chore: Rename to CudaGraphsTorchTensorRTModule class

Author: keehyuna

Diff for: examples/dynamo/cudagraphs_wrapper_example.py

@@ -12,8 +12,8 @@
 from torch_tensorrt._features import ENABLED_FEATURES
 from torch_tensorrt._Input import Input
 from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._WrapperTorchTensorRTModule import (
-    WrapperTorchTensorRTModule,
+from torch_tensorrt.dynamo.runtime._CudaGraphsTorchTensorRTModule import (
+    CudaGraphsTorchTensorRTModule,
 )
 from torch_tensorrt.fx import InputTensorSpec
 from torch_tensorrt.fx.lower import compile as fx_compile
@@ -589,15 +589,15 @@ def save(
     Save the model to disk in the specified output format.
 
     Arguments:
-        module (Optional(torch.jit.ScriptModule | torch.export.ExportedProgram | torch.fx.GraphModule | WrapperTorchTensorRTModule)): Compiled Torch-TensorRT module
+        module (Optional(torch.jit.ScriptModule | torch.export.ExportedProgram | torch.fx.GraphModule | CudaGraphsTorchTensorRTModule)): Compiled Torch-TensorRT module
         inputs (torch.Tensor): Torch input tensors
         arg_inputs (Tuple[Any, ...]): Same as inputs. Alias for better understanding with kwarg_inputs.
         kwarg_inputs (dict[Any, ...]): Optional, kwarg inputs to the module forward function.
         output_format (str): Format to save the model. Options include exported_program | torchscript.
         retrace (bool): When the module type is a fx.GraphModule, this option re-exports the graph using torch.export.export(strict=False) to save it.
                 This flag is experimental for now.
     """
-    if isinstance(module, WrapperTorchTensorRTModule):
+    if isinstance(module, CudaGraphsTorchTensorRTModule):
         module = module.compiled_module
     module_type = _parse_module_type(module)
     accepted_formats = {"exported_program", "torchscript"}

Diff for: py/torch_tensorrt/_compile.py

@@ -11,7 +11,7 @@
 logger = logging.getLogger(__name__)
 
 
-class WrapperTorchTensorRTModule(torch.nn.Module):  # type: ignore[misc]
+class CudaGraphsTorchTensorRTModule(torch.nn.Module):  # type: ignore[misc]
     """This Wrapper runtime module is to record/replay whole cuda graph in sub modules
 
     Args:
@@ -24,7 +24,7 @@ def __init__(
         self,
         compiled_module: torch.nn.Module,
     ):
-        super(WrapperTorchTensorRTModule, self).__init__()
+        super(CudaGraphsTorchTensorRTModule, self).__init__()
         self.compiled_module = compiled_module
         self.inputs = partitioning.construct_submodule_inputs(compiled_module)
 

Diff for: py/torch_tensorrt/dynamo/runtime/_WrapperTorchTensorRTModule.py renamed to py/torch_tensorrt/dynamo/runtime/_CudaGraphsTorchTensorRTModule.py

@@ -3,8 +3,8 @@
 
 import torch
 import torch_tensorrt
-from torch_tensorrt.dynamo.runtime._WrapperTorchTensorRTModule import (
-    WrapperTorchTensorRTModule,
+from torch_tensorrt.dynamo.runtime._CudaGraphsTorchTensorRTModule import (
+    CudaGraphsTorchTensorRTModule,
 )
 
 
@@ -90,7 +90,7 @@ def __enter__(self) -> torch.nn.Module:
             logger.debug(
                 f"{num_torch_module} torch modules are in subgraphs. Using wrapper module for cuda graphs"
             )
-            return WrapperTorchTensorRTModule(self.compiled_module)
+            return CudaGraphsTorchTensorRTModule(self.compiled_module)
         else:
             if num_trt_module > 0:
                 logger.debug(

Diff for: py/torch_tensorrt/runtime/_cudagraphs.py

@@ -3,8 +3,8 @@
 
 import torch
 from torch_tensorrt.dynamo.runtime import PythonTorchTensorRTModule, TorchTensorRTModule
-from torch_tensorrt.dynamo.runtime._WrapperTorchTensorRTModule import (
-    WrapperTorchTensorRTModule,
+from torch_tensorrt.dynamo.runtime._CudaGraphsTorchTensorRTModule import (
+    CudaGraphsTorchTensorRTModule,
 )
 
 logger = logging.getLogger(__name__)
@@ -16,12 +16,12 @@ class _WeightStreamingContextManager(object):
     """
 
     def __init__(
-        self, module: torch.fx.GraphModule | WrapperTorchTensorRTModule
+        self, module: torch.fx.GraphModule | CudaGraphsTorchTensorRTModule
     ) -> None:
         rt_mods = []
         self.current_device_budget = 0
 
-        if isinstance(module, WrapperTorchTensorRTModule):
+        if isinstance(module, CudaGraphsTorchTensorRTModule):
             module = module.compiled_module
         for name, rt_mod in module.named_children():
             if "_run_on_acc" in name and isinstance(