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

Start by reproducing the two examples with the reported versions, then inspect the tgate/SDXL.py and tgate/SD.py entry points shown in the traces, especially tgate and check_inputs. Compare those calls with the corresponding Diffusers img2img pipeline interfaces; done means both Stable Diffusion and SDXL img2img pipelines run successfully with tgate without breaking the existing text2img behavior.

Written by the indexing model from the issue text.