fix

Author: crusaderky

src/array_api_extra/testing.py

@@ -143,7 +143,7 @@ def test_myfunc(xp):
     }
     try:
         func._lazy_xp_function = tags  # type: ignore[attr-defined]  # pylint: disable=protected-access  # pyright: ignore[reportFunctionMemberAccess]
-    except AttributeError:  # numpy.ufunc
+    except AttributeError:  # @cython.vectorize
         _ufuncs_tags[func] = tags
 
 

tests/test_testing.py

@@ -3,7 +3,6 @@
 
 import numpy as np
 import pytest
-from numpy import min as numpy_min
 
 from array_api_extra._lib import Backend
 from array_api_extra._lib._testing import xp_assert_close, xp_assert_equal
@@ -205,21 +204,30 @@ def test_lazy_xp_function_static_params(xp: ModuleType, func: Callable[..., Arra
     xp_assert_equal(func(x, n=1, flag=True), xp.asarray([2.0, 4.0]))
 
 
-lazy_xp_function(numpy_min, static_argnames="axis")
+try:
+    # Test an arbitrary Cython ufunc (@cython.vectorize).
+    # When SCIPY_ARRAY_API is not set, this is the same as
+    # scipy.special.erf.
+    from scipy.special._ufuncs import erf  # type: ignore[import-not-found]
 
+    lazy_xp_function(erf)  # pyright: ignore[reportUnknownArgumentType]
+except ImportError:
+    erf = None
 
-def test_lazy_xp_function_ufunc(xp: ModuleType, library: Backend):
-    x = xp.asarray([[1, 4], [3, 2]])
-    if library in (Backend.ARRAY_API_STRICT, Backend.TORCH, Backend.JAX):
-        # array-api-strict, torch and jax don't define __array_ufunc__
-        # numpy ufuncs can't auto-convert to numpy from torch
+
+@pytest.mark.filterwarnings("ignore:__array_wrap__:DeprecationWarning")  # torch
+def test_lazy_xp_function_cython_ufuncs(xp: ModuleType, library: Backend):
+    pytest.importorskip("scipy")
+    assert erf is not None
+    x = xp.asarray([6.0, 7.0])
+    if library in (Backend.ARRAY_API_STRICT, Backend.JAX):
         # array-api-strict arrays are auto-converted to numpy
         # eager jax arrays are auto-converted to numpy in eager jax
         # and fail in jax.jit (which lazy_xp_function tests here)
         with pytest.raises((TypeError, AssertionError)):
-            xp_assert_equal(numpy_min(x, axis=0), xp.asarray([1, 2]))
+            xp_assert_equal(erf(x), xp.asarray([1.0, 1.0]))
     else:
         # cupy, dask and sparse define __array_ufunc__ and dispatch accordingly
         # note that when sparse reduces to scalar it returns a np.generic, which
         # would make xp_assert_equal fail.
-        xp_assert_equal(numpy_min(x, axis=0), xp.asarray([1, 2]))
+        xp_assert_equal(erf(x), xp.asarray([1.0, 1.0]))