Allow non-shared untraced SIT-SOT

pytensor/link/jax/dispatch/scan.py

@@ -60,23 +60,23 @@ def jax_funcify_Scan(op: Scan, **kwargs):
             mit_mot_init,
             mit_sot_init,
             sit_sot_init,
-            op.outer_shared(outer_inputs),
+            op.outer_untraced_sit_sot(outer_inputs),
             op.outer_non_seqs(outer_inputs),
         )  # JAX `init`
 
         def jax_args_to_inner_func_args(carry, x):
             """Convert JAX scan arguments into format expected by scan_inner_func.
 
-            scan(carry, x) -> scan_inner_func(seqs, MIT-SOT, SIT-SOT, shared, non_seqs)
+            scan(carry, x) -> scan_inner_func(seqs, MIT-SOT, SIT-SOT, untraced SIT-SOT, non_seqs)
             """
 
-            # `carry` contains all inner taps, shared terms, and non_seqs
+            # `carry` contains all inner taps and non_seqs
             (
                 i,
                 inner_mit_mot,
                 inner_mit_sot,
                 inner_sit_sot,
-                inner_shared,
+                inner_untraced_sit_sot,
                 inner_non_seqs,
             ) = carry
 
@@ -108,7 +108,7 @@ def jax_funcify_Scan(op: Scan, **kwargs):
                 *mit_mot_flatten,
                 *mit_sot_flatten,
                 *inner_sit_sot,
-                *inner_shared,
+                *inner_untraced_sit_sot,
                 *inner_non_seqs,
             )
 
@@ -118,14 +118,14 @@ def jax_funcify_Scan(op: Scan, **kwargs):
         ):
             """Convert inner_scan_func outputs into format expected by JAX scan.
 
-            old_carry + (MIT-SOT_outs, SIT-SOT_outs, NIT-SOT_outs, shared_outs) -> (new_carry, ys)
+            old_carry + (MIT-SOT_outs, SIT-SOT_outs, NIT-SOT_outs, untraced_SIT-SOT_outs) -> (new_carry, ys)
             """
             (
                 i,
                 old_mit_mot,
                 old_mit_sot,
                 _old_sit_sot,
-                _old_shared,
+                _old_untraced_sit_sot,
                 inner_non_seqs,
             ) = old_carry
 
@@ -133,7 +133,7 @@ def jax_funcify_Scan(op: Scan, **kwargs):
             new_mit_sot_vals = op.inner_mitsot_outs(inner_scan_outs)
             new_sit_sot = op.inner_sitsot_outs(inner_scan_outs)
             new_nit_sot = op.inner_nitsot_outs(inner_scan_outs)
-            new_shared = op.inner_shared_outs(inner_scan_outs)
+            new_untraced_sit_sot = op.inner_untraced_sit_sot_outs(inner_scan_outs)
 
             # New carry for next step
             # Update MIT-MOT buffer at positions indicated by output taps
@@ -150,14 +150,14 @@ def jax_funcify_Scan(op: Scan, **kwargs):
                     old_mit_sot, new_mit_sot_vals, strict=True
                 )
             ]
-            # For SIT-SOT, and shared just pass along the new value
+            # For SIT-SOT just pass along the new value
             # Non-sequences remain unchanged
             new_carry = (
                 i + 1,
                 new_mit_mot,
                 new_mit_sot,
                 new_sit_sot,
-                new_shared,
+                new_untraced_sit_sot,
                 inner_non_seqs,
             )
 
@@ -183,7 +183,7 @@ def jax_funcify_Scan(op: Scan, **kwargs):
                 final_mit_mot,
                 _final_mit_sot,
                 _final_sit_sot,
-                final_shared,
+                final_untraced_sit_sot,
                 _final_non_seqs,
             ),
             traces,
@@ -238,7 +238,7 @@ def jax_funcify_Scan(op: Scan, **kwargs):
         scan_outs_final = [
             *final_mit_mot,
             *get_partial_traces(traces),
-            *final_shared,
+            *final_untraced_sit_sot,
         ]
 
         if len(scan_outs_final) == 1:

pytensor/link/numba/dispatch/scan.py

@@ -108,19 +108,19 @@ def numba_funcify_Scan(op: Scan, node, **kwargs):
     outer_in_mit_sot_names = op.outer_mitsot(outer_in_names)
     outer_in_sit_sot_names = op.outer_sitsot(outer_in_names)
     outer_in_nit_sot_names = op.outer_nitsot(outer_in_names)
-    outer_in_shared_names = op.outer_shared(outer_in_names)
+    outer_in_untraced_sit_sot_names = op.outer_untraced_sit_sot(outer_in_names)
     outer_in_non_seqs_names = op.outer_non_seqs(outer_in_names)
 
