cuda_unionarray = ak.to_backend(unionarray, "cuda")
assert ak.num(cuda_unionarray, 0) == ak.num(unionarray, 0)
def test_num_9():
content = ak.contents.numpyarray.NumpyArray(
np.array([0.0, 1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
)
index = ak.index.Index32(np.array([0, 2, 4, 6, 8, 9, 7, 5], dtype=np.int64))
indexedarray = ak.Array(ak.contents.indexedarray.IndexedArray(index, content))
cuda_indexedarray = ak.to_backend(indexedarray, "cuda")
assert ak.num(cuda_indexedarray, 0) == ak.num(indexedarray, 0)
ioa = ak.Array(
ak.contents.indexedoptionarray.IndexedOptionArray(
ak.index.Index32([-30, 19, 6, 7, -3, 21, 13, 22, 17, 9, -12, 16]),
ak.contents.numpyarray.NumpyArray(
np.array(
[
5.2,
1.7,
6.7,
-0.4,
4.0,
7.8,
3.8,
6.8,
4.2,
0.3,
4.6,
6.2,
6.9,
-0.7,
3.9,
1.6,
8.7,
-0.7,
3.2,
4.3,
4.0,
5.8,
4.2,
7.0,
5.6,
3.8,
]
)
),
)
)
cuda_ioa = ak.to_backend(ioa, "cuda")
assert ak.num(cuda_ioa, 0) == ak.num(ioa, 0)