### What this PR does / why we need it?
1. New Custom NPU Operation: Introduced npu_gemma_rms_norm in
csrc/torch_binding.cpp to provide optimized Gemma RMS Normalization
support for Ascend NPUs. This function includes logic to handle dynamic
shapes for the gamma tensor.
2. PyTorch Operator Registration: The new npu_gemma_rms_norm operation
has been registered with the PyTorch custom operator library, making it
accessible from Python.
Meta-Implementation for ACLGraph: A corresponding meta-implementation,
npu_gemma_rms_norm_meta, was added in csrc/torch_binding_meta.cpp. This
is crucial for symbolic tracing and allowing the custom kernel to be
captured and optimized by ACLGraph.
3. Python Frontend Integration: The vllm_ascend/ops/layernorm.py file
was updated to utilize the newly added
torch.ops._C_ascend.npu_gemma_rms_norm for Gemma RMS Normalization,
replacing the generic torch_npu.npu_rms_norm
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.14.1
- vLLM main:
dc917cceb8
---------
Signed-off-by: SunnyLee219 <3294305115@qq.com>
Signed-off-by: LeeWenquan <83354342+SunnyLee151064@users.noreply.github.com>
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