tgate error on img2img sd/sdxl pipelines

### Describe the bug

I minimally modified the working example in https://huggingface.co/docs/diffusers/main/en/optimization/tgate?pipelines=Stable+Diffusion+XL to use img2img pipeline which results in the first error, and also tried with SD which gave the second error. both pipelines work when calling without the tgate. text2img does work for me with tgate.

### Reproduction

sdxl:
```py
!pip install tgate

import torch
from diffusers import StableDiffusionXLImg2ImgPipeline
from diffusers import DPMSolverMultistepScheduler
from tgate import TgateSDXLLoader
from PIL import Image

pipe = StableDiffusionXLImg2ImgPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16,
variant="fp16",
use_safetensors=True,
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

gate_step = 10
inference_step = 25
pipe = TgateSDXLLoader(
pipe,
gate_step=gate_step,
num_inference_steps=inference_step,
).to("cuda")

image = pipe.tgate(
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.",
image = Image.new('RGB', (1024, 1024)),
gate_step=gate_step,
num_inference_steps=inference_step
).images[0]
```

sd:
```py
!pip install tgate

import torch
from diffusers import StableDiffusionImg2ImgPipeline
from diffusers import DPMSolverMultistepScheduler
from tgate import TgateSDLoader
from PIL import Image

pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
"stable-diffusion-v1-5/stable-diffusion-v1-5",
torch_dtype=torch.float16,
variant="fp16",
use_safetensors=True,
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

gate_step = 10
inference_step = 25
pipe = TgateSDLoader(
pipe,
gate_step=gate_step,
num_inference_steps=inference_step,
).to("cuda")

image = pipe.tgate(
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.",
image = Image.new('RGB', (512, 512)),
gate_step=gate_step,
num_inference_steps=inference_step
).images[0]
```

### Logs

```shell
SDXL
---------------------------------------------------------------------------

AttributeError Traceback (most recent call last)

/tmp/ipython-input-800193126.py in ()
23 ).to("cuda")
24
---> 25 image = pipe.tgate(
26 "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.",
27 image = Image.new('RGB', (1024, 1024)),

2 frames

/usr/local/lib/python3.12/dist-packages/torch/utils/_contextlib.py in decorate_context(*args, **kwargs)
118 def decorate_context(*args, **kwargs):
119 with ctx_factory():
--> 120 return func(*args, **kwargs)
121
122 return decorate_context

/usr/local/lib/python3.12/dist-packages/tgate/SDXL.py in tgate(self, prompt, prompt_2, height, width, num_inference_steps, timesteps, sigmas, denoising_end, guidance_scale, negative_prompt, negative_prompt_2, num_images_per_prompt, eta, generator, latents, prompt_embeds, negative_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds, ip_adapter_image, ip_adapter_image_embeds, output_type, return_dict, cross_attention_kwargs, guidance_rescale, original_size, crops_coords_top_left, target_size, negative_original_size, negative_crops_coords_top_left, negative_target_size, clip_skip, callback_on_step_end, callback_on_step_end_tensor_inputs, gate_step, sp_interval, fi_interval, warm_up, lcm, **kwargs)
251
252 # 0. Default height and width to unet
--> 253 height = height or self.default_sample_size * self.vae_scale_factor
254 width = width or self.default_sample_size * self.vae_scale_factor
255

/usr/local/lib/python3.12/dist-packages/diffusers/configuration_utils.py in __getattr__(self, name)
142 return self._internal_dict[name]
143
--> 144 raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
145
146 def save_config(self, save_directory: Union[str, os.PathLike], push_to_hub: bool = False, **kwargs):

AttributeError: 'StableDiffusionXLImg2ImgPipeline' object has no attribute 'default_sample_size'

--------

SD:
---------------------------------------------------------------------------

TypeError Traceback (most recent call last)

/tmp/ipython-input-3990070211.py in ()
23 ).to("cuda")
24
---> 25 image = pipe.tgate(
26 "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.",
27 image = Image.new('RGB', (512, 512)),

1 frames

/usr/local/lib/python3.12/dist-packages/torch/utils/_contextlib.py in decorate_context(*args, **kwargs)
118 def decorate_context(*args, **kwargs):
119 with ctx_factory():
--> 120 return func(*args, **kwargs)
121
122 return decorate_context

/usr/local/lib/python3.12/dist-packages/tgate/SD.py in tgate(self, prompt, height, width, num_inference_steps, timesteps, sigmas, guidance_scale, negative_prompt, num_images_per_prompt, eta, generator, latents, prompt_embeds, negative_prompt_embeds, ip_adapter_image, ip_adapter_image_embeds, output_type, return_dict, cross_attention_kwargs, guidance_rescale, clip_skip, callback_on_step_end, callback_on_step_end_tensor_inputs, gate_step, sp_interval, fi_interval, warm_up, **kwargs)
174
175 # 1. Check inputs. Raise error if not correct
--> 176 self.check_inputs(
177 prompt,
178 height,

TypeError: StableDiffusionImg2ImgPipeline.check_inputs() takes from 4 to 10 positional arguments but 11 were given
```

### System Info

- 🤗 Diffusers version: 0.35.2
- Platform: Linux-6.6.105+-x86_64-with-glibc2.35
- Running on Google Colab?: Yes
- Python version: 3.12.12
- PyTorch version (GPU?): 2.8.0+cu126 (True)
- Flax version (CPU?/GPU?/TPU?): 0.10.6 (gpu)
- Jax version: 0.5.3
- JaxLib version: 0.5.3
- Huggingface_hub version: 0.35.3
- Transformers version: 4.57.1
- Accelerate version: 1.10.1
- PEFT version: 0.17.1
- Bitsandbytes version: not installed
- Safetensors version: 0.6.2
- xFormers version: not installed
- Accelerator: Tesla T4, 15360 MiB
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no

### Who can help?

@yiyixuxu

Inizia riproducendo i due esempi con le versioni indicate, quindi esamina i punti di ingresso tgate/SDXL.py e tgate/SD.py mostrati nelle tracce, in particolare tgate e check_inputs. Confronta queste chiamate con le interfacce corrispondenti delle pipeline img2img di Diffusers; il lavoro è completato quando entrambe le pipeline img2img Stable Diffusion e SDXL vengono eseguite correttamente con tgate senza interrompere il comportamento text2img esistente.

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