Can't load multiple loras when using Flux Control LoRA 
### Describe the bug

I was trying out the FluxControlPipeline with the Control LoRA introduced in #9999 , but had issues loading in multiple loras. 

For example, if I load the depth lora first and then the 8-step lora, it errors on the 8-step lora, and if I load the 8-step lora first and then the depth lora, it errors when loading the depth lora. 



### Reproduction

```
from diffusers import FluxControlPipeline
from huggingface_hub import hf_hub_download
import torch

control_pipe = FluxControlPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to("cuda")
control_pipe.load_lora_weights("black-forest-labs/FLUX.1-Depth-dev-lora")
control_pipe.load_lora_weights(hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"))

```

### Logs

```shell
AttributeError                            Traceback (most recent call last)
Cell In[6], line 8
      5 control_pipe = FluxControlPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to("cuda")
      7 control_pipe.load_lora_weights("black-forest-labs/FLUX.1-Depth-dev-lora")
----> 8 control_pipe.load_lora_weights(
      9         hf_hub_download(
     10             "ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"
     11         ),
     12         adapter_name="HyperFlux",
     13     )

File ~/.venv/lib/python3.10/site-packages/diffusers/loaders/lora_pipeline.py:1856, in FluxLoraLoaderMixin.load_lora_weights(self, pretrained_model_name_or_path_or_dict, adapter_name, **kwargs)
   1849 transformer_norm_state_dict = {
   1850     k: state_dict.pop(k)
   1851     for k in list(state_dict.keys())
   1852     if "transformer." in k and any(norm_key in k for norm_key in self._control_lora_supported_norm_keys)
   1853 }
   1855 transformer = getattr(self, self.transformer_name) if not hasattr(self, "transformer") else self.transformer
-> 1856 has_param_with_expanded_shape = self._maybe_expand_transformer_param_shape_or_error_(
   1857     transformer, transformer_lora_state_dict, transformer_norm_state_dict
   1858 )
   1860 if has_param_with_expanded_shape:
   1861     logger.info(
   1862         "The LoRA weights contain parameters that have different shapes that expected by the transformer. "
   1863         "As a result, the state_dict of the transformer has been expanded to match the LoRA parameter shapes. "
   1864         "To get a comprehensive list of parameter names that were modified, enable debug logging."
   1865     )

File ~/.venv/lib/python3.10/site-packages/diffusers/loaders/lora_pipeline.py:2316, in FluxLoraLoaderMixin._maybe_expand_transformer_param_shape_or_error_(cls, transformer, lora_state_dict, norm_state_dict, prefix)
   2314 if isinstance(module, torch.nn.Linear):
   2315     module_weight = module.weight.data
-> 2316     module_bias = module.bias.data if hasattr(module, "bias") else None
   2317     bias = module_bias is not None
   2319     lora_A_weight_name = f"{name}.lora_A.weight"

AttributeError: 'NoneType' object has no attribute 'data'
```


### System Info

- 🤗 Diffusers version: 0.32.0.dev0
- Platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
- Running on Google Colab?: No
- Python version: 3.10.12
- PyTorch version (GPU?): 2.5.1+cu124 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Huggingface_hub version: 0.26.5
- Transformers version: 4.47.0
- Accelerate version: 1.2.0
- PEFT version: 0.14.0
- Bitsandbytes version: not installed
- Safetensors version: 0.4.5
- xFormers version: not installed
- Accelerator: NVIDIA H100 80GB HBM3, 81559 MiB
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help?

@a-r-r-o-w @sayakpaul