Support numba compiled sort and argsort functions

pytensor/link/numba/dispatch/basic.py

@@ -37,6 +37,7 @@
 from pytensor.tensor.math import Dot
 from pytensor.tensor.shape import Reshape, Shape, Shape_i, SpecifyShape
 from pytensor.tensor.slinalg import Solve
+from pytensor.tensor.sort import ArgSortOp, SortOp
 from pytensor.tensor.type import TensorType
 from pytensor.tensor.type_other import MakeSlice, NoneConst
 
@@ -432,6 +433,49 @@ def shape_i(x):
     return shape_i
 
 
+@numba_funcify.register(SortOp)
+def numba_funcify_SortOp(op, node, **kwargs):
+    @numba_njit
+    def sort_f(a, axis):
+        return np.sort(a)  # numba supports sort without arguments
+
+    if op.kind != "quicksort":
+        warnings.warn(
+            (
+                f'Numba function sort doesn\'t support kind="{op.kind}"'
+                " switching to `quicksort`."
+            ),
+            UserWarning,
+        )
+
+    return sort_f
+
+
+@numba_funcify.register(ArgSortOp)
+def numba_funcify_ArgSortOp(op, node, **kwargs):
+    def argsort_f_kind(kind):
+        @numba_njit
+        def argsort_f(a, axis):
+            return np.argsort(a, kind=kind)
+
+        return argsort_f
+
+    kind = op.kind
+
+    if kind in ["quicksort", "mergesort"]:
+        return argsort_f_kind(kind)
+    else:
+        warnings.warn(
+            (
+                f'Numba function argsort doesn\'t support kind="{op.kind}"'
+                " switching to `quicksort`."
+            ),
+            UserWarning,
+        )
+
+        return argsort_f_kind("quicksort")
+
+
 @numba.extending.intrinsic
 def direct_cast(typingctx, val, typ):
     if isinstance(typ, numba.types.TypeRef):

tests/link/numba/test_basic.py

@@ -33,6 +33,7 @@
 from pytensor.tensor import blas
 from pytensor.tensor.elemwise import Elemwise
 from pytensor.tensor.shape import Reshape, Shape, Shape_i, SpecifyShape
+from pytensor.tensor.sort import ArgSortOp, SortOp
 
 
 if TYPE_CHECKING:
@@ -378,6 +379,49 @@ def test_Shape(x, i):
     compare_numba_and_py([], [g], [])
 
 
+@pytest.mark.parametrize(
+    "kind, exc",
+    [
+        ["quicksort", None],
+        ["mergesort", UserWarning],
+        ["heapsort", UserWarning],
+        ["stable", UserWarning],
+    ],
+)
+def test_Sort(kind, exc):
+    x = [5, 4, 3, 2, 1]
+
+    g = SortOp(kind)(pt.as_tensor_variable(x))
+
+    if exc:
+        with pytest.warns(exc):
+            compare_numba_and_py([], [g], [])
+    else:
+        compare_numba_and_py([], [g], [])
+
+    compare_numba_and_py([], [g], [])
+
+
+@pytest.mark.parametrize(
+    "kind, exc",
+    [
+        ["quicksort", None],
+        ["mergesort", None],
+        ["heapsort", UserWarning],
+        ["stable", UserWarning],
+    ],
+)
+def test_ArgSort(kind, exc):
+    x = [5, 4, 3, 2, 1]
+    g = ArgSortOp(kind)(pt.as_tensor_variable(x))
+
+    if exc:
+        with pytest.warns(exc):
+            compare_numba_and_py([], [g], [])
+    else:
+        compare_numba_and_py([], [g], [])
+
+
 @pytest.mark.parametrize(
     "v, shape, ndim",
     [