Simplify in2out and out2in construction

aesara/graph/opt.py

@@ -15,7 +15,7 @@ import traceback
 import warnings
 from collections import OrderedDict, UserList, defaultdict, deque
 from collections.abc import Iterable
-from functools import reduce
+from functools import partial, reduce
 from typing import Dict, List, Optional, Tuple, Union
 
 import numpy as np
@@ -2172,34 +2172,11 @@ class TopoOptimizer(NavigatorOptimizer):
         return getattr(self, "__name__", "<TopoOptimizer instance>")
 
 
-def out2in(*local_opts, **kwargs):
-    """
-    Uses the TopoOptimizer from the output nodes to input nodes of the graph.
-    """
-    name = kwargs and kwargs.pop("name", None)
-    if len(local_opts) > 1:
-        # Don't wrap it uselessly if their is only 1 optimization.
-        local_opts = LocalOptGroup(*local_opts)
-    else:
-        (local_opts,) = local_opts
-        if not name:
-            name = local_opts.__name__
-    ret = TopoOptimizer(
-        local_opts,
-        order="out_to_in",
-        failure_callback=TopoOptimizer.warn_inplace,
-        **kwargs,
-    )
-    if name:
-        ret.__name__ = name
-    return ret
-
+def topogroup_optimizer(order, *local_opts, name=None, **kwargs):
+    """Apply `local_opts` from the input/output nodes to the output/input nodes of a graph.
 
-def in2out(*local_opts, **kwargs):
-    """
-    Uses the TopoOptimizer from the input nodes to output nodes of the graph.
+    This uses a combination of `LocalOptGroup` and `TopoOptimizer`.
     """
-    name = kwargs and kwargs.pop("name", None)
     if len(local_opts) > 1:
         # Don't wrap it uselessly if their is only 1 optimization.
         local_opts = LocalOptGroup(*local_opts)
@@ -2218,6 +2195,10 @@ def in2out(*local_opts, **kwargs):
     return ret
 
 
+in2out = partial(topogroup_optimizer, "in_to_out")
+out2in = partial(topogroup_optimizer, "out_to_in")
+
+
 class OpKeyOptimizer(NavigatorOptimizer):
     r"""An optimizer that applies a `LocalOptimizer` to specific `Op`\s.