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from __future__ import annotations
import cupy as cp
import pytest
import awkward as ak
to_list = ak.operations.to_list
@pytest.fixture(scope="function", autouse=True)
def cleanup_cuda():
yield
cp._default_memory_pool.free_all_blocks()
cp.cuda.Device().synchronize()
def test_0835_argmin_argmax_axis_None():
array = ak.highlevel.Array(
[
[
[2022, 2023, 2025],
[],
[2027, 2011],
[2013],
],
[],
[[2017, 2019], [2023]],
],
)
cuda_array = ak.to_backend(array, "cuda")
assert ak.operations.argmin(cuda_array) == 4
assert ak.operations.argmax(cuda_array) == 3
def test_1106_argminmax_axis_None_missing_values():
array = ak.highlevel.Array([1, 2, 3, None, 4])
cuda_array = ak.to_backend(array, "cuda")
assert ak.operations.argmax(cuda_array) == 4
def test_0070_argmin_and_argmax_jagged():
v2_array = ak.operations.from_iter(
[[2.2, 1.1, 3.3], [], [4.4, 5.5], [5.5], [-4.4, -5.5, -6.6]], highlevel=False
)
cuda_v2_array = ak.to_backend(v2_array, "cuda", highlevel=False)
assert to_list(ak.argmin(cuda_v2_array, axis=1, highlevel=False)) == [
1,
None,
0,
0,
2,
]
assert (
ak.argmin(cuda_v2_array.to_typetracer(), axis=1, highlevel=False).form
== ak.argmin(cuda_v2_array, axis=1, highlevel=False).form
)
index2 = ak.index.Index64(cp.array([4, 3, 2, 1, 0], dtype=cp.int64))
cuda_v2_array2 = ak.contents.IndexedArray(index2, cuda_v2_array)
assert to_list(ak.argmin(cuda_v2_array2, axis=1, highlevel=False)) == [
2,
0,
0,
None,
1,
]
assert (
ak.argmin(cuda_v2_array2.to_typetracer(), axis=1, highlevel=False).form
== ak.argmin(cuda_v2_array2, axis=1, highlevel=False).form
)
index3 = ak.index.Index64(cp.array([4, 3, -1, 4, 0], dtype=cp.int64))
cuda_v2_array2 = ak.contents.IndexedOptionArray(index3, cuda_v2_array)
assert to_list(ak.argmin(cuda_v2_array2, axis=1, highlevel=False)) == [
2,
0,
None,
2,
1,
]
assert (
ak.argmin(cuda_v2_array2.to_typetracer(), axis=1, highlevel=False).form
== ak.argmin(cuda_v2_array2, axis=1, highlevel=False).form
)
assert to_list(ak.argmin(cuda_v2_array2, axis=-1, highlevel=False)) == [
2,
0,
None,
2,
1,
]
assert (
ak.argmin(cuda_v2_array2.to_typetracer(), axis=-1, highlevel=False).form
== ak.argmin(cuda_v2_array2, axis=-1, highlevel=False).form
)
def test_0070_argmin_and_argmax_missing():
array = ak.operations.from_iter(
[[[2.2, 1.1, 3.3]], [[]], [None, None, None], [[-4.4, -5.5, -6.6]]],
highlevel=False,
)
cuda_array = ak.to_backend(array, "cuda", highlevel=False)
assert to_list(ak.argmin(cuda_array, axis=2, highlevel=False)) == [
[1],
[None],
[None, None, None],
[2],
]
assert (
ak.argmin(cuda_array.to_typetracer(), axis=2, highlevel=False).form
== ak.argmin(cuda_array, axis=2, highlevel=False).form
)
def test_0115_generic_reducer_operation_ByteMaskedArray():
content = ak.operations.from_iter(
[
[[1.1, 0.0, 2.2], [], [3.3, 4.4]],
[],
[[5.5]],
[[6.6, 9.9, 8.8, 7.7]],
[[], [12.2, 11.1, 10.0]],
],
highlevel=False,
)
mask = ak.index.Index8(cp.array([0, 0, 1, 1, 0], dtype=cp.int8))
content = ak.to_backend(content, "cuda", highlevel=False)
cuda_v2_array = ak.contents.ByteMaskedArray(mask, content, valid_when=False)
assert to_list(cuda_v2_array) == [
[[1.1, 0.0, 2.2], [], [3.3, 4.4]],
[],
None,
None,
[[], [12.2, 11.1, 10.0]],
]
assert to_list(ak.argmin(cuda_v2_array, axis=-1, highlevel=False)) == [
[1, None, 0],
[],
None,
None,
[None, 2],
]
assert (
ak.argmin(cuda_v2_array.to_typetracer(), axis=-1, highlevel=False).form
== ak.argmin(cuda_v2_array, axis=-1, highlevel=False).form
)
@pytest.mark.parametrize(
"func",
[
ak.argmin,
ak.argmax,
],
)
def test_2754_highlevel_behavior_missing_reducers(func):
behavior_1 = {"foo": "bar"}
behavior_2 = {"baz": "bargh!"}
array = ak.Array([[1, 2, 3, 4], [5], [10]])
cuda_array = ak.to_backend(array, "cuda")
assert isinstance(func(cuda_array, axis=1, highlevel=True), ak.Array)
assert isinstance(func(cuda_array, axis=1, highlevel=False), ak.contents.Content)
assert (
func(
ak.Array(cuda_array, behavior=behavior_1),
axis=1,
highlevel=True,
behavior=behavior_2,
).behavior
== behavior_2
)
assert (
func(
ak.Array(cuda_array, behavior=behavior_1),
axis=1,
highlevel=True,
).behavior
== behavior_1
)
|
