[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>

vllm_ascend/platform.py

@@ -38,6 +38,27 @@ from vllm_ascend.utils import (
     prefill_context_parallel_enable, update_aclgraph_sizes,
     update_cudagraph_capture_sizes, update_default_aclgraph_sizes)
 
+# set custom ops path
+CUR_DIR = os.path.dirname(os.path.realpath(__file__))
+CUSTOM_OPP_PATH = os.path.join(CUR_DIR, "vllm_ascend", "_cann_ops_custom",
+                               "vendors", "customize")
+CUSTOM_LIB_PATH = os.path.join(CUSTOM_OPP_PATH, "op_api", "lib")
+
+if os.path.exists(CUSTOM_OPP_PATH):
+    current_cust_opp_path = os.environ.get("ASCEND_CUSTOM_OPP_PATH", "")
+    if current_cust_opp_path:
+        os.environ[
+            "ASCEND_CUSTOM_OPP_PATH"] = f"{CUSTOM_OPP_PATH}:{current_cust_opp_path}"
+    else:
+        os.environ["ASCEND_CUSTOM_OPP_PATH"] = CUSTOM_OPP_PATH
+
+if os.path.exists(CUSTOM_LIB_PATH):
+    current_lib_path = os.environ.get("LD_LIBRARY_PATH", "")
+    if current_lib_path:
+        os.environ["LD_LIBRARY_PATH"] = f"{CUSTOM_LIB_PATH}:{current_lib_path}"
+    else:
+        os.environ["LD_LIBRARY_PATH"] = CUSTOM_LIB_PATH
+
 if TYPE_CHECKING:
     from vllm.config import ModelConfig, VllmConