TypeError: Missing a required argument with thunder.jit in NeMo SD ResBlock

@athitten is already working on this.

Since Jun 10, 2024.

### 🐛 Bug

Adding `thunder.jit` to `ResBlock` in the UNet stage of NeMo SD is raising an error. From looking at the ResBlock call in NeMo code, the class is called correctly with right arguments. In-spite of that its unsure why thunder is raising this error.

`Encountered exception TypeError: missing a required argument: 'emb' while tracing ResBlock`

Stack trace of the error can be found here:
[resblock_error.log](https://github.com/user-attachments/files/15685760/resblock_error.log)

### To Reproduce

Steps to reproduce the behavior:

1. Pull the appropriate NeMo docker image
2. Apply the git patch:
[resblock.patch](https://github.com/user-attachments/files/15685773/resblock.patch)

3. Run Stable Diffusion with the command:
```python
python examples/multimodal/text_to_image/stable_diffusion/sd_train.py trainer.precision=16 trainer.num_nodes=1 trainer.devices=1 ++exp_manager.max_time_per_run=00:00:03:00 trainer.max_steps=20 model.micro_batch_size=1 model.global_batch_size=1 model.data.synthetic_data=True exp_manager.exp_dir=/workspace/TestData/multimodal/stable_diffusion_train model.inductor=False model.cond_stage_config._target_=nemo.collections.multimodal.modules.stable_diffusion.encoders.modules.FrozenCLIPEmbedder ++model.cond_stage_config.version=openai/clip-vit-large-patch14 ++model.cond_stage_config.max_length=77 ~model.cond_stage_config.restore_from_path ~model.cond_stage_config.freeze ~model.cond_stage_config.layer model.unet_config.from_pretrained=null model.first_stage_config.from_pretrained=null model.unet_config.use_flash_attention=False model.unet_config.attention_resolutions=\[1\] model.unet_config.channel_mult=\[1\]`
```
cc: @tfogal

cc @tfogal