add rmsnorm kernels support for npu

[zheliuyu]

What does this PR do?

As title.

Test script

from transformers import AutoModelForCausalLM, AutoTokenizer
import logging
import time


# Set the level to `DEBUG` to see which kernels are being called.
# logging.basicConfig(level=logging.DEBUG)

model_name = "Qwen/Qwen3-0.6B"

# load the tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto",
    use_kernels=True,
)

# prepare the model input
prompt = "Output the first 20 digits of pi."
messages = [
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
    enable_thinking=False,
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

# Print Runtime
start_time = time.time()
generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=32768
)
print("runtime: ", time.time()-start_time)

output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
content = tokenizer.decode(output_ids, skip_special_tokens=True).strip("\n")

print("content:", content)