     # These are all the outer-input names that have produce outputs/have output
     # taps (i.e. they have inner-outputs and corresponding outer-outputs).
     # Outer-outputs are ordered as follows:
-    # mit-mot-outputs + mit-sot-outputs + sit-sot-outputs + nit-sots + shared-outputs
+    # mit-mot-outputs + mit-sot-outputs + sit-sot-outputs + nit-sots + untraced-sit-sot-outputs
     outer_in_outtap_names = (
         outer_in_mit_mot_names
         + outer_in_mit_sot_names
         + outer_in_sit_sot_names
         + outer_in_nit_sot_names
-        + outer_in_shared_names
+        + outer_in_untraced_sit_sot_names
     )
 
     # We create distinct variables for/references to the storage arrays for
@@ -138,8 +138,10 @@ def numba_funcify_Scan(op: Scan, node, **kwargs):
     for outer_in_name in outer_in_nit_sot_names:
         outer_in_to_storage_name[outer_in_name] = f"{outer_in_name}_nitsot_storage"
 
-    for outer_in_name in outer_in_shared_names:
-        outer_in_to_storage_name[outer_in_name] = f"{outer_in_name}_shared_storage"
+    for outer_in_name in outer_in_untraced_sit_sot_names:
+        outer_in_to_storage_name[outer_in_name] = (
+            f"{outer_in_name}_untraced_sit_sot_storage"
+        )
 
     outer_output_names = list(outer_in_to_storage_name.values())
     assert len(outer_output_names) == len(node.outputs)
@@ -147,7 +149,7 @@ def numba_funcify_Scan(op: Scan, node, **kwargs):
     # Construct the inner-input expressions (e.g. indexed storage expressions)
     # Inner-inputs are ordered as follows:
     # sequences + mit-mot-inputs + mit-sot-inputs + sit-sot-inputs +
-    # shared-inputs + non-sequences.
+    # untraced-sit-sot-inputs + non-sequences.
     temp_scalar_storage_alloc_stmts: list[str] = []
     inner_in_exprs_scalar: list[str] = []
     inner_in_exprs: list[str] = []
@@ -204,11 +206,9 @@ def numba_funcify_Scan(op: Scan, node, **kwargs):
 
     # Inner-outputs consist of:
     # mit-mot-outputs + mit-sot-outputs + sit-sot-outputs + nit-sots +
-    # shared-outputs [+ while-condition]
+    # untraced-sit-sot-outputs [+ while-condition]
     inner_output_names = [f"inner_out_{i}" for i in range(len(op.inner_outputs))]
 
-    # inner_out_shared_names = op.inner_shared_outs(inner_output_names)
-
     # The assignment statements that copy inner-outputs into the outer-outputs
     # storage
     inner_out_to_outer_in_stmts: list[str] = []

pytensor/scan/basic.py

+import typing
 import warnings
 from itertools import chain
 
@@ -11,6 +12,7 @@ from pytensor.graph.basic import Constant, Variable
 from pytensor.graph.op import get_test_value
 from pytensor.graph.replace import clone_replace
 from pytensor.graph.traversal import explicit_graph_inputs
+from pytensor.graph.type import HasShape
 from pytensor.graph.utils import MissingInputError, TestValueError
 from pytensor.scan.op import Scan, ScanInfo
 from pytensor.scan.utils import expand_empty, safe_new, until
@@ -22,6 +24,10 @@ from pytensor.tensor.type import TensorType, integer_dtypes
 from pytensor.updates import OrderedUpdates
 
 
+if typing.TYPE_CHECKING:
+    from pytensor.tensor.type import TensorVariable
+
+
 def get_updates_and_outputs(ls):
     """Recognize and order the updates, outputs, and stopping condition for a `Scan`.
 
