replace allow_complex_guards_as_runtime_assertswithprefer_deferred_ru…

examples/apps/flux_demo.py

@@ -121,7 +121,7 @@ def forward_loop(mod):
 
     settings = {
         "strict": False,
-        "allow_complex_guards_as_runtime_asserts": True,
+        "prefer_deferred_runtime_asserts_over_guards": True,
         "enabled_precisions": enabled_precisions,
         "truncate_double": True,
         "min_block_size": 1,

examples/dynamo/torch_export_flux_dev.py

@@ -92,7 +92,7 @@
     kwargs=dummy_inputs,
     dynamic_shapes=dynamic_shapes,
     strict=False,
-    allow_complex_guards_as_runtime_asserts=True,
+    prefer_deferred_runtime_asserts_over_guards=True,
 )
 
 # %%

examples/dynamo/weight_streaming_example.py

@@ -65,7 +65,7 @@ def export_llm(model, inputs, min_seq_len=1, max_seq_len=16):
                 kwargs={"position_ids": position_ids},
                 dynamic_shapes=({1: seq_len}, {1: seq_len}),
                 strict=False,
-                allow_complex_guards_as_runtime_asserts=True,
+                prefer_deferred_runtime_asserts_over_guards=True,
             )
 
     return ep

py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py

@@ -68,7 +68,7 @@ def __init__(
         use_python_runtime: bool = _defaults.USE_PYTHON_RUNTIME,
         immutable_weights: bool = False,
         strict: bool = True,
-        allow_complex_guards_as_runtime_asserts: bool = False,
+        prefer_deferred_runtime_asserts_over_guards: bool = False,
         weight_streaming_budget: Optional[int] = None,
         enabled_precisions: Optional[Set[Union[torch.dtype, dtype]]] = None,
         **kwargs: Any,
@@ -134,8 +134,8 @@ def __init__(
         self.kwarg_inputs: dict[str, Any] = {}
         self.additional_settings = kwargs
         self.strict = strict
-        self.allow_complex_guards_as_runtime_asserts = (
-            allow_complex_guards_as_runtime_asserts
+        self.prefer_deferred_runtime_asserts_over_guards = (
+            prefer_deferred_runtime_asserts_over_guards
         )
         self.use_python_runtime = use_python_runtime
         self.trt_device = to_torch_tensorrt_device(device)
@@ -312,14 +312,14 @@ def refit_gm(self) -> None:
     def get_exported_program(self) -> torch.export.ExportedProgram:
 
         def export_fn() -> torch.export.ExportedProgram:
-            if self.allow_complex_guards_as_runtime_asserts:
+            if self.prefer_deferred_runtime_asserts_over_guards:
                 return _export(
                     self.original_model,
                     self.arg_inputs,
                     kwargs=self.kwarg_inputs,
                     dynamic_shapes=self._get_total_dynamic_shapes(),
                     strict=self.strict,
-                    allow_complex_guards_as_runtime_asserts=self.allow_complex_guards_as_runtime_asserts,
+                    prefer_deferred_runtime_asserts_over_guards=self.prefer_deferred_runtime_asserts_over_guards,
                 )
             else:
                 return torch.export.export(

tests/py/dynamo/models/test_engine_cache.py

@@ -856,7 +856,7 @@ def export_llm(model, inputs, min_seq_len=1, max_seq_len=16):
                         (inputs,),
                         dynamic_shapes=({1: seq_len},),
                         strict=False,
-                        allow_complex_guards_as_runtime_asserts=True,
+                        prefer_deferred_runtime_asserts_over_guards=True,
                     )
 
             return ep

tools/llm/test_llama_components.py

@@ -79,7 +79,7 @@ def test_llama_attention(args):
         args=(hidden_states, position_embeddings, None),
         dynamic_shapes=dynamic_shapes,
         strict=False,
-        allow_complex_guards_as_runtime_asserts=True,
+        prefer_deferred_runtime_asserts_over_guards=True,
     )
 
     with torch_tensorrt.logging.debug() if args.debug else nullcontext():
@@ -463,7 +463,7 @@ def test_llama_model(args):
         kwargs=kwarg_inputs,
         dynamic_shapes=dynamic_shapes,
         strict=False,
-        allow_complex_guards_as_runtime_asserts=True,
+        prefer_deferred_runtime_asserts_over_guards=True,
     )
 
     with torch_tensorrt.logging.debug() if args.debug else nullcontext():

tools/llm/utils.py

@@ -41,7 +41,7 @@ def export_llm(model, inputs, min_seq_len=1, max_seq_len=16):
                 kwargs={"position_ids": position_ids},
                 dynamic_shapes=({1: seq_len}, {1: seq_len}),
                 strict=False,
-                allow_complex_guards_as_runtime_asserts=True,
+                prefer_deferred_runtime_asserts_over_guards=True,
             )
 
     return ep

tools/perf/utils.py

@@ -228,7 +228,7 @@ def export_llm(model, inputs, min_seq_len=1, max_seq_len=16):
                 (inputs,),
                 dynamic_shapes=({1: seq_len},),
                 strict=False,
-                allow_complex_guards_as_runtime_asserts=True,
+                prefer_deferred_runtime_asserts_over_guards=True,
             )
 
     return ep