diff --git a/torchchat/utils/build_utils.py b/torchchat/utils/build_utils.py
index abda72d70..c9a9eae14 100644
--- a/torchchat/utils/build_utils.py
+++ b/torchchat/utils/build_utils.py
@@ -6,6 +6,7 @@
 
 from __future__ import annotations
 
+from enum import Enum
 import logging
 import os
 from pathlib import Path
@@ -78,36 +79,33 @@ def set_backend(dso, pte):
     active_builder_args_pte = pte
 
 
-def use_aoti_backend() -> bool:
+class _Backend(Enum):
+    AOTI = 0,
+    EXECUTORCH = 1
+
+
+def _active_backend() -> _Backend:
     global active_builder_args_dso
     global active_builder_args_pte
 
     # eager == aoti, which is when backend has not been explicitly set
     if (not active_builder_args_dso) and not (active_builder_args_pte):
-        return True
+        return _Backend.AOTI
 
     if active_builder_args_pte and active_builder_args_dso:
         raise RuntimeError(
             "code generation needs to choose different implementations for DSO and PTE path.  Please only use one export option, and call export twice if necessary!"
         )
 
-    return bool(active_builder_args_dso)
+    return _Backend.AOTI if active_builder_args_dso else _Backend.EXECUTORCH
 
 
-def use_et_backend() -> bool:
-    global active_builder_args_dso
-    global active_builder_args_pte
-
-    # eager == aoti, which is when backend has not been explicitly set
-    if not (active_builder_args_pte or active_builder_args_dso):
-        return False
+def use_aoti_backend() -> bool:
+    return _active_backend() == _Backend.AOTI
 
-    if active_builder_args_pte and active_builder_args_dso:
-        raise RuntimeError(
-            "code generation needs to choose different implementations for DSO and PTE path.  Please only use one export option, and call export twice if necessary!"
-        )
 
-    return bool(active_builder_args_pte)
+def use_et_backend() -> bool:
+    return _active_backend() == _Backend.EXECUTORCH
 
 
 ##########################################################################
@@ -142,9 +140,9 @@ def name_to_dtype(name, device):
                 return torch.float16
         return torch.bfloat16
 
-    if name in name_to_dtype_dict:
+    try:
         return name_to_dtype_dict[name]
-    else:
+    except KeyError:
         raise RuntimeError(f"unsupported dtype name {name} specified")
 
 
@@ -212,10 +210,7 @@ def canonical_path(path):
 
 
 def state_dict_device(d, device="cpu") -> Dict:
-    for key, weight in d.items():
-        d[key] = weight.to(device=device)
-
-    return d
+    return {key : weight.to(device=device) for (key, weight) in d.items()}
 
 
 #########################################################################
@@ -259,9 +254,9 @@ def get_device(device) -> str:
     return torch.device(device)
 
 
-def is_cuda_or_cpu_device(device) -> bool:
-    return device == "" or str(device) == "cpu" or ("cuda" in str(device))
-
-
 def is_cpu_device(device) -> bool:
     return device == "" or str(device) == "cpu"
+
+
+def is_cuda_or_cpu_device(device) -> bool:
+    return is_cpu_device(device) or ("cuda" in str(device))