Numba OpFromGraph: Prevent alias of outputs

pytensor/link/numba/dispatch/compile_ops.py

@@ -5,8 +5,8 @@ import numba
 import numpy as np
 
 from pytensor.compile.builders import OpFromGraph
-from pytensor.compile.function.types import add_supervisor_to_fgraph
-from pytensor.compile.io import In
+from pytensor.compile.function.types import add_supervisor_to_fgraph, insert_deepcopy
+from pytensor.compile.io import In, Out
 from pytensor.compile.mode import NUMBA
 from pytensor.compile.ops import DeepCopyOp, TypeCastingOp
 from pytensor.ifelse import IfElse
@@ -56,14 +56,17 @@ def numba_funcify_OpFromGraph(op, node=None, **kwargs):
     #  explicitly triggers the optimization of the inner graphs of OpFromGraph?
     #  The C-code defers it to the make_thunk phase
     fgraph = op.fgraph
+    input_specs = [In(x, borrow=True, mutable=False) for x in fgraph.inputs]
     add_supervisor_to_fgraph(
         fgraph=fgraph,
-        input_specs=[In(x, borrow=True, mutable=False) for x in fgraph.inputs],
+        input_specs=input_specs,
         accept_inplace=True,
     )
     NUMBA.optimizer(fgraph)
+    output_specs = [Out(o, borrow=False) for o in fgraph.outputs]
+    insert_deepcopy(fgraph, wrapped_inputs=input_specs, wrapped_outputs=output_specs)
     fgraph_fn, fgraph_cache_key = numba_funcify_and_cache_key(
-        op.fgraph, squeeze_output=True, **kwargs
+        fgraph, squeeze_output=True, **kwargs
     )
 
     if fgraph_cache_key is None:

tests/link/numba/test_compile_ops.py

@@ -5,6 +5,9 @@ from pytensor import OpFromGraph, config, function, ifelse
 from pytensor import tensor as pt
 from pytensor.compile import ViewOp
 from pytensor.raise_op import assert_op
+from pytensor.scalar import Add
+from pytensor.tensor import matrix
+from pytensor.tensor.elemwise import Elemwise
 from tests.link.numba.test_basic import compare_numba_and_py
 
 
@@ -146,6 +149,28 @@ def test_ofg_inner_inplace():
     np.testing.assert_allclose(res1, [1, np.e, np.e])
 
 
+def test_ofg_aliased_outputs():
+    x = matrix("x")
+    # Create multiple views of x
+    outs = OpFromGraph([x], [x, x.T, x[::-1]])(x)
+    # Add one to each x, which when inplace shouldn't propagate across outputs
+    bumped_outs = [o + 1 for o in outs]
+    fn = function([x], bumped_outs, mode="NUMBA")
+    fn.dprint(print_destroy_map=True)
+    # Check our outputs are indeed inplace adds
+    assert all(
+        (
+            isinstance(o.owner.op, Elemwise)
+            and isinstance(o.owner.op.scalar_op, Add)
+            and o.owner.op.destroy_map
+        )
+        for o in fn.maker.fgraph.outputs
+    )
+    x_test = np.zeros((2, 2))
+    for res in fn(x_test):
+        np.testing.assert_allclose(res, np.ones((2, 2)))
+
+
 def test_check_and_raise():
     x = pt.vector()
     x_test_value = np.array([1.0, 2.0], dtype=config.floatX)