FluxTransformer2DModel does not have config and cannot set_default_attn_processor

### Describe the bug

```
scheduler = FlowMatchEulerDiscreteScheduler.from_pretrained(
BFL_REPO, subfolder="scheduler", revision=REVISION
)
text_encoder = CLIPTextModel.from_pretrained(
"openai/clip-vit-large-patch14", torch_dtype=DTYPE
)
tokenizer = CLIPTokenizer.from_pretrained(
"openai/clip-vit-large-patch14", torch_dtype=DTYPE
)
text_encoder_2 = T5EncoderModel.from_pretrained(
BFL_REPO, subfolder="text_encoder_2", torch_dtype=DTYPE, revision=REVISION
)
tokenizer_2 = T5TokenizerFast.from_pretrained(
BFL_REPO, subfolder="tokenizer_2", torch_dtype=DTYPE, revision=REVISION
)
vae = AutoencoderKL.from_pretrained(
BFL_REPO, subfolder="vae", torch_dtype=DTYPE, revision=REVISION
)
transformer = FluxTransformer2DModel.from_pretrained(
BFL_REPO, subfolder="transformer", torch_dtype=DTYPE, revision=REVISION
)

quantize(transformer, weights=qfloat8)
freeze(transformer)

quantize(text_encoder_2, weights=qfloat8)
freeze(text_encoder_2)

pipe = FluxPipeline(
scheduler=scheduler,
text_encoder=text_encoder,
tokenizer=tokenizer,
text_encoder_2=None,
tokenizer_2=tokenizer_2,
vae=vae,
transformer=None,
)
pipe.text_encoder_2 = text_encoder_2
pipe.transformer = transformer
pipe.enable_model_cpu_offload()
```

Running the attention ops without SDPA
```
pipe.transformer.set_default_attn_processor()
```

Returns an error
```
1727 if name in modules:
1728 return modules[name]
-> 1729 raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")

AttributeError: 'FluxTransformer2DModel' object has no attribute 'set_default_attn_processor'
```

And also, you cannot do `pipe.transformer.config`

### Reproduction

Latest diffusers

### Logs

```shell

```

### System Info

Latest diffusion version (0.33.0)
A100
pytorch/pytorch:2.4.1-cuda12.4-cudnn9-devel
accelerate, peft, transformers are also all up to date

Moreover, torch.compile do not work

Start with FluxTransformer2DModel and its use from FluxPipeline, reproducing the reported calls on diffusers 0.33.0. Compare the model's configuration and attention-processor behavior with related transformer models. Done means the reported config access and set_default_attn_processor call work, with the torch.compile concern checked.

Scritto dal modello di indicizzazione a partire dal testo della issue.