Repository: huggingface/diffusers

Issue:
[StableDiffusionXLInstructPix2PixPipeline] RuntimeError: Sizes of tensors must match except in dimension 1
### Describe the bug

While working on #6569 related to #6545, I run the InstructPix2Pix SDXL training example [code](https://github.com/huggingface/diffusers/blob/main/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py) and noticed this issue.

I think before merging #6569, we should fix this issue first.

### Reproduction

I just followed the **Toy example** [guide].(https://github.com/huggingface/diffusers/blob/main/examples/instruct_pix2pix/README_sdxl.md#toy-example)

```shell
export MODEL_NAME="stabilityai/stable-diffusion-xl-base-1.0"
export DATASET_ID="fusing/instructpix2pix-1000-samples"

accelerate launch train_instruct_pix2pix_sdxl.py \
    --pretrained_model_name_or_path=stabilityai/stable-diffusion-xl-base-1.0 \
    --dataset_name=$DATASET_ID \
    --use_ema \
    --enable_xformers_memory_efficient_attention \
    --resolution=512 --random_flip \
    --train_batch_size=4 --gradient_accumulation_steps=4 --gradient_checkpointing \
    --max_train_steps=15000 \
    --checkpointing_steps=5000 --checkpoints_total_limit=1 \
    --learning_rate=5e-05 --lr_warmup_steps=0 \
    --conditioning_dropout_prob=0.05 \
    --seed=42 \
    --val_image_url_or_path="https://datasets-server.huggingface.co/assets/fusing/instructpix2pix-1000-samples/--/fusing--instructpix2pix-1000-samples/train/23/input_image/image.jpg" \
    --validation_prompt="make it in japan" \
    --report_to=wandb \
    --push_to_hub
```

### Logs

```shell
Traceback (most recent call last):
  File "/root/dev/diffusers/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py", line 1234, in <module>
    main()
  File "/root/dev/diffusers/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py", line 1147, in main
    a_val_img = pipeline(
  File "/opt/env/conda/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/root/dev/diffusers/src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_instruct_pix2pix.py", line 952, in __call__
    scaled_latent_model_input = torch.cat([scaled_latent_model_input, image_latents], dim=1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 128 but got size 64 for tensor number 1 in the list.
```


### System Info

- `diffusers` version: 0.26.0.dev0
- Platform: Linux-4.19.93-1
- Python version: 3.10.8
- PyTorch version (GPU?): 2.0.1+cu117 (True)
- Huggingface_hub version: 0.20.2
- Transformers version: 4.36.2
- Accelerate version: 0.26.1
- xFormers version: 0.0.22
- Using GPU in script?: Yes, a single GPU
- Using distributed or parallel set-up in script?: No

### Who can help?

@yiyixuxu @DN6 


Discussion:
@sayakpaul Could you take a look please? 
Thanks for reporting. Do you want to create a PR fixing the issue? 
Thanks for the reply, @DN6 @sayakpaul! 
Sure, I will look into this.
Please let me know if there are any specific parts I should check out first by any chance.
The inputs should be checked first because that is causing the concatenation problem. 
Ok, thanks for letting me know 👍 
You can also refer to https://github.com/huggingface/diffusers/blob/instruct-pix2pix/emu/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py that works. 

Training command: https://github.com/huggingface/diffusers/blob/3a95742edc3ead6e0598121fc80764d65ce9de67/examples/instruct_pix2pix/run.slurm#L57

Resolving patch:
diff --git a/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py b/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py
--- a/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py
+++ b/examples/instruct_pix2pix/train_instruct_pix2pix_sdxl.py
@@ -1109,7 +1109,7 @@ def collate_fn(examples):
             progress_bar.set_postfix(**logs)
 
             ### BEGIN: Perform validation every `validation_epochs` steps
-            if global_step % args.validation_steps == 0 or global_step == 1:
+            if global_step % args.validation_steps == 0:
                 if (args.val_image_url_or_path is not None) and (args.validation_prompt is not None):
                     logger.info(
                         f"Running validation... \n Generating {args.num_validation_images} images with prompt:"
diff --git a/src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_instruct_pix2pix.py b/src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_instruct_pix2pix.py
--- a/src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_instruct_pix2pix.py
+++ b/src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_instruct_pix2pix.py
@@ -858,7 +858,7 @@ def __call__(
         )
 
         # 4. Preprocess image
-        image = self.image_processor.preprocess(image).to(device)
+        image = self.image_processor.preprocess(image, height=height, width=width).to(device)
 
         # 5. Prepare timesteps
         self.scheduler.set_timesteps(num_inference_steps, device=device)


Test patch: