Llama model cannot be fx traced 
Author: xuzifei-dmatrix
Pull request: no

### System Info

- `transformers` version: 4.39.1
- Platform: Linux-5.15.0-1057-azure-x86_64-with-glibc2.35
- Python version: 3.10.13
- Huggingface_hub version: 0.22.1
- Safetensors version: 0.4.2
- Accelerate version: 0.28.0
- Accelerate config:    - compute_environment: LOCAL_MACHINE
        - distributed_type: MULTI_GPU
        - mixed_precision: no
        - use_cpu: False
        - debug: False
        - num_processes: 4
        - machine_rank: 0
        - num_machines: 1
        - gpu_ids: all
        - rdzv_backend: static
        - same_network: True
        - main_training_function: main
        - downcast_bf16: no
        - tpu_use_cluster: False
        - tpu_use_sudo: False
        - tpu_env: []
        - dynamo_config: {'dynamo_backend': 'INDUCTOR'}
- PyTorch version (GPU?): 2.2.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>

### Who can help?

_No response_

### Information

- [ ] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

```python
from transformers.utils.fx import symbolic_trace
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf")
gm = symbolic_trace(model)
```
```python
File ~/miniconda3/envs/mltools/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:665, in LlamaSdpaAttention.forward(self, hidden_states, attention_mask, position_ids, past_key_value, output_attentions, use_cache, cache_position)
    661     causal_mask = causal_mask[:, :, :, : key_states.shape[-2]]
    663 # SDPA with memory-efficient backend is currently (torch==2.1.2) bugged with non-contiguous inputs with custom attn_mask,
    664 # Reference: https://github.com/pytorch/pytorch/issues/112577.
--> 665 if query_states.device.type == "cuda" and causal_mask is not None:
    666     query_states = query_states.contiguous()
    667     key_states = key_states.contiguous()

File ~/miniconda3/envs/mltools/lib/python3.10/site-packages/transformers/utils/fx.py:653, in HFProxy.__bool__(self)
    651 if hasattr(self, "_metadata") and self._metadata is not None:
    652     return self._metadata
--> 653 return super().__bool__()

File ~/miniconda3/envs/mltools/lib/python3.10/site-packages/torch/fx/proxy.py:441, in Proxy.__bool__(self)
    438             self.tracer.create_proxy('call_function', assert_fn, (self,), {})
    439             return True
--> 441 return self.tracer.to_bool(self)

File ~/miniconda3/envs/mltools/lib/python3.10/site-packages/torch/fx/proxy.py:301, in TracerBase.to_bool(self, obj)
    294 @compatibility(is_backward_compatible=True)
    295 def to_bool(self, obj: 'Proxy') -> bool:
    296     """Called when a proxy object is being converted to a boolean, such as
    297     when used in control flow.  Normally we don't know what to do because
    298     we don't know the value of the proxy, but a custom tracer can attach more
    299     information to the graph node using create_node and can choose to return a value.
    300     """
--> 301     raise TraceError('symbolically traced variables cannot be used as inputs to control flow')

TraceError: symbolically traced variables cannot be used as inputs to control flow
```

### Expected behavior
It should trace with no error, which is the case for v4.38.2



Comments:
Hey! Thanks for reporting. As mentioned in the release notes, this is expected and waiting for a fix from @fxmarty or @michaelbenayoun to patch it! 🤗 

Yes, I will work on it asap. 

Gentle ping @michaelbenayoun 

(He has a PR going on, just needs to be linked! #30259 )

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