Guarantee unique signature variable names during Numba conversion

aesara/link/numba/dispatch.py

@@ -25,6 +25,7 @@ from aesara.link.utils import (
     compile_function_src,
     fgraph_to_python,
     get_name_for_object,
+    unique_name_generator,
 )
 from aesara.scalar.basic import (
     Cast,
@@ -352,11 +353,15 @@ def numba_funcify_ScalarOp(op, node, **kwargs):
     else:
         scalar_func = getattr(func_package, scalar_func_name)
 
-    input_names = ", ".join([v.auto_name for v in node.inputs])
+    scalar_op_fn_name = get_name_for_object(scalar_func)
+    unique_names = unique_name_generator(
+        [scalar_op_fn_name, "scalar_func"], suffix_sep="_"
+    )
+
+    input_names = ", ".join([unique_names(v, force_unique=True) for v in node.inputs])
 
     global_env = {"scalar_func": scalar_func}
 
-    scalar_op_fn_name = get_name_for_object(scalar_func)
     scalar_op_src = f"""
 def {scalar_op_fn_name}({input_names}):
     return scalar_func({input_names})
@@ -370,8 +375,6 @@ def {scalar_op_fn_name}({input_names}):
 def numba_funcify_Elemwise(op, node, use_signature=False, identity=None, **kwargs):
     scalar_op_fn = numba_funcify(op.scalar_op, node, **kwargs)
 
-    input_names = ", ".join([v.auto_name for v in node.inputs])
-
     if use_signature:
         signature = [create_numba_signature(node, force_scalar=True)]
     else:
@@ -381,6 +384,12 @@ def numba_funcify_Elemwise(op, node, use_signature=False, identity=None, **kwarg
     global_env = {"scalar_op": scalar_op_fn, "numba_vectorize": numba_vectorize}
 
     elemwise_fn_name = f"elemwise_{get_name_for_object(scalar_op_fn)}"
+
+    unique_names = unique_name_generator(
+        [elemwise_fn_name, "scalar_op", "scalar_op", "numba_vectorize"], suffix_sep="_"
+    )
+    input_names = ", ".join([unique_names(v, force_unique=True) for v in node.inputs])
+
     elemwise_src = f"""
 @numba_vectorize
 def {elemwise_fn_name}({input_names}):
@@ -574,7 +583,11 @@ def create_index_func(node, objmode=False):
     )
     index_start_idx = 1 + int(set_or_inc)
 
-    input_names = [v.auto_name for v in node.inputs]
+    unique_names = unique_name_generator(
+        ["subtensor", "incsubtensor", "z"], suffix_sep="_"
+    )
+
+    input_names = [unique_names(v, force_unique=True) for v in node.inputs]
     op_indices = list(node.inputs[index_start_idx:])
     idx_list = getattr(node.op, "idx_list", None)
 
@@ -756,7 +769,10 @@ def numba_funcify_AllocEmpty(op, node, **kwargs):
 
     global_env = {"np": np, "to_scalar": to_scalar, "dtype": op.dtype}
 
-    shape_var_names = [v.auto_name for v in node.inputs]
+    unique_names = unique_name_generator(
+        ["np", "to_scalar", "dtype", "allocempty", "scalar_shape"], suffix_sep="_"
+    )
+    shape_var_names = [unique_names(v, force_unique=True) for v in node.inputs]
     shape_var_item_names = [f"{name}_item" for name in shape_var_names]
     shapes_to_items_src = indent(
         "\n".join(
@@ -785,7 +801,11 @@ def numba_funcify_Alloc(op, node, **kwargs):
 
     global_env = {"np": np, "to_scalar": to_scalar}
 
-    shape_var_names = [v.auto_name for v in node.inputs[1:]]
+    unique_names = unique_name_generator(
+        ["np", "to_scalar", "alloc", "val_np", "val", "scalar_shape", "res"],
+        suffix_sep="_",
+    )
+    shape_var_names = [unique_names(v, force_unique=True) for v in node.inputs[1:]]
     shape_var_item_names = [f"{name}_item" for name in shape_var_names]
     shapes_to_items_src = indent(
         "\n".join(