[Kernel] add custom op GmmSwigluQuantWeightNzTensorList (#3804)

### What this PR does / why we need it?

This PR introduces support for adding custom CANN `aclnn` ops to
`vllm-ascend`, allowing users to define and use their own custom
operators.

Key changes include:
- Building and installing custom ops into the `vllm-ascend`-specified
directory
- Binding the `aclnn` op interface to the `torch.ops._C_ascend` module
- Enabling invocation of these ops within `vllm-ascend`

This PR includes a sample custom op:
`aclnnGroupedMatmulSwigluQuantWeightNzTensorList`, which is adapted from
the CANN operator
[`aclnnGroupedMatmulSwigluQuantWeightNZ`](https://www.hiascend.com/document/detail/zh/canncommercial/83RC1/API/aolapi/context/aclnnGroupedMatmulSwigluQuantWeightNZ.md).
Its input parameters `weight` and `weight_scale` now accept
`list[torch.Tensor]` (i.e., `at::TensorList`).

### Does this PR introduce _any_ user-facing change?

No.


- vLLM version: v0.11.2

---------

Signed-off-by: QianChenxi <chenxi.qian.cq@outlook.com>

docs/source/developer_guide/feature_guide/add_custom_aclnn_op.md

@@ -0,0 +1,25 @@
+# Adding a custom aclnn operation
+
+This document describes how to add a custom aclnn operation to vllm-ascend.
+
+## How custom aclnn operation works in vllm-ascend?
+
+Custom aclnn operations are built and installed into `vllm_ascend/cann_ops_custom` directory during the build process of vllm-ascend. Then the aclnn operators are bound to `torch.ops._C_ascend` module, enabling users to invoke them in vllm-ascend python code.
+
+To enable custom operations, use the following code:
+
+```python
+from vllm_ascend.utils import enable_custom_op
+
+enable_custom_op()
+```
+
+## How to add a custom aclnn operation?
+
+- Create a new operation folder under `csrc` directory
+- Create `op_host` and `op_kernel` directories for host and kernel source code
+- Add build options in `csrc/build_aclnn.sh` for supported SOC. Note that multiple ops should be separated with `;`, i.e. `CUSTOM_OPS=op1;op2;op3`
+- Bind aclnn operators to torch.ops._C_ascend module in `csrc/torch_binding.cpp`
+- Write a meta implementation in `csrc/torch_binding_meta.cpp` for op being captured into aclgraph
+
+After a successful build of vllm-ascend, the custom aclnn operation can be invoked in python code.

docs/source/developer_guide/feature_guide/index.md

@@ -12,4 +12,5 @@ eplb_swift_balancer.md
 Multi_Token_Prediction
 ACL_Graph
 KV_Cache_Pool_Guide
+add_custom_aclnn_op
 :::