Constant folding doesn't work for ThunderFX and NeMo

@kshitij12345 is already working on this.

Since Nov 26, 2024.

## 🐛 Bug

When running Phi-3.5-mini-instruct,Mistral-Nemo-Base-2407 and Qwen2.5-7B-Instruct with NeMo + ThunderFX and constant folding enabled we get error:

> File ".1546", line 7, in forward
0: thunder_2 = self.thunder_2(inductor_1, l__self___model_layers_0_input_layernorm_weight); l__self___model_layers_0_input_layernorm_weight = None
0: File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1552, in _wrapped_call_impl
0: return self._call_impl(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1561, in _call_impl
0: return forward_call(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/core/module.py", line 80, in forward
0: res = self._forward_fn(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/__init__.py", line 774, in wrapped
0: return fn(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/__init__.py", line 824, in fn_
0: cache_entry, inps, pro_to_epi = get_computation_and_inputs(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/__init__.py", line 756, in wrapped
0: cache_entry, inps, pro_to_epi = get_computation_and_inputs_fn(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/core/langctxs.py", line 136, in _fn
0: result = fn(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/__init__.py", line 236, in cache_info_wrapper
0: res = fn(*args, **kwargs)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/__init__.py", line 602, in get_computation_and_inputs
0: new_prologue_trc, new_computation_trc, new_epilogue_trc = transform.transform_traces_pre_prologue(
0: File "/usr/local/lib/python3.10/dist-packages/thunder/transforms/constant_folding.py", line 105, in transform_traces_pre_prologue
0: new_concrete_output = compute_with_constant_tensors(bsym, const_values)
0: File "/usr/local/lib/python3.10/dist-packages/thunder/transforms/constant_folding.py", line 63, in compute_with_constant_tensors
0: return torch_fn(*new_args, **new_kwargs)
0: TypeError: arange() received an invalid combination of arguments - got (int, int, int, dtype=NoneType, device=Device), but expected one of:
0: * (Number end, *, Tensor out = None, torch.dtype dtype = None, torch.layout layout = None, torch.device device = None, bool pin_memory = False, bool requires_grad = False)
0: * (Number start, Number end, *, torch.dtype dtype = None, torch.layout layout = None, torch.device device = None, bool pin_memory = False, bool requires_grad = False)
0: * (Number start, Number end, Number step = 1, *, Tensor out = None, torch.dtype dtype = None, torch.layout layout = None, torch.device device = None, bool pin_memory = False, bool requires_grad = False)

### To Reproduce

The error is present on 1xH100.

Dockerfile used (I build it yesterday and I'm not sure yet how nemo:dev images are versioned, so I can't provide its detailed version):

```
FROM nvcr.io/nvidia/nemo:dev
ARG NVFUSER_REPO=git+https://github.com/NVIDIA/Fuser.git
ARG THUNDER_REPO=git+https://github.com/Lightning-AI/lightning-thunder.git

# Add cloned NeMo latest code
RUN git clone --recursive https://github.com/NVIDIA/NeMo.git /NeMo_cloned
RUN (cd /NeMo_cloned && python -m pip install .)

# Install requirements needed for NeMo, Thunder and NVFUser.
# We must install them in such compilated way because otherwise Thunder is not
# updated and we are not able to use the latest version.
RUN python -m pip install -r /NeMo_cloned/requirements/requirements_lightning.txt && \
python -m pip install --upgrade ${NVFUSER_REPO} && \
python -m pip install --upgrade ${THUNDER_REPO} && \
python -m pip install --upgrade --no-deps --force-reinstall ${NVFUSER_REPO} && \
python -m pip install --upgrade --no-deps --force-reinstall ${THUNDER_REPO}

# Install Mixology requirements (this can be skipped, so I'm commenting it out)
# COPY requirements/mixology.txt mixology_requirements.txt
# RUN pip install --upgrade -r mixology_requirements.txt

```
Inside docker container please run:

```
model=microsoft/Phi-3.5-mini-instruct
# Download the model (you might need to set HF_TOKEN and agree on the website to terms of use of this model)
huggingface-cli download $model --local-dir checkpoints/$model --cache-dir checkpoints/$model
# Run benchmark
python bench_targets/llm_peft/_nemo.py --model checkpoints/$model --mbs 1 --seq-length 2048 --jit-backend thunder
```
Script `bench_targets/llm_peft/_nemo.py` can be obtained from internal Gitlab from `akoumparouli/nemo_bench`. You can contact me or @tfogal if you have any questions. In order to use constant folding it's code around line 90 must be modified:
```
from thunder.transforms.constant_folding import ConstantFolding
xforms: list = [NvtxProfileTransform(), ConstantFolding()]
nvtx.mark("thunder compilation", domain="model")
be = thunder.dynamo.ThunderCompiler(transforms=xforms)
pl_module.model.compile(backend=be)
```

### Expected behavior

No error.

### Environment

* nvfuser @ git+https://github.com/NVIDIA/Fuser.git@bb058595c49dc32416d563f5a4c1c5f22a01ca54
* lightning-thunder @ git+https://github.com/Lightning-AI/lightning-thunder.git@81f83f3549d0cde9fc012fb9ebfb9eb4a3254e61

cc @tfogal