FluxFillPipeline quality deteriorates over multiple iterations of inpainting

### Describe the bug

When the FluxFillPipeline is run multiple times on the same image, the image quality deteriorates in each iteration.

### Reproduction

```python
import torch
from diffusers import FluxFillPipeline
from diffusers.utils import load_image

pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")

img = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")

def fill(prompt, image, mask):
return pipe(
prompt=prompt,
image=image,
mask_image=mask,
guidance_scale=30,
num_inference_steps=50,
max_sequence_length=512,
height=1632,
width=1232,
generator=torch.Generator("cpu").manual_seed(0),
).images[0]

prompt = "a white paper cup"
for i in range(12):
print(i)
img = fill(prompt, img, mask)
img.save(f"output_{i}.png")
```

### Logs


### System Info

Diffusers Version 0.31.0
Python Version 3.10
CUDA Version 12.1.0
DGX H100

### Who can help?

@yiyixuxu @DN6 @aso

Start by running the provided Python reproduction for FluxFillPipeline with the listed Diffusers, Python, CUDA, and hardware versions, then inspect the pipeline entry point to trace repeated inpainting calls. Done means repeated iterations no longer show the reported quality deterioration, with the behavior checked against the supplied outputs.

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