Do not recompute toposort in every iteration of FusionOptimizer

It's not really needed as we never expand on the new nodes

Author: ricardoV94

pytensor/tensor/rewriting/elemwise.py

@@ -625,10 +625,10 @@ def elemwise_scalar_op_has_c_code(node: Apply) -> bool:
 
             def find_fuseable_subgraph(
                 *,
-                fg: FunctionGraph,
                 visited_nodes: set[Apply],
                 fuseable_clients: FUSEABLE_MAPPING,
                 unfuseable_clients: UNFUSEABLE_MAPPING,
+                toposort_index: dict[Apply, int],
             ) -> tuple[list[Variable], list[Variable]]:
                 KT = TypeVar("KT")
                 VT = TypeVar("VT", list, set)
@@ -648,8 +648,7 @@ def variables_depend_on(
                         for a in ancestors(variables, blockers=stop_search_at)
                     )
 
-                toposort = fg.toposort()
-                for starting_node in toposort:
+                for starting_node in toposort_index:
                     if starting_node in visited_nodes:
                         continue
 
@@ -791,7 +790,7 @@ def variables_depend_on(
                                     and inp.owner not in visited_nodes
                                 )
                             ),
-                            key=lambda inp: toposort.index(inp.owner),
+                            key=lambda inp: toposort_index[inp.owner],
                             reverse=True,
                         ):
                             fuseable_nodes_to_visit.appendleft(inp.owner)
@@ -803,7 +802,7 @@ def variables_depend_on(
                                 for node in fuseable_clients_temp.get(next_out, ())
                                 if node not in visited_nodes
                             ),
-                            key=lambda node: toposort.index(node),
+                            key=lambda node: toposort_index[node],
                         ):
                             fuseable_nodes_to_visit.append(next_node)
 
@@ -877,20 +876,22 @@ def update_fuseable_mappings_after_fg_replace(
             # client (those that don't fit into 1))
             fuseable_clients, unfuseable_clients = initialize_fuseable_mappings(fg=fg)
             visited_nodes: set[Apply] = set()
+            toposort_index = {node: i for i, node in enumerate(fgraph.toposort())}
             while True:
-                starting_nodes = fg.apply_nodes.copy()
                 try:
                     subgraph_inputs, subgraph_outputs = find_fuseable_subgraph(
-                        fg=fg,
                         visited_nodes=visited_nodes,
                         fuseable_clients=fuseable_clients,
                         unfuseable_clients=unfuseable_clients,
+                        toposort_index=toposort_index,
                     )
                 except ValueError:
                     return
                 else:
                     # The caller is now expected to update fg in place,
                     # by replacing the subgraph with a Composite Op
+                    starting_nodes = fg.apply_nodes.copy()
+
                     yield subgraph_inputs, subgraph_outputs
 
                     # This is where we avoid repeated work by using a stateful