@@ -469,7 +475,7 @@ def scan(
 
     # Make sure we get rid of numpy arrays or ints or anything like that
     # passed as inputs to scan
-    non_seqs = []
+    non_seqs: list[Variable] = []
     for elem in wrap_into_list(non_sequences):
         if not isinstance(elem, Variable):
             non_seqs.append(pt.as_tensor_variable(elem))
@@ -685,10 +691,10 @@ def scan(
 
     # MIT_MOT -- not provided by the user only by the grad function
     n_mit_mot = 0
-    mit_mot_scan_inputs = []
-    mit_mot_inner_inputs = []
-    mit_mot_inner_outputs = []
-    mit_mot_out_slices = []
+    mit_mot_scan_inputs: list[TensorVariable] = []
+    mit_mot_inner_inputs: list[TensorVariable] = []
+    mit_mot_inner_outputs: list[TensorVariable] = []
+    mit_mot_out_slices: list[TensorVariable] = []
 
     # SIT_SOT -- provided by the user
     n_mit_sot = 0
@@ -706,6 +712,12 @@ def scan(
     sit_sot_inner_outputs = []
     sit_sot_rightOrder = []
 
+    n_untraced_sit_sot_outs = 0
+    untraced_sit_sot_scan_inputs = []
+    untraced_sit_sot_inner_inputs = []
+    untraced_sit_sot_inner_outputs = []
+    untraced_sit_sot_rightOrder = []
+
     # go through outputs picking up time slices as needed
     for i, init_out in enumerate(outs_info):
         # Note that our convention dictates that if an output uses
@@ -741,17 +753,35 @@ def scan(
             # We need now to allocate space for storing the output and copy
             # the initial state over. We do this using the expand function
             # defined in scan utils
+            if isinstance(actual_arg.type, HasShape):
                 sit_sot_scan_inputs.append(
                     expand_empty(
                         shape_padleft(actual_arg),
                         actual_n_steps,
                     )
                 )
-
                 sit_sot_inner_slices.append(actual_arg)
+
                 sit_sot_inner_inputs.append(arg)
                 sit_sot_rightOrder.append(i)
                 n_sit_sot += 1
+            else:
+                # Assume variables without shape cannot be stacked (e.g., RNG variables)
+                # Because this is new, issue a warning to inform the user, except for RNG, which were the main reason for this feature
+                from pytensor.tensor.random.type import RandomType
+
+                if not isinstance(arg.type, RandomType):
+                    warnings.warn(
+                        (
+                            f"Output {actual_arg} (index {i}) with type {actual_arg.type} will be treated as untraced variable in scan. "
+                            "Only the last value will be returned, not the entire sequence."
+                        ),
+                        UserWarning,
+                    )
+                untraced_sit_sot_scan_inputs.append(actual_arg)
+                untraced_sit_sot_inner_inputs.append(arg)
+                n_untraced_sit_sot_outs += 1
+                untraced_sit_sot_rightOrder.append(i)
 
         elif init_out.get("taps", None):
             if np.any(np.array(init_out.get("taps", [])) > 0):
@@ -802,10 +832,11 @@ def scan(
         #      a map); in that case we do not have to do anything ..
 
     # Re-order args
-    max_mit_sot = np.max([-1, *mit_sot_rightOrder]) + 1
-    max_sit_sot = np.max([-1, *sit_sot_rightOrder]) + 1
-    n_elems = np.max([max_mit_sot, max_sit_sot])
-    _ordered_args = [[] for x in range(n_elems)]
+    max_mit_sot = max(mit_sot_rightOrder, default=-1) + 1
+    max_sit_sot = max(sit_sot_rightOrder, default=-1) + 1
+    max_untraced_sit_sot_outs = max(untraced_sit_sot_rightOrder, default=-1) + 1
+    n_elems = np.max((max_mit_sot, max_sit_sot, max_untraced_sit_sot_outs))
+    _ordered_args: list[list[Variable]] = [[] for x in range(n_elems)]
     offset = 0
     for idx in range(n_mit_sot):
         n_inputs = len(mit_sot_tap_array[idx])
@@ -825,6 +856,11 @@ def scan(
         else:
             _ordered_args[sit_sot_rightOrder[idx]] = [sit_sot_inner_inputs[idx]]
 
