[JAX] Update JAX users in preparation for a change that makes iterati…

…on over a JAX array return JAX arrays, instead of NumPy arrays.

See #8043 for context as to why we are making this change.

The upshot for most users is that the values returned by iteration over a JAX array are now themselves JAX arrays, with the semantics of JAX arrays, which sometimes differ from the semantics of NumPy scalars and arrays.

PiperOrigin-RevId: 405995198

tests/ann_test.py

@@ -49,7 +49,7 @@ def test_approx_max_k(self, qy_shape, db_shape, dtype, k, recall):
     _, gt_args = lax.top_k(scores, k)
     _, ann_args = ann.approx_max_k(scores, k, recall_target=recall)
     self.assertEqual(k, len(ann_args[0]))
-    gt_args_sets = [set(x) for x in gt_args]
+    gt_args_sets = [set(np.asarray(x)) for x in gt_args]
     hits = sum(
         len(list(x
                  for x in ann_args_per_q
@@ -77,7 +77,7 @@ def test_approx_min_k(self, qy_shape, db_shape, dtype, k, recall):
     _, gt_args = lax.top_k(-scores, k)
     _, ann_args = ann.approx_min_k(scores, k, recall_target=recall)
     self.assertEqual(k, len(ann_args[0]))
-    gt_args_sets = [set(x) for x in gt_args]
+    gt_args_sets = [set(np.asarray(x)) for x in gt_args]
     hits = sum(
         len(list(x
                  for x in ann_args_per_q