BUG: work around/comment on the strategy for x in count_nonzero

On torch, work around count_nonzero not implemented for uints
On jax, there are problems with integers > iinfo(jnp.int32)

Author: ev-br

Diff for: array_api_tests/test_searching_functions.py

@@ -88,10 +88,18 @@ def test_argmin(x, data):
         ph.assert_scalar_equals("argmin", type_=int, idx=out_idx, out=min_i, expected=expected)
 
 
+# XXX: dtype= stanza below is to work around unsigned int dtypes in torch
+# (count_nonzero_cpu not implemented for uint32 etc)
+# XXX: the strategy for x is problematic on JAX unless JAX_ENABLE_X64 is on
+# the problem is tha for ints >iinfo(int32) it runs into essentially this:
+#  >>> jnp.asarray[2147483648], dtype=jnp.int64)
+#  .... https://github.com/jax-ml/jax/pull/6047 ...
+# Explicitly limiting the range in elements(...) runs into problems with
+# hypothesis where floating-point numbers are not exactly representable.
 @pytest.mark.min_version("2024.12")
 @given(
     x=hh.arrays(
-        dtype=hh.real_dtypes,
+        dtype=st.sampled_from(dh.int_dtypes + dh.real_float_dtypes + dh.complex_dtypes + (xp.bool,)),
         shape=hh.shapes(min_dims=1, min_side=1),
         elements={"allow_nan": False},
     ),