+    for idx in range(n_untraced_sit_sot_outs):
+        _ordered_args[untraced_sit_sot_rightOrder[idx]] = [
+            untraced_sit_sot_inner_inputs[idx]
+        ]
+
     ordered_args = list(chain.from_iterable(_ordered_args))
     if single_step_requested:
         args = inner_slices + ordered_args + non_seqs
@@ -939,18 +975,19 @@ def scan(
         if "taps" in out and out["taps"] != [-1]:
             mit_sot_inner_outputs.append(outputs[i])
 
-    # Step 5.2 Outputs with tap equal to -1
+    # Step 5.2 Outputs with tap equal to -1 (traced and untraced)
     for i, out in enumerate(outs_info):
         if "taps" in out and out["taps"] == [-1]:
-            sit_sot_inner_outputs.append(outputs[i])
+            output = outputs[i]
+            if isinstance(output.type, HasShape):
+                sit_sot_inner_outputs.append(output)
+            else:
+                untraced_sit_sot_inner_outputs.append(output)
 
     # Step 5.3 Outputs that correspond to update rules of shared variables
+    # This whole special logic for shared variables is deprecated
+    sit_sot_shared: list[Variable] = []
     inner_replacements = {}
-    n_shared_outs = 0
-    shared_scan_inputs = []
-    shared_inner_inputs = []
-    shared_inner_outputs = []
-    sit_sot_shared = []
     no_update_shared_inputs = []
     for input in dummy_inputs:
         if not isinstance(input.variable, SharedVariable):
@@ -976,8 +1013,8 @@ def scan(
 
             new_var = safe_new(input.variable)
 
-            if getattr(input.variable, "name", None) is not None:
-                new_var.name = input.variable.name + "_copy"
+            if input.variable.name is not None:
+                new_var.name = f"{input.variable.name}_copy"
 
             inner_replacements[input.variable] = new_var
 
@@ -1003,10 +1040,10 @@ def scan(
                 sit_sot_shared.append(input.variable)
 
             else:
-                shared_inner_inputs.append(new_var)
-                shared_scan_inputs.append(input.variable)
-                shared_inner_outputs.append(input.update)
-                n_shared_outs += 1
+                untraced_sit_sot_inner_inputs.append(new_var)
+                untraced_sit_sot_scan_inputs.append(input.variable)
+                untraced_sit_sot_inner_outputs.append(input.update)
+                n_untraced_sit_sot_outs += 1
         else:
             no_update_shared_inputs.append(input)
 
@@ -1071,7 +1108,7 @@ def scan(
         + mit_mot_inner_inputs
         + mit_sot_inner_inputs
         + sit_sot_inner_inputs
-        + shared_inner_inputs
+        + untraced_sit_sot_inner_inputs
         + other_shared_inner_args
         + other_inner_args
     )
@@ -1081,7 +1118,7 @@ def scan(
         + mit_sot_inner_outputs
         + sit_sot_inner_outputs
         + nit_sot_inner_outputs
-        + shared_inner_outputs
+        + untraced_sit_sot_inner_outputs
     )
     if condition is not None:
         inner_outs.append(condition)
@@ -1101,7 +1138,7 @@ def scan(
         mit_mot_out_slices=tuple(tuple(v) for v in mit_mot_out_slices),
         mit_sot_in_slices=tuple(tuple(v) for v in mit_sot_tap_array),
         sit_sot_in_slices=tuple((-1,) for x in range(n_sit_sot)),
-        n_shared_outs=n_shared_outs,
+        n_untraced_sit_sot_outs=n_untraced_sit_sot_outs,
         n_nit_sot=n_nit_sot,
         n_non_seqs=len(other_shared_inner_args) + len(other_inner_args),
         as_while=as_while,
@@ -1127,7 +1164,7 @@ def scan(
         + mit_mot_scan_inputs
         + mit_sot_scan_inputs
         + sit_sot_scan_inputs
-        + shared_scan_inputs
+        + untraced_sit_sot_scan_inputs
         + [actual_n_steps for x in range(n_nit_sot)]
         + other_shared_scan_args
         + other_scan_args
@@ -1173,13 +1210,26 @@ def scan(
     nit_sot_outs = remove_dimensions(scan_outs[offset : offset + n_nit_sot])
 
     offset += n_nit_sot
-    for idx, update_rule in enumerate(scan_outs[offset : offset + n_shared_outs]):
-        update_map[shared_scan_inputs[idx]] = update_rule
 
