Accelerate + Dynamo broken in 4.46.0 due to model loss functions refactor
Author: AbrahamSanders
Pull request: no
Labels: name: bug

### System Info

- `transformers` version: 4.46.0
- Platform: Linux-5.15.0-91-generic-x86_64-with-glibc2.35
- Python version: 3.9.16
- Huggingface_hub version: 0.24.0
- Safetensors version: 0.4.5
- Accelerate version: 1.0.1
- Accelerate config:    - compute_environment: LOCAL_MACHINE
        - distributed_type: NO
        - mixed_precision: bf16
        - use_cpu: False
        - debug: False
        - num_processes: 1
        - machine_rank: 0
        - num_machines: 1
        - gpu_ids: 0
        - rdzv_backend: static
        - same_network: True
        - main_training_function: main
        - enable_cpu_affinity: True
        - downcast_bf16: no
        - tpu_use_cluster: False
        - tpu_use_sudo: False
        - tpu_env: []
        - dynamo_config: {'dynamo_backend': 'INDUCTOR'}
- PyTorch version (GPU?): 2.5.0+cu121 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: No
- Using GPU in script?: Yes
- GPU type: NVIDIA RTX A6000

### Who can help?

@muellerzr @ArthurZucker

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

#34191 introduced custom loss functions to the model classes. This appears to have broken training with accelerate + torch dynamo.

To reproduce, use `run_clm.py` with the following accelerate config:
```yaml
compute_environment: LOCAL_MACHINE
debug: false
distributed_type: 'NO'
downcast_bf16: 'no'
dynamo_config:
  dynamo_backend: INDUCTOR
enable_cpu_affinity: true
gpu_ids: '0'
machine_rank: 0
main_training_function: main
mixed_precision: bf16
num_machines: 1
num_processes: 1
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false
```
```bash
accelerate launch run_clm.py \
    --log_level info \
    --model_name_or_path=meta-llama/Llama-3.2-1B \
    --dataset_name=Salesforce/wikitext \
    --dataset_config_name=wikitext-2-raw-v1 \
    --block_size=1024 \
    --per_device_train_batch_size=4 \
    --do_train \
    --bf16 \
    --output_dir=Llama-3.2-1B-wikitext-2-raw-v1 \
    --overwrite_output_dir \
    --seed=42 \
    --logging_steps=10 \
    --lr_scheduler_type=cosine \
    --num_train_epochs=3 \
    --learning_rate=5e-05 \
    --warmup_ratio=0.03 \
    --dataloader_drop_last
```

This produces an error from dynamo relating to the new `model_cls.loss_function` attribute added in #34191:
https://github.com/huggingface/transformers/blob/239a256a0c3bf2edab2bbd614923c4eaf88b867d/src/transformers/models/llama/modeling_llama.py#L1209-L1211

Important part of the traceback:
```text
  File "/anaconda3/envs/dev/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 152, in __init__
    assert isinstance(
AssertionError: expected FunctionType found _lru_cache_wrapper <functools._lru_cache_wrapper object at 0x7f1091109a40>

from user code:
   File "/anaconda3/envs/dev/lib/python3.9/site-packages/accelerate/utils/operations.py", line 820, in forward
    return model_forward(*args, **kwargs)
  File "/anaconda3/envs/dev/lib/python3.9/site-packages/accelerate/utils/operations.py", line 808, in __call__
    return convert_to_fp32(self.model_forward(*args, **kwargs))
  File "/anaconda3/envs/dev/lib/python3.9/site-packages/torch/amp/autocast_mode.py", line 44, in decorate_autocast
    return func(*args, **kwargs)
  File "/anaconda3/envs/dev/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1214, in forward
    loss = self.loss_function(logits=logits, labels=labels, vocab_size=self.config.vocab_size, **loss_kwargs)

Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information
```

Now, if you update the accelerate config to not use dynamo, it runs just fine:
```yaml
compute_environment: LOCAL_MACHINE
debug: false
distributed_type: 'NO'
downcast_bf16: 'no'
enable_cpu_affinity: true
gpu_ids: '0'
machine_rank: 0
main_training_function: main
mixed_precision: bf16
num_machines: 1
num_processes: 1
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false
```


### Expected behavior

Accelerate should not throw the error when using torch dynamo.

Comments:
I think removing the @lru_cache is the fix no? Can you confirm that this resolves your issue? 🤗 

Hi, I am seeing the same issue. Looking forward to the fix!