TST: re-enable xpassing JAX tests

Author: lucascolley

tests/test_funcs.py

@@ -39,10 +39,9 @@
 )
 from array_api_extra._lib._backends import NUMPY_VERSION, Backend
 from array_api_extra._lib._funcs import searchsorted as _funcs_searchsorted
-from array_api_extra._lib._testing import xfail, xp_assert_close, xp_assert_equal
+from array_api_extra._lib._testing import xp_assert_close, xp_assert_equal
 from array_api_extra._lib._utils._compat import (
     array_namespace,
-    is_jax_namespace,
     is_torch_namespace,
 )
 from array_api_extra._lib._utils._compat import device as get_device
@@ -1399,7 +1398,6 @@ def test_assume_unique(self, xp: ModuleType):
     @pytest.mark.parametrize("shape2", [(), (1,), (1, 1)])
     def test_shapes(
         self,
-        request: pytest.FixtureRequest,
         assume_unique: bool,
         shape1: tuple[int, ...],
         shape2: tuple[int, ...],
@@ -1408,26 +1406,18 @@ def test_shapes(
         x1 = xp.zeros(shape1)
         x2 = xp.zeros(shape2)
 
-        if is_jax_namespace(xp) and assume_unique and shape1 != (1,):
-            xfail(request=request, reason="jax#32335 fixed with jax>=0.8.0")
-
         actual = setdiff1d(x1, x2, assume_unique=assume_unique)
         xp_assert_equal(actual, xp.empty((0,)))
 
     @assume_unique
     @pytest.mark.skip_xp_backend(Backend.NUMPY_READONLY, reason="xp=xp")
-    def test_python_scalar(
-        self, request: pytest.FixtureRequest, xp: ModuleType, assume_unique: bool
-    ):
+    def test_python_scalar(self, xp: ModuleType, assume_unique: bool):
         # Test no dtype promotion to xp.asarray(x2); use x1.dtype
         x1 = xp.asarray([3, 1, 2], dtype=xp.int16)
         x2 = 3
         actual = setdiff1d(x1, x2, assume_unique=assume_unique)
         xp_assert_equal(actual, xp.asarray([1, 2], dtype=xp.int16))
 
-        if is_jax_namespace(xp) and assume_unique:
-            xfail(request=request, reason="jax#32335 fixed with jax>=0.8.0")
-
         actual = setdiff1d(x2, x1, assume_unique=assume_unique)
         xp_assert_equal(actual, xp.asarray([], dtype=xp.int16))