-    _scan_out_list = mit_sot_outs + sit_sot_outs + nit_sot_outs
+    # Support for explicit untraced sit_sot
+    n_explicit_untraced_sit_sot_outs = len(untraced_sit_sot_rightOrder)
+    untraced_sit_sot_outs = scan_outs[
+        offset : offset + n_explicit_untraced_sit_sot_outs
+    ]
+
+    offset += n_explicit_untraced_sit_sot_outs
+    for idx, update_rule in enumerate(scan_outs[offset:]):
+        update_map[untraced_sit_sot_scan_inputs[idx]] = update_rule
+
+    _scan_out_list = mit_sot_outs + sit_sot_outs + nit_sot_outs + untraced_sit_sot_outs
     # Step 10. I need to reorder the outputs to be in the order expected by
     # the user
-    rightOrder = mit_sot_rightOrder + sit_sot_rightOrder + nit_sot_rightOrder
+    rightOrder = (
+        mit_sot_rightOrder
+        + sit_sot_rightOrder
+        + untraced_sit_sot_rightOrder
+        + nit_sot_rightOrder
+    )
     scan_out_list = [None] * len(rightOrder)
     for idx, pos in enumerate(rightOrder):
         if pos >= 0:

pytensor/scan/rewriting.py

@@ -110,7 +110,7 @@ def remove_constants_and_unused_inputs_scan(fgraph, node):
         sum(len(x) for x in chain(op_info.mit_mot_in_slices, op_info.mit_sot_in_slices))
     )
     st += op_info.n_sit_sot
-    st += op_info.n_shared_outs
+    st += op_info.n_untraced_sit_sot_outs
 
     op_ins = op.inner_inputs
     op_outs = op.inner_outputs
@@ -126,7 +126,7 @@ def remove_constants_and_unused_inputs_scan(fgraph, node):
         + op_info.n_mit_sot
         + op_info.n_sit_sot
         + op_info.n_nit_sot
-        + op_info.n_shared_outs
+        + op_info.n_untraced_sit_sot_outs
         + 1
     )
     outer_non_seqs = node.inputs[st:]
@@ -983,7 +983,7 @@ class ScanInplaceOptimizer(GraphRewriter):
         ls = op.outer_mitmot(node.inputs)
         ls += op.outer_mitsot(node.inputs)
         ls += op.outer_sitsot(node.inputs)
-        ls_end = op.outer_shared(node.inputs)
+        ls_end = op.outer_untraced_sit_sot(node.inputs)
         ls_end += op.outer_nitsot(node.inputs)
         ls_end += op.outer_non_seqs(node.inputs)
 
@@ -1628,7 +1628,7 @@ def scan_save_mem_rewrite(fgraph, node, backend_supports_output_pre_allocation:
                         + idx
                         + op_info.n_seqs
                         + 1
-                        + op_info.n_shared_outs
+                        + op_info.n_untraced_sit_sot_outs
                     )
                     if nw_inputs[pos] == node.inputs[0]:
                         nw_inputs[pos] = 1 if required_orphan else val
@@ -1662,7 +1662,7 @@ def scan_save_mem_rewrite(fgraph, node, backend_supports_output_pre_allocation:
                     elif (
                         idx < op_info.n_mit_sot + op_info.n_sit_sot + op_info.n_nit_sot
                     ):
-                        in_idx = offset + idx + op_info.n_shared_outs
+                        in_idx = offset + idx + op_info.n_untraced_sit_sot_outs
                         if nw_inputs[in_idx] == node.inputs[0]:
                             nw_inputs[in_idx] = nw_steps
 
