pytorch
diff --git a/‎torch/_inductor/compile_fx.py
Lines changed: 18 additions & 15 deletions b/‎torch/_inductor/compile_fx.py
Lines changed: 18 additions & 15 deletions
diff --git a/‎torch/_inductor/config.py
Lines changed: 1 addition & 1 deletion b/‎torch/_inductor/config.py
Lines changed: 1 addition & 1 deletion
@@ -13,7 +13,7 @@
 import warnings
 from abc import ABC, abstractmethod
 from collections import defaultdict
-from contextlib import AbstractContextManager
+from contextlib import AbstractContextManager, nullcontext
 from inspect import currentframe
 from itertools import count
 from typing import Any, Callable, Optional, TYPE_CHECKING, TypeVar, Union
@@ -1530,35 +1530,34 @@ def compile_fx_aot(
     model_: GraphModule,
     example_inputs_: list[InputType],
     inner_compile: _CompileFxCallable = compile_fx_inner,
-    config_patches: Optional[dict[str, str]] = None,
+    config_patches: Optional[dict[str, Any]] = None,
 ) -> Union[list[str], str]:
     assert isinstance(model_, GraphModule), model_
 
     # [See NOTE] Unwrapping subclasses AOT
     unwrap_tensor_subclass_parameters(model_)
 
-    config_patches: dict[str, Any] = (
-        {"cpp_wrapper": True}
-        if config_patches is None
-        else {**config_patches, "cpp_wrapper": True}
+    if config_patches is None:
+        config_patches = {}
 
-    output_path = config_patches.get(
-        "aot_inductor.output_path", config.aot_inductor.output_path
+    config_patches.update(
+        cpp_wrapper=True,
+        freezing=config.freezing
+        if config.freezing is not None
+        else not config.aot_inductor.use_runtime_constant_folding,
     )
 
-    if output_path:
+    if output_path := config_patches.get(
+        "aot_inductor.output_path", config.aot_inductor.output_path
+    ):
         assert not output_path.endswith(".pt2"), (
             "The output path for aot_compile should not have an extension with .pt2 "
             "this is for specifying the output path for the .so in AOTInductor. "
             "If you would like to package the AOTInductor generated files "
             "into a pt2, please call `torch._inductor.aoti_compile_and_package`."
         )
     else:
-        config_patches = {
-            **config_patches,
-            "aot_inductor.output_path": code_hash(model_.code),
-        }
+        config_patches["aot_inductor.output_path"] = code_hash(model_.code)
 
     extern_node_serializer = config_patches.pop("extern_node_serializer", None)
     saved_compile_id = model_.meta.get("dynamo_compile_id", None)
@@ -1664,7 +1663,11 @@ def fw_compiler_freezing(
         if tracing_context.fw_metadata:
             static_input_idxs += tracing_context.fw_metadata.static_input_indices
 
-    with mock.patch.object(fake_mode, "allow_non_fake_inputs", True):
+    with (
+        mock.patch.object(fake_mode, "allow_non_fake_inputs", True)
+        if fake_mode
+        else nullcontext()
+    ):
         optimized_function = inner_compile(
             opt_model,
             aot_example_inputs,
 
@@ -844,7 +844,7 @@ def decide_compile_threads() -> int:
 # Freezing will attempt to inline weights as constants in optimization
 # and run constant folding and other optimizations on them. After freezing, weights
 # can no longer be updated.
-freezing: bool = os.environ.get("TORCHINDUCTOR_FREEZING", "0") == "1"
+freezing: Optional[bool] = get_tristate_env("TORCHINDUCTOR_FREEZING")
 
 # Make freezing invalidate the eager Parameters of nn modules, to avoid memory overhead
 # of potentially keeping multiple copies of weights.