turn off normalize_ir, turn on use_functionalization by default (#1050)

* turn off normalize_ir, turn on use_functionalization by default

ghstack-source-id: 86d8054
Pull Request resolved: #1026

* add to CI skip list

* lint

* force CI to re-run

* force CI rerun

Author: bdhirsh

benchmarks/common.py

@@ -93,6 +93,12 @@ def set_model_name(name):
     "mobilenet_",
     "pytorch_struct",
     "vgg16",
+    "Background_Matting",  # from functionalization
+    "mobilenet_v2_quantized_qat",  # from functionalization
+    "resnet50_quantized_qat",  # from functionalization
+    "speech_transformer",  # from functionalization
+    "vision_maskrcnn",  # from functionalization
+    "timm_efficientnet",  # from functionalization (only fails for inductor)
     # Huggingface
     "AlbertForMaskedLM",
     "BartForConditionalGeneration",

torchdynamo/__init__.py

@@ -1,3 +1,6 @@
+# TODO: remove this config entirely
+import functorch.compile
+
 from . import allowed_functions
 from . import convert_frame
 from . import eval_frame
@@ -13,6 +16,8 @@
 from .utils import guard_failures
 from .utils import orig_code_map
 
+functorch.compile.config.use_functionalize = True
+
 __all__ = [
     "optimize",
     "optimize_assert",

torchdynamo/config.py

@@ -66,7 +66,7 @@ class AccessLimitingConfig(ModuleType):
     fake_tensor_propagation = True
 
     # run FX normalization passes in optimizer
-    normalize_ir = True
+    normalize_ir = False
 
     # If a tensor subclass type is in this set, torchdynamo will inline the
     # __torch_function__ logic of the subclass.