@@ -1886,8 +1886,8 @@ class ScanMerge(GraphRewriter):
 
         for idx, nd in enumerate(nodes):
             # Shared
-            inner_ins[idx].append(nd.op.inner_shared(nd.op.inner_inputs))
-            outer_ins += nd.op.outer_shared(nd.inputs)
+            inner_ins[idx].append(nd.op.inner_untraced_sit_sot(nd.op.inner_inputs))
+            outer_ins += nd.op.outer_untraced_sit_sot(nd.inputs)
 
         for idx, nd in enumerate(nodes):
             # NitSot
@@ -1897,8 +1897,10 @@ class ScanMerge(GraphRewriter):
 
         for idx, nd in enumerate(nodes):
             # Shared
-            outer_outs += nd.op.outer_shared_outs(nd.outputs)
-            inner_outs[idx].append(nd.op.inner_shared_outs(nd.op.inner_outputs))
+            outer_outs += nd.op.outer_untraced_sit_sot_outs(nd.outputs)
+            inner_outs[idx].append(
+                nd.op.inner_untraced_sit_sot_outs(nd.op.inner_outputs)
+            )
 
         n_non_seqs = 0
         for idx, nd in enumerate(nodes):
@@ -1978,7 +1980,9 @@ class ScanMerge(GraphRewriter):
             mit_sot_in_slices=mit_sot_in_slices,
             sit_sot_in_slices=sit_sot_in_slices,
             n_nit_sot=sum(nd.op.info.n_nit_sot for nd in nodes),
-            n_shared_outs=sum(nd.op.info.n_shared_outs for nd in nodes),
+            n_untraced_sit_sot_outs=sum(
+                nd.op.info.n_untraced_sit_sot_outs for nd in nodes
+            ),
             n_non_seqs=n_non_seqs,
             as_while=as_while,
         )
@@ -2360,7 +2364,7 @@ def scan_push_out_dot1(fgraph, node):
     # When seq[t] is a vector/matrix  and `value` is a matrix
     # Note that this works when only you need X[-1] in the end
     # and assumes dimshuffle are applied to vectors before calling dot
-    op = node.op
+    op: Scan = node.op
     sitsot_ins = op.inner_sitsot(op.inner_inputs)
     sitsot_outs = op.inner_sitsot_outs(op.inner_outputs)
     outer_sitsot = op.outer_sitsot_outs(node.outputs)
@@ -2416,9 +2420,13 @@ def scan_push_out_dot1(fgraph, node):
                     inner_sitsot_outs = op.inner_sitsot_outs(op.inner_outputs)
                     outer_nitsot = op.outer_nitsot(node.inputs)
                     inner_nitsot_outs = op.inner_nitsot_outs(op.inner_outputs)
-                    inner_shared = op.inner_shared(op.inner_inputs)
-                    outer_shared = op.outer_shared(node.inputs)
-                    inner_shared_outs = op.inner_shared_outs(op.inner_outputs)
+                    inner_untraced_sitsot = op.inner_untraced_sitsot(op.inner_inputs)
+                    outer_untraced_sitsot_outs = op.outer_untraced_sitsot_outs(
+                        node.inputs
+                    )
+                    inner_untraced_sitsot_outs = op.inner_untraced_sitsot_outs(
+                        op.inner_outputs
+                    )
                     inner_non_seqs = op.inner_non_seqs(op.inner_inputs)
                     outer_non_seqs = op.outer_non_seqs(node.inputs)
 
@@ -2441,7 +2449,7 @@ def scan_push_out_dot1(fgraph, node):
                         + inner_mitmot
                         + inner_mitsot
                         + inner_sitsot
-                        + inner_shared
+                        + inner_untraced_sitsot
                         + inner_non_seqs
                     )
                     _new_inner_outs = (
@@ -2449,7 +2457,7 @@ def scan_push_out_dot1(fgraph, node):
                         + inner_mitsot_outs
                         + inner_sitsot_outs
                         + inner_nitsot_outs
-                        + inner_shared_outs
+                        + inner_untraced_sitsot_outs
                     )
                     new_inner_inps, new_inner_outs = reconstruct_graph(
                         _new_inner_inps, _new_inner_outs
@@ -2471,7 +2479,7 @@ def scan_push_out_dot1(fgraph, node):
                         *outer_mitmot,
                         *outer_mitsot,
                         *outer_sitsot,
-                        *outer_shared,
+                        *outer_untraced_sitsot_outs,
                         *outer_nitsot,
                         node.inputs[0],
                         *outer_non_seqs,

