Fix generation using flash-attention and static cache
Author: qgallouedec
Pull request: yes

# What does this PR do?

Previously, this would fail:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
import torch

device = "cuda"
model_id = "Qwen/Qwen2.5-0.5B"

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    attn_implementation="flash_attention_2",
    torch_dtype=torch.bfloat16,
    device_map=device,
)

tokenizer = AutoTokenizer.from_pretrained(model_id)

generation_config = GenerationConfig(
    cache_implementation="static",
    disable_compile=True,  # flash_attention_2 does not support compilation
)

processed = tokenizer(["My cat is cute", "My dog too"], return_tensors="pt", padding=True, padding_side="left")
processed = {k: v.to(device) for k, v in processed.items()}
output = model.generate(**processed, generation_config=generation_config)
```

```
$ /fsx/qgallouedec/miniconda3/envs/trl/bin/python /fsx/qgallouedec/trl/sandbox/flash_attention_static_cache.py
Setting `pad_token_id` to `eos_token_id`:151643 for open-end generation.
Traceback (most recent call last):
  File "/fsx/qgallouedec/trl/sandbox/flash_attention_static_cache.py", line 20, in <module>
    output = model.generate(**processed, generation_config=generation_config)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/miniconda3/envs/trl/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/transformers/src/transformers/generation/utils.py", line 2286, in generate
    result = self._sample(
             ^^^^^^^^^^^^^
  File "/fsx/qgallouedec/transformers/src/transformers/generation/utils.py", line 3274, in _sample
    outputs = self(**model_inputs, return_dict=True)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/miniconda3/envs/trl/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/miniconda3/envs/trl/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/transformers/src/transformers/utils/deprecation.py", line 172, in wrapped_func
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/transformers/src/transformers/models/qwen2/modeling_qwen2.py", line 855, in forward
    outputs = self.model(
              ^^^^^^^^^^^
  File "/fsx/qgallouedec/miniconda3/envs/trl/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/miniconda3/envs/trl/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/transformers/src/transformers/models/qwen2/modeling_qwen2.py", line 549, in forward
    causal_mask = self._update_causal_mask(
                  ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/fsx/qgallouedec/transformers/src/transformers/models/qwen2/modeling_qwen2.py", line 622, in _update_causal_mask
    raise ValueError(
ValueError: You are attempting to perform batched generation with padding_side='right' this may lead to unexpected behaviour for Flash Attention version of Qwen2. Make sure to  call `tokenizer.padding_side  = 'left'` before tokenizing the input. 
```

It's because 

https://github.com/huggingface/transformers/blob/2c2495cc7b0e3e2942a9310f61548f40a2bc8425/src/transformers/models/mistral/modular_mistral.py#L125

assumes a 2D attention mask. However, with static cache, the attention mask is 4D. To make it work, we recover the 2D attention mask.

## Before submitting
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- [ ] Did you write any new necessary tests?


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