WIP ENH: setdiff1d delegate function

src/array_api_extra/__init__.py

@@ -1,6 +1,6 @@
 """Extra array functions built on top of the array API standard."""
 
-from ._delegation import expand_dims, isclose, nan_to_num, one_hot, pad, sinc
+from ._delegation import expand_dims, isclose, nan_to_num, one_hot, pad, setdiff1d, sinc
 from ._lib._at import at
 from ._lib._funcs import (
     apply_where,
@@ -11,7 +11,6 @@
     default_dtype,
     kron,
     nunique,
-    setdiff1d,
 )
 from ._lib._lazy import lazy_apply
 

src/array_api_extra/_delegation.py

@@ -416,6 +416,58 @@ def pad(
     return _funcs.pad(x, pad_width, constant_values=constant_values, xp=xp)
 
 
+def setdiff1d(
+    x1: Array | complex,
+    x2: Array | complex,
+    /,
+    *,
+    assume_unique: bool = False,
+    xp: ModuleType | None = None,
+) -> Array:
+    """
+    Find the set difference of two arrays.
+
+    Return the unique values in `x1` that are not in `x2`.
+
+    Parameters
+    ----------
+    x1 : array | int | float | complex | bool
+        Input array.
+    x2 : array
+        Input comparison array.
+    assume_unique : bool
+        If ``True``, the input arrays are both assumed to be unique, which
+        can speed up the calculation. Default is ``False``.
+    xp : array_namespace, optional
+        The standard-compatible namespace for `x1` and `x2`. Default: infer.
+
+    Returns
+    -------
+    array
+        1D array of values in `x1` that are not in `x2`. The result
+        is sorted when `assume_unique` is ``False``, but otherwise only sorted
+        if the input is sorted.
+
+    Examples
+    --------
+    >>> import array_api_strict as xp
+    >>> import array_api_extra as xpx
+
+    >>> x1 = xp.asarray([1, 2, 3, 2, 4, 1])
+    >>> x2 = xp.asarray([3, 4, 5, 6])
+    >>> xpx.setdiff1d(x1, x2, xp=xp)
+    Array([1, 2], dtype=array_api_strict.int64)
+    """
+
+    if xp is None:
+        xp = array_namespace(x1, x2)
+
+    if is_numpy_namespace(xp) or is_jax_namespace(xp) or is_cupy_namespace(xp):
+        return xp.setdiff1d(x1, x2, assume_unique=assume_unique)
+
+    return _funcs.setdiff1d(x1, x2, assume_unique=assume_unique, xp=xp)
+
+
 def sinc(x: Array, /, *, xp: ModuleType | None = None) -> Array:
     r"""
     Return the normalized sinc function.

src/array_api_extra/_lib/_funcs.py

@@ -813,44 +813,10 @@ def setdiff1d(
     /,
     *,
     assume_unique: bool = False,
-    xp: ModuleType | None = None,
-) -> Array:
-    """
-    Find the set difference of two arrays.
-
-    Return the unique values in `x1` that are not in `x2`.
-
-    Parameters
-    ----------
-    x1 : array | int | float | complex | bool
-        Input array.
-    x2 : array
-        Input comparison array.
-    assume_unique : bool
-        If ``True``, the input arrays are both assumed to be unique, which
-        can speed up the calculation. Default is ``False``.
-    xp : array_namespace, optional
-        The standard-compatible namespace for `x1` and `x2`. Default: infer.
-
-    Returns
-    -------
-    array
-        1D array of values in `x1` that are not in `x2`. The result
-        is sorted when `assume_unique` is ``False``, but otherwise only sorted
-        if the input is sorted.
-
-    Examples
-    --------
-    >>> import array_api_strict as xp
-    >>> import array_api_extra as xpx
+    xp: ModuleType,
+) -> Array:  # numpydoc ignore=PR01,RT01
+    """See docstring in `array_api_extra._delegation.py`."""
 
-    >>> x1 = xp.asarray([1, 2, 3, 2, 4, 1])
-    >>> x2 = xp.asarray([3, 4, 5, 6])
-    >>> xpx.setdiff1d(x1, x2, xp=xp)
-    Array([1, 2], dtype=array_api_strict.int64)
-    """
-    if xp is None:
-        xp = array_namespace(x1, x2)
     # https://github.com/microsoft/pyright/issues/10103
     x1_, x2_ = asarrays(x1, x2, xp=xp)