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ENH: allow_dask_compute=True instead of 999 #283

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Merged
merged 1 commit into from
Apr 25, 2025
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ENH: allow_dask_compute=True instead of 999 #283

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18 changes: 13 additions & 5 deletions src/array_api_extra/testing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ def override(func: object) -> object:
def lazy_xp_function( # type: ignore[explicit-any]
func: Callable[..., Any],
*,
allow_dask_compute: int = 0,
allow_dask_compute: bool | int = False,
jax_jit: bool = True,
static_argnums: int | Sequence[int] | None = None,
static_argnames: str | Iterable[str] | None = None,
Expand All @@ -59,9 +59,10 @@ def lazy_xp_function( # type: ignore[explicit-any]
----------
func : callable
Function to be tested.
allow_dask_compute : int, optional
Number of times `func` is allowed to internally materialize the Dask graph. This
is typically triggered by ``bool()``, ``float()``, or ``np.asarray()``.
allow_dask_compute : bool | int, optional
Whether `func` is allowed to internally materialize the Dask graph, or maximum
number of times it is allowed to do so. This is typically triggered by
``bool()``, ``float()``, or ``np.asarray()``.

Set to 1 if you are aware that `func` converts the input parameters to NumPy and
want to let it do so at least for the time being, knowing that it is going to be
Expand All @@ -75,7 +76,10 @@ def lazy_xp_function( # type: ignore[explicit-any]
a test function that invokes `func` multiple times should still work with this
parameter set to 1.

Default: 0, meaning that `func` must be fully lazy and never materialize the
Set to True to allow `func` to materialize the graph an unlimited number
of times.

Default: False, meaning that `func` must be fully lazy and never materialize the
graph.
jax_jit : bool, optional
Set to True to replace `func` with ``jax.jit(func)`` after calling the
Expand Down Expand Up @@ -235,6 +239,10 @@ def iter_tagged() -> ( # type: ignore[explicit-any]
if is_dask_namespace(xp):
for mod, name, func, tags in iter_tagged():
n = tags["allow_dask_compute"]
if n is True:
n = 1_000_000
elif n is False:
n = 0
wrapped = _dask_wrap(func, n)
monkeypatch.setattr(mod, name, wrapped)

Expand Down
20 changes: 13 additions & 7 deletions tests/test_testing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -130,13 +130,18 @@ def non_materializable4(x: Array) -> Array:
return non_materializable(x)


def non_materializable5(x: Array) -> Array:
return non_materializable(x)


lazy_xp_function(good_lazy)
# Works on JAX and Dask
lazy_xp_function(non_materializable2, jax_jit=False, allow_dask_compute=2)
lazy_xp_function(non_materializable3, jax_jit=False, allow_dask_compute=True)
# Works on JAX, but not Dask
lazy_xp_function(non_materializable3, jax_jit=False, allow_dask_compute=1)
lazy_xp_function(non_materializable4, jax_jit=False, allow_dask_compute=1)
# Works neither on Dask nor JAX
lazy_xp_function(non_materializable4)
lazy_xp_function(non_materializable5)


def test_lazy_xp_function(xp: ModuleType):
Expand All @@ -147,29 +152,30 @@ def test_lazy_xp_function(xp: ModuleType):
xp_assert_equal(non_materializable(x), xp.asarray([1.0, 2.0]))
# Wrapping explicitly disabled
xp_assert_equal(non_materializable2(x), xp.asarray([1.0, 2.0]))
xp_assert_equal(non_materializable3(x), xp.asarray([1.0, 2.0]))

if is_jax_namespace(xp):
xp_assert_equal(non_materializable3(x), xp.asarray([1.0, 2.0]))
xp_assert_equal(non_materializable4(x), xp.asarray([1.0, 2.0]))
with pytest.raises(
TypeError, match="Attempted boolean conversion of traced array"
):
_ = non_materializable4(x) # Wrapped
_ = non_materializable5(x) # Wrapped

elif is_dask_namespace(xp):
with pytest.raises(
AssertionError,
match=r"dask\.compute.* 2 times, but only up to 1 calls are allowed",
):
_ = non_materializable3(x)
_ = non_materializable4(x)
with pytest.raises(
AssertionError,
match=r"dask\.compute.* 1 times, but no calls are allowed",
):
_ = non_materializable4(x)
_ = non_materializable5(x)

else:
xp_assert_equal(non_materializable3(x), xp.asarray([1.0, 2.0]))
xp_assert_equal(non_materializable4(x), xp.asarray([1.0, 2.0]))
xp_assert_equal(non_materializable5(x), xp.asarray([1.0, 2.0]))


def static_params(x: Array, n: int, flag: bool = False) -> Array:
Expand Down