SD3ControlNetModel.from_transformer load weights error

### Describe the bug

When specifying `num_layers` in `SD3ControlNetModel.from_transformer`, the function results in an error of unexpected key(s). I think this is because that in `SD3ControlNetModel`, there is only `num_layers` of transformer blocks, while in `SD3Transformer2DModel`, there are 24 transformer blocks. I think it can be fixed by looping over the transformer blocks in the controlnet for `num_layers` times when loading the weights from SD3 transformer.

### Reproduction

```python
from diffusers import SD3Transformer2DModel
from diffusers.models.controlnet_sd3 import SD3ControlNetModel

n_layers = 12 # Value that is less than 24

transformer = SD3Transformer2DModel.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", subfolder="transformer")
controlnet = SD3ControlNetModel.from_transformer(transformer, n_layers)
```

### Logs

```shell
Traceback (most recent call last):
File "", line 1, in
File "/root/anaconda3/envs/geolight/lib/python3.9/site-packages/diffusers/models/controlnet_sd3.py", line 251, in from_transformer
controlnet.transformer_blocks.load_state_dict(transformer.transformer_blocks.state_dict())
File "/root/anaconda3/envs/geolight/lib/python3.9/site-packages/torch/nn/modules/module.py", line 2152, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for ModuleList:
Unexpected key(s) in state_dict: "12.norm1.linear.weight", "12.norm1.linear.bias", "12.norm1_context.linear.weight", "12.norm1_context.linear.bias", "12.attn.to_q.weight", "
12.attn.to_q.bias", "12.attn.to_k.weight", "12.attn.to_k.bias", "12.attn.to_v.weight", "12.attn.to_v.bias", "12.attn.add_k_proj.weight", "12.attn.add_k_proj.bias", "12.attn.add_v_pr
oj.weight", "12.attn.add_v_proj.bias", "12.attn.add_q_proj.weight", "12.attn.add_q_proj.bias", "12.attn.to_out.0.weight", "12.attn.to_out.0.bias", "12.attn.to_add_out.weight", "12.a
ttn.to_add_out.bias", "12.ff.net.0.proj.weight", "12.ff.net.0.proj.bias", "12.ff.net.2.weight", "12.ff.net.2.bias", "12.ff_context.net.0.proj.weight", "12.ff_context.net.0.proj.bias
", "12.ff_context.net.2.weight", "12.ff_context.net.2.bias"...
```

### System Info

- 🤗 Diffusers version: 0.29.2
- Platform: Linux-5.15.0-117-generic-x86_64-with-glibc2.27
- Running on a notebook?: No
- Running on Google Colab?: No
- Python version: 3.9.19
- PyTorch version (GPU?): 2.1.1+cu121 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Huggingface_hub version: 0.24.3
- Transformers version: 4.33.2
- Accelerate version: 0.33.0
- PEFT version: not installed
- Bitsandbytes version: not installed
- Safetensors version: 0.4.3
- xFormers version: not installed
- Accelerator: Tesla V100-SXM2-32GB, 32768 MiB
Tesla V100-SXM2-32GB, 32768 MiB
Tesla V100-SXM2-32GB, 32768 MiB
Tesla V100-SXM2-32GB, 32768 MiB VRAM
- Using GPU in script?:
- Using distributed or parallel set-up in script?:

### Who can help?

@haofanwang

Start in diffusers/models/controlnet_sd3.py at SD3ControlNetModel.from_transformer, especially the transformer_blocks state-dict loading shown in the traceback. Reproduce the issue with SD3Transformer2DModel.from_pretrained and num_layers=12, then verify that loading no longer reports unexpected keys for the extra transformer blocks.

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