pytensor/scan/utils.py

@@ -370,7 +370,9 @@ def scan_can_remove_outs(op, out_idxs):
         out_ins += [op.inner_inputs[offset : offset + n_ins]]
         offset += n_ins
     out_ins += [[] for k in range(op.info.n_nit_sot)]
-    out_ins += [[op.inner_inputs[offset + k]] for k in range(op.info.n_shared_outs)]
+    out_ins += [
+        [op.inner_inputs[offset + k]] for k in range(op.info.n_untraced_sit_sot_outs)
+    ]
 
     added = True
     out_idxs_mask = [1 for idx in out_idxs]
@@ -409,7 +411,7 @@ def compress_outs(op, not_required, inputs):
         mit_sot_in_slices=(),
         sit_sot_in_slices=(),
         n_nit_sot=0,
-        n_shared_outs=0,
+        n_untraced_sit_sot_outs=0,
         n_non_seqs=0,
         as_while=op_info.as_while,
     )
@@ -515,17 +517,19 @@ def compress_outs(op, not_required, inputs):
             info = dataclasses.replace(info, n_nit_sot=info.n_nit_sot + 1)
             op_outputs += [op.inner_outputs[o_offset]]
             o_offset += 1
-            nit_sot_ins += [inputs[ni_offset + idx + op_info.n_shared_outs]]
+            nit_sot_ins += [inputs[ni_offset + idx + op_info.n_untraced_sit_sot_outs]]
         else:
             o_offset += 1
 
     offset += op_info.n_nit_sot
     shared_ins = []
-    for idx in range(op_info.n_shared_outs):
+    for idx in range(op_info.n_untraced_sit_sot_outs):
         if offset + idx not in not_required:
             map_old_new[offset + idx] = curr_pos
             curr_pos += 1
-            info = dataclasses.replace(info, n_shared_outs=info.n_shared_outs + 1)
+            info = dataclasses.replace(
+                info, n_untraced_sit_sot_outs=info.n_untraced_sit_sot_outs + 1
+            )
             op_outputs += [op.inner_outputs[o_offset]]
             o_offset += 1
             op_inputs += [op.inner_inputs[i_offset]]
@@ -539,7 +543,9 @@ def compress_outs(op, not_required, inputs):
     # other stuff
     op_inputs += op.inner_inputs[i_offset:]
     info = dataclasses.replace(info, n_non_seqs=len(op.inner_inputs[i_offset:]))
-    node_inputs += inputs[ni_offset + op_info.n_shared_outs + op_info.n_nit_sot :]
+    node_inputs += inputs[
+        ni_offset + op_info.n_untraced_sit_sot_outs + op_info.n_nit_sot :
+    ]
     if op_info.as_while:
         op_outputs += [op.inner_outputs[o_offset]]
         map_old_new[o_offset] = len(op_outputs) - 1
@@ -658,11 +664,11 @@ class ScanArgs:
         p += n_sit_sot
         q += n_sit_sot
 
-        n_shared_outs = info.n_shared_outs
-        self.outer_in_shared = list(outer_inputs[p : p + n_shared_outs])
-        self.inner_in_shared = list(inner_inputs[q : q + n_shared_outs])
-        p += n_shared_outs
-        q += n_shared_outs
+        n_untraced_sit_sot_outs = info.n_untraced_sit_sot_outs
+        self.outer_in_shared = list(outer_inputs[p : p + n_untraced_sit_sot_outs])
+        self.inner_in_shared = list(inner_inputs[q : q + n_untraced_sit_sot_outs])
+        p += n_untraced_sit_sot_outs
+        q += n_untraced_sit_sot_outs
 
         n_nit_sot = info.n_nit_sot
         self.outer_in_nit_sot = list(outer_inputs[p : p + n_nit_sot])
@@ -702,10 +708,10 @@ class ScanArgs:
         p += n_nit_sot
         q += n_nit_sot
 
