Type two functions in graph/rewriting/utils.py

pytensor/graph/basic.py

@@ -986,7 +986,7 @@ def explicit_graph_inputs(
 
 
 def vars_between(
-    ins: Collection[Variable], outs: Iterable[Variable]
+    ins: Iterable[Variable], outs: Iterable[Variable]
 ) -> Generator[Variable, None, None]:
     r"""Extract the `Variable`\s within the sub-graph between input and output nodes.
 
@@ -1006,6 +1006,8 @@ def vars_between(
 
     """
 
+    ins = set(ins)
+
     def expand(r: Variable) -> Iterable[Variable] | None:
         if r.owner and r not in ins:
             return reversed(r.owner.inputs + r.owner.outputs)

pytensor/graph/rewriting/utils.py

@@ -72,7 +72,16 @@ def rewrite_graph(
             return fgraph.outputs[0]
 
 
-def is_same_graph_with_merge(var1, var2, givens=None):
+def is_same_graph_with_merge(
+    var1: Variable,
+    var2: Variable,
+    givens: (
+        list[tuple[Variable, Variable]]
+        | tuple[tuple[Variable, Variable], ...]
+        | dict[Variable, Variable]
+        | None
+    ) = None,
+) -> bool:
     """
     Merge-based implementation of `pytensor.graph.basic.is_same_graph`.
 
@@ -83,8 +92,10 @@ def is_same_graph_with_merge(var1, var2, givens=None):
 
     if givens is None:
         givens = {}
+    givens = dict(givens)
+
     # Copy variables since the MergeOptimizer will modify them.
-    copied = copy.deepcopy([var1, var2, givens])
+    copied = copy.deepcopy((var1, var2, givens))
     vars = copied[0:2]
     givens = copied[2]
     # Create FunctionGraph.
@@ -113,7 +124,16 @@ def is_same_graph_with_merge(var1, var2, givens=None):
         return o1 is o2
 
 
-def is_same_graph(var1, var2, givens=None):
+def is_same_graph(
+    var1: Variable,
+    var2: Variable,
+    givens: (
+        list[tuple[Variable, Variable]]
+        | tuple[tuple[Variable, Variable], ...]
+        | dict[Variable, Variable]
+        | None
+    ) = None,
+) -> bool:
     """
     Return True iff Variables `var1` and `var2` perform the same computation.
 
@@ -155,8 +175,6 @@ def is_same_graph(var1, var2, givens=None):
 
     if givens is None:
         givens = {}
-
-    if not isinstance(givens, dict):
     givens = dict(givens)
 
     # Get result from the merge-based function.
@@ -174,10 +192,11 @@ def is_same_graph(var1, var2, givens=None):
         in_xs = []
         in_ys = []
         # Compute the sets of all variables found in each computational graph.
-        inputs_var = list(map(graph_inputs, ([var1], [var2])))
+        inputs_var1 = graph_inputs([var1])
+        inputs_var2 = graph_inputs([var2])
         all_vars = [
             set(vars_between(v_i, v_o))
-            for v_i, v_o in ((inputs_var[0], [var1]), (inputs_var[1], [var2]))
+            for v_i, v_o in ((inputs_var1, [var1]), (inputs_var2, [var2]))
         ]
 
         def in_var(x, k):