prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Add Test Suite for `torch.compile` backend Partitioning/Lowering Phases
  - Add robust test suite for `torch.compile` backend, ensuring each phase functions correctly
  - Add general-purpose utilities for test expansion as the backend evolves
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `py/torch_tensorrt/dynamo/torch_compile/utils.py`
  Content:
  ```
  1 import torch
  2 
  3 from typing import Any, Union, Sequence, Dict
  4 from torch_tensorrt import _Input, Device
  5 
  6 
  7 def prepare_inputs(
  8     inputs: Union[_Input.Input, torch.Tensor, Sequence, Dict],
  9     device: torch.device = torch.device("cuda"),
  10 ) -> Any:
  11     if isinstance(inputs, _Input.Input):
  12         if isinstance(inputs.shape, dict):
  13             return inputs.example_tensor(optimization_profile_field="opt_shape").to(
  14                 device
  15             )
  16         else:
  17             return inputs.example_tensor().to(device)
  18 
  19     elif isinstance(inputs, torch.Tensor):
  20         return inputs
  21 
  22     elif isinstance(inputs, list):
  23         prepared_input = list()
  24 
  25         for input_obj in inputs:
  26             prepared_input.append(prepare_inputs(input_obj))
  27 
  28         return prepared_input
  29 
  30     elif isinstance(inputs, tuple):
  31         prepared_input = list()
  32 
  33         for input_obj in inputs:
  34             prepared_input.append(prepare_inputs(input_obj))
  35 
  36         return tuple(prepared_input)
  37 
  38     elif isinstance(inputs, dict):
  39         prepared_input = dict()
  40 
  41         for key, input_obj in inputs.items():
  42             prepared_input[key] = prepare_inputs(input_obj)
  43 
  44         return prepared_input
  45 
  46     else:
  47         raise ValueError(
  48             f"Invalid input type {type(inputs)} encountered in the torch_compile input parsing. "
  49             + "Allowed input types: {torch_tensorrt.Input, torch.Tensor, list, tuple, dict}"
  50         )
  51 
  52 
  53 def prepare_device(device: Union[Device, torch.device]) -> torch.device:
  54     if isinstance(device, Device):
  55         if device.gpu_id != -1:
  56             device = torch.device(device.gpu_id)
  57         else:
  58             raise ValueError("Invalid GPU ID provided for the CUDA device provided")
  59 
  60     elif isinstance(device, torch.device):
  61         device = device
  62 
  63     else:
  64         raise ValueError(
  65             "Invalid device provided. Supported options: torch.device | torch_tensorrt.Device"
  66         )
  67
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/py/torch_tensorrt/dynamo/torch_compile/utils.py b/py/torch_tensorrt/dynamo/torch_compile/utils.py
  --- a/py/torch_tensorrt/dynamo/torch_compile/utils.py
  +++ b/py/torch_tensorrt/dynamo/torch_compile/utils.py
  @@ -64,3 +64,5 @@
           raise ValueError(
               "Invalid device provided. Supported options: torch.device | torch_tensorrt.Device"
           )
  +
  +    return device
  
verification_info: {"golden_diff": "diff --git a/py/torch_tensorrt/dynamo/torch_compile/utils.py b/py/torch_tensorrt/dynamo/torch_compile/utils.py\n--- a/py/torch_tensorrt/dynamo/torch_compile/utils.py\n+++ b/py/torch_tensorrt/dynamo/torch_compile/utils.py\n@@ -64,3 +64,5 @@\n         raise ValueError(\n             \"Invalid device provided. Supported options: torch.device | torch_tensorrt.Device\"\n         )\n+\n+    return device\n", "issue": "Add Test Suite for `torch.compile` backend Partitioning/Lowering Phases\n- Add robust test suite for `torch.compile` backend, ensuring each phase functions correctly\r\n- Add general-purpose utilities for test expansion as the backend evolves\n", "before_files": [{"content": "import torch\n\nfrom typing import Any, Union, Sequence, Dict\nfrom torch_tensorrt import _Input, Device\n\n\ndef prepare_inputs(\n    inputs: Union[_Input.Input, torch.Tensor, Sequence, Dict],\n    device: torch.device = torch.device(\"cuda\"),\n) -> Any:\n    if isinstance(inputs, _Input.Input):\n        if isinstance(inputs.shape, dict):\n            return inputs.example_tensor(optimization_profile_field=\"opt_shape\").to(\n                device\n            )\n        else:\n            return inputs.example_tensor().to(device)\n\n    elif isinstance(inputs, torch.Tensor):\n        return inputs\n\n    elif isinstance(inputs, list):\n        prepared_input = list()\n\n        for input_obj in inputs:\n            prepared_input.append(prepare_inputs(input_obj))\n\n        return prepared_input\n\n    elif isinstance(inputs, tuple):\n        prepared_input = list()\n\n        for input_obj in inputs:\n            prepared_input.append(prepare_inputs(input_obj))\n\n        return tuple(prepared_input)\n\n    elif isinstance(inputs, dict):\n        prepared_input = dict()\n\n        for key, input_obj in inputs.items():\n            prepared_input[key] = prepare_inputs(input_obj)\n\n        return prepared_input\n\n    else:\n        raise ValueError(\n            f\"Invalid input type {type(inputs)} encountered in the torch_compile input parsing. \"\n            + \"Allowed input types: {torch_tensorrt.Input, torch.Tensor, list, tuple, dict}\"\n        )\n\n\ndef prepare_device(device: Union[Device, torch.device]) -> torch.device:\n    if isinstance(device, Device):\n        if device.gpu_id != -1:\n            device = torch.device(device.gpu_id)\n        else:\n            raise ValueError(\"Invalid GPU ID provided for the CUDA device provided\")\n\n    elif isinstance(device, torch.device):\n        device = device\n\n    else:\n        raise ValueError(\n            \"Invalid device provided. Supported options: torch.device | torch_tensorrt.Device\"\n        )\n", "path": "py/torch_tensorrt/dynamo/torch_compile/utils.py"}], "after_files": [{"content": "import torch\n\nfrom typing import Any, Union, Sequence, Dict\nfrom torch_tensorrt import _Input, Device\n\n\ndef prepare_inputs(\n    inputs: Union[_Input.Input, torch.Tensor, Sequence, Dict],\n    device: torch.device = torch.device(\"cuda\"),\n) -> Any:\n    if isinstance(inputs, _Input.Input):\n        if isinstance(inputs.shape, dict):\n            return inputs.example_tensor(optimization_profile_field=\"opt_shape\").to(\n                device\n            )\n        else:\n            return inputs.example_tensor().to(device)\n\n    elif isinstance(inputs, torch.Tensor):\n        return inputs\n\n    elif isinstance(inputs, list):\n        prepared_input = list()\n\n        for input_obj in inputs:\n            prepared_input.append(prepare_inputs(input_obj))\n\n        return prepared_input\n\n    elif isinstance(inputs, tuple):\n        prepared_input = list()\n\n        for input_obj in inputs:\n            prepared_input.append(prepare_inputs(input_obj))\n\n        return tuple(prepared_input)\n\n    elif isinstance(inputs, dict):\n        prepared_input = dict()\n\n        for key, input_obj in inputs.items():\n            prepared_input[key] = prepare_inputs(input_obj)\n\n        return prepared_input\n\n    else:\n        raise ValueError(\n            f\"Invalid input type {type(inputs)} encountered in the torch_compile input parsing. \"\n            + \"Allowed input types: {torch_tensorrt.Input, torch.Tensor, list, tuple, dict}\"\n        )\n\n\ndef prepare_device(device: Union[Device, torch.device]) -> torch.device:\n    if isinstance(device, Device):\n        if device.gpu_id != -1:\n            device = torch.device(device.gpu_id)\n        else:\n            raise ValueError(\"Invalid GPU ID provided for the CUDA device provided\")\n\n    elif isinstance(device, torch.device):\n        device = device\n\n    else:\n        raise ValueError(\n            \"Invalid device provided. Supported options: torch.device | torch_tensorrt.Device\"\n        )\n\n    return device\n", "path": "py/torch_tensorrt/dynamo/torch_compile/utils.py"}]}