-        self.outer_out_shared = list(outer_outputs[p : p + n_shared_outs])
-        self.inner_out_shared = list(inner_outputs[q : q + n_shared_outs])
-        p += n_shared_outs
-        q += n_shared_outs
+        self.outer_out_shared = list(outer_outputs[p : p + n_untraced_sit_sot_outs])
+        self.inner_out_shared = list(inner_outputs[q : q + n_untraced_sit_sot_outs])
+        p += n_untraced_sit_sot_outs
+        q += n_untraced_sit_sot_outs
 
         assert p == len(outer_outputs)
         assert q == len(inner_outputs)
@@ -816,7 +822,7 @@ class ScanArgs:
             mit_sot_in_slices=tuple(tuple(v) for v in self.mit_sot_in_slices),
             sit_sot_in_slices=((-1,),) * len(self.inner_in_sit_sot),
             n_nit_sot=len(self.outer_in_nit_sot),
-            n_shared_outs=len(self.outer_in_shared),
+            n_untraced_sit_sot_outs=len(self.outer_in_shared),
             n_non_seqs=len(self.inner_in_non_seqs),
             as_while=self.as_while,
         )

tests/link/numba/test_scan.py

@@ -85,7 +85,7 @@ from tests.link.numba.test_basic import compare_numba_and_py
             3,
             [],
             [np.array([0.50100236, 2.16822932, 1.36326596])],
-            lambda op: op.info.n_shared_outs > 0,
+            lambda op: op.info.n_untraced_sit_sot_outs > 0,
         ),
         # mit-sot (that's also a type of sit-sot)
         (

tests/scan/test_basic.py

@@ -42,11 +42,13 @@ from pytensor.tensor.math import all as pt_all
 from pytensor.tensor.math import dot, exp, mean, sigmoid, tanh
 from pytensor.tensor.math import sum as pt_sum
 from pytensor.tensor.random import normal
+from pytensor.tensor.random.type import RandomGeneratorType, random_generator_type
 from pytensor.tensor.random.utils import RandomStream
 from pytensor.tensor.shape import Shape_i, reshape, specify_shape
 from pytensor.tensor.sharedvar import SharedVariable
 from pytensor.tensor.subtensor import Subtensor
 from pytensor.tensor.type import (
+    TensorType,
     dcol,
     dmatrix,
     dscalar,
@@ -4007,7 +4009,7 @@ class TestExamples:
             [{}],
             [],
             3,
-            lambda op: op.info.n_shared_outs > 0,
+            lambda op: op.info.n_untraced_sit_sot_outs > 0,
         ),
         # mit-sot (that's also a type of sit-sot)
         (
@@ -4106,3 +4108,34 @@ def test_output_storage_reuse(linker_mode):
     res = f_cvm()
 
     assert np.array_equal(res, np.array([3, 1, 0]))
+
+
+def test_rng_outputs_info():
+    rng_init = random_generator_type("rng")
+    rng_x0, x0 = pt.random.normal(0, rng=rng_init, dtype="float64").owner.outputs
+
+    def step(prev_x, prev_rng):
+        next_rng, next_x = pt.random.normal(
+            prev_x, rng=prev_rng, dtype="float64"
+        ).owner.outputs
+        return next_x, next_rng
+
+    [xs, rng_final], updates = scan(
+        fn=step,
+        outputs_info=[x0, rng_x0],
+        n_steps=10,
+    )
+    assert isinstance(xs.type, TensorType)
+    assert isinstance(rng_final.type, RandomGeneratorType)
+    assert not updates
+
+    fn = function([rng_init], [xs, rng_final])
+    xs_eval, rng_final_eval = fn(np.random.default_rng(0))
+
+    rng_ref = np.random.default_rng(0)
+    assert not random_generator_type.values_eq(rng_ref, rng_final_eval)
+    xs_ref = [rng_ref.normal(0)]
+    for i in range(10):
+        xs_ref.append(rng_ref.normal(xs_ref[-1]))
+    assert random_generator_type.values_eq(rng_ref, rng_final_eval)
+    np.testing.assert_allclose(xs_eval, xs_ref[1:])