Fix numba implementation of CumOp when axis is None

pytensor/link/numba/dispatch/extra_ops.py

 import warnings
+from typing import cast
 
 import numba
 import numpy as np
 
 from pytensor import config
+from pytensor.graph import Apply
 from pytensor.link.numba.dispatch import basic as numba_basic
 from pytensor.link.numba.dispatch.basic import get_numba_type, numba_funcify
 from pytensor.raise_op import CheckAndRaise
+from pytensor.tensor import TensorVariable
 from pytensor.tensor.extra_ops import (
     Bartlett,
     CumOp,
@@ -30,21 +33,22 @@ def numba_funcify_Bartlett(op, **kwargs):
 
 
 @numba_funcify.register(CumOp)
-def numba_funcify_CumOp(op, node, **kwargs):
+def numba_funcify_CumOp(op: CumOp, node: Apply, **kwargs):
     axis = op.axis
     mode = op.mode
-    ndim = node.outputs[0].ndim
+    ndim = cast(TensorVariable, node.outputs[0]).ndim
 
-    if axis < 0:
-        axis = ndim + axis
-    if axis < 0 or axis >= ndim:
-        raise ValueError(f"Invalid axis {axis} for array with ndim {ndim}")
+    if axis is not None:
+        if axis < 0:
+            axis = ndim + axis
+        if axis < 0 or axis >= ndim:
+            raise ValueError(f"Invalid axis {axis} for array with ndim {ndim}")
 
-    reaxis_first = (axis,) + tuple(i for i in range(ndim) if i != axis)
-    reaxis_first_inv = tuple(np.argsort(reaxis_first))
+        reaxis_first = (axis,) + tuple(i for i in range(ndim) if i != axis)
+        reaxis_first_inv = tuple(np.argsort(reaxis_first))
 
     if mode == "add":
-        if ndim == 1:
+        if axis is None or ndim == 1:
 
             @numba_basic.numba_njit(fastmath=config.numba__fastmath)
             def cumop(x):
@@ -68,7 +72,7 @@ def numba_funcify_CumOp(op, node, **kwargs):
                 return res.transpose(reaxis_first_inv)
 
     else:
-        if ndim == 1:
+        if axis is None or ndim == 1:
 
             @numba_basic.numba_njit(fastmath=config.numba__fastmath)
             def cumop(x):

pytensor/tensor/extra_ops.py

 from collections.abc import Collection
-from typing import Iterable, Set, Tuple, Union
+from typing import Iterable, Optional, Set, Tuple, Union
 
 import numpy as np
 from numpy.core.multiarray import normalize_axis_index
@@ -291,7 +291,7 @@ class CumOp(COp):
         c_axis=int_t, mode=EnumList(("MODE_ADD", "add"), ("MODE_MUL", "mul"))
     )
 
-    def __init__(self, axis=None, mode="add"):
+    def __init__(self, axis: Optional[int] = None, mode="add"):
         if mode not in ("add", "mul"):
             raise ValueError(f'{type(self).__name__}: Unknown mode "{mode}"')
         self.axis = axis

pytensor/tensor/var.py

@@ -619,7 +619,7 @@ class _tensor_py_operators:
             )
 
     @property
-    def ndim(self):
+    def ndim(self) -> int:
         """The rank of this tensor."""
         return self.type.ndim
 

tests/link/numba/test_extra_ops.py

@@ -67,6 +67,13 @@ def test_Bartlett(val):
             1,
             "add",
         ),
+        (
+            set_test_value(
+                at.matrix(), np.arange(6, dtype=config.floatX).reshape((3, 2))
+            ),
+            None,
+            "add",
+        ),
         (
             set_test_value(
                 at.matrix(), np.arange(6, dtype=config.floatX).reshape((3, 2))
@@ -81,6 +88,13 @@ def test_Bartlett(val):
             1,
             "mul",
         ),
+        (
+            set_test_value(
+                at.matrix(), np.arange(6, dtype=config.floatX).reshape((3, 2))
+            ),
+            None,
+            "mul",
+        ),
     ],
 )
 def test_CumOp(val, axis, mode):