non power of 2 sized images with stable cascade fail

### Describe the bug

I am not sure if this is a bug, but the documentation does not mention a limitation to power of 2 that I can find.

Generating a non power of 2 sized image fails.

### Reproduction

```python
import torch
from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline

device = "cuda"
num_images_per_prompt = 1

prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", variant='bf16',
torch_dtype=torch.bfloat16)
decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", variant='bf16',
torch_dtype=torch.float16)

prompt = "Anthropomorphic cat dressed as a pilot"
negative_prompt = ""

prior.enable_model_cpu_offload()
decoder.enable_model_cpu_offload()

prior_output = prior(
prompt=prompt,
height=1024,
width=680,
negative_prompt=negative_prompt,
guidance_scale=4.0,
num_images_per_prompt=num_images_per_prompt,
num_inference_steps=20
)

decoder_output = decoder(
image_embeddings=prior_output.image_embeddings.half(),
prompt=prompt,
negative_prompt=negative_prompt,
guidance_scale=0.0,
output_type="pil",
num_inference_steps=10
).images
```

### Logs

```shell
Traceback (most recent call last):
File "REDACT\test.py", line 28, in
decoder_output = decoder(
^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\diffusers\pipelines\stable_cascade\pipeline_stable_cascade.py", line 443, in __call__
predicted_latents = self.decoder(
^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\accelerate\hooks.py", line 166, in new_forward
output = module._old_forward(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\diffusers\models\unets\unet_stable_cascade.py", line 605, in forward
x = self._up_decode(level_outputs, timestep_ratio_embed, clip)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\diffusers\models\unets\unet_stable_cascade.py", line 553, in _up_decode
x = block(x, skip)
^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\diffusers\models\unets\unet_stable_cascade.py", line 74, in forward
x = self.norm(self.depthwise(x))
^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\conv.py", line 460, in forward
return self._conv_forward(input, self.weight, self.bias)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "REDACT\venv\Lib\site-packages\torch\nn\modules\conv.py", line 456, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Input type (float) and bias type (struct c10::Half) should be the same

Process finished with exit code 1
```

### System Info

diffusers 0.27.2
torch 2.2.2+cu121

### Who can help?

_No response_

Reproduce the Stable Cascade example with height=1024 and width=680 using the reported versions. Start with src/diffusers/pipelines/stable_cascade/pipeline_stable_cascade.py and src/diffusers/models/unets/unet_stable_cascade.py, especially the decoder call and _up_decode path. Determine whether the failure is caused by non-power-of-two dimensions or the reported dtype mismatch, then add a regression test or clarify the supported dimensions in the documentation.

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