Apply suggestions from code review

Co-authored-by: Lucas Colley <lucas.colley8@gmail.com>

Author: mdhaber

src/array_api_extra/_delegation.py

@@ -647,9 +647,9 @@ def searchsorted(
     Find the indices into a sorted array ``x1`` such that if the elements in ``x2``
     were inserted before the indices, the resulting array would remain sorted.
 
-    The behavior of this function is similar to that of the homonymous function in the
-    array API standard, but it relaxes the requirement that `x1` must be
-    one-dimensional. The function is vectorized, treating slices along the last axis
+    The behavior of this function is similar to that of `array_api.searchsorted`,
+    but it relaxes the requirement that `x1` must be one-dimensional.
+    This function is vectorized, treating slices along the last axis
     as elements and preceding axes as batch (or "loop") dimensions.
 
     Parameters
@@ -701,11 +701,11 @@ def searchsorted(
         raise ValueError(message)
 
     xp_default_int = _funcs.default_dtype(xp, kind="integral")
-    y_0d = xp.asarray(x2).ndim == 0
-    x_1d = x1.ndim <= 1
+    x2_0d = x2.ndim == 0
+    x1_1d = x1.ndim <= 1
 
-    if x_1d or is_torch_namespace(xp):
-        x2 = xp.reshape(x2, ()) if (y_0d and x_1d) else x2
+    if x1_1d or is_torch_namespace(xp):
+        x2 = xp.reshape(x2, ()) if (x2_0d and x1_1d) else x2
         out = xp.searchsorted(x1, x2, side=side)
         return xp.astype(out, xp_default_int, copy=False)
 

tests/test_funcs.py

@@ -1789,7 +1789,7 @@ def xp_searchsorted(
     side: Literal["left", "right"],
     xp: ModuleType,
 ) -> Array:
-    return xp.searchsorted(xp.asarray(a), xp.asarray(v), side=side)
+    return xp.searchsorted(a, v, side=side)
 
 
 @pytest.mark.skip_xp_backend(Backend.DASK, reason="no take_along_axis")
@@ -1845,7 +1845,7 @@ def test_nd(
             x[mask] = np.inf
         x = np.sort(x, axis=-1)  # type:ignore[assignment]
         x, y = np.asarray(x, dtype=np.float64), np.asarray(y, dtype=np.float64)
-        xp_default_int = xp.asarray(1).dtype
+        xp_default_int = default_dtype(xp, kind="integral")
         if x.size == 0 and x.ndim > 0 and x.shape[-1] != 0:
             ref = xp.empty((*x.shape[:-1], y.shape[-1]), dtype=xp_default_int)
         else: