🐛 [Bug] run llm exmples are broken in thor platform

[lanluo-nvidia]

Bug Description

Trying to export the model using torch.export.export()..
Trying torch.export._trace._export to trace the graph since torch.export.export() failed
WARNING:py.warnings:/opt/conda/envs/py310/lib/python3.10/copyreg.py:101: FutureWarning: `isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.
  return cls.__new__(cls, *args)

WARNING:py.warnings:/workspace/TensorRT/tools/llm/cache_utils.py:126: FutureWarning: `treespec.children_specs` is deprecated. Use `treespec.child(index)` to access a single child, or `treespec.children()` to get all children.
  in_spec_for_args = in_spec.children_specs[0]

WARNING:py.warnings:/workspace/TensorRT/tools/llm/cache_utils.py:134: FutureWarning: `treespec.children_specs` is deprecated. Use `treespec.child(index)` to access a single child, or `treespec.children()` to get all children.
  in_spec_for_args.children_specs.append(_LEAF_SPEC)

WARNING:py.warnings:/workspace/TensorRT/tools/llm/cache_utils.py:139: FutureWarning: `treespec.children_specs` is deprecated. Use `treespec.child(index)` to access a single child, or `treespec.children()` to get all children.
  for child_spec in spec.children_specs:

Traceback (most recent call last):
  File "/workspace/TensorRT/tools/llm/run_llm.py", line 323, in <module>
    trt_model = compile_torchtrt(model, input_ids, args)
  File "/workspace/TensorRT/tools/llm/run_llm.py", line 134, in compile_torchtrt
    trt_model = torch_tensorrt.dynamo.compile(
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch_tensorrt/dynamo/_compiler.py", line 764, in compile
    gm = post_lowering(gm, settings)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py", line 139, in post_lowering
    fake_tensor_updater.incremental_update(fake_mode)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch_tensorrt/dynamo/lowering/passes/_FakeTensorUpdater.py", line 193, in incremental_update
    new_fake_tensor = node.target(*args, **kwargs)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_ops.py", line 819, in __call__
    return self._op(*args, **kwargs)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/utils/_stats.py", line 29, in wrapper
    return fn(*args, **kwargs)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1397, in __torch_dispatch__
    return self.dispatch(func, types, args, kwargs)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2155, in dispatch
    return self._cached_dispatch_impl(func, types, args, kwargs)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1548, in _cached_dispatch_impl
    entry = self._make_cache_entry(state, key, func, args, kwargs, output)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1969, in _make_cache_entry
    output_info = self._get_output_info_for_cache_entry(
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1863, in _get_output_info_for_cache_entry
    synth_output = self._output_from_cache_entry(
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2076, in _output_from_cache_entry
    return self._get_output_tensor_from_cache_entry(
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2031, in _get_output_tensor_from_cache_entry
    empty = torch.empty_strided(
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/fx/experimental/sym_node.py", line 562, in expect_true
    return self.shape_env.guard_or_defer_runtime_assert(
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/fx/experimental/recording.py", line 273, in wrapper
    return retlog(fn(*args, **kwargs))
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 7779, in guard_or_defer_runtime_assert
    static_expr = self._maybe_evaluate_static(expr)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 2636, in wrapper
    return fn_cache(self, *args, **kwargs)
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 6437, in _maybe_evaluate_static
    r = _maybe_evaluate_static_worker(
  File "/opt/conda/envs/py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 2421, in _maybe_evaluate_static_worker
    assert vr is not None
AssertionError

To Reproduce

Steps to reproduce the behavior:

Expected behavior

Environment

Build information about Torch-TensorRT can be found by turning on debug messages

• Torch-TensorRT Version (e.g. 1.0.0):
• PyTorch Version (e.g. 1.0):
• CPU Architecture:
• OS (e.g., Linux):
• How you installed PyTorch (conda, pip, libtorch, source):
• Build command you used (if compiling from source):
• Are you using local sources or building from archives:
• Python version:
• CUDA version:
• GPU models and configuration:
• Any other relevant information:

Additional context

[zeel2104]

Is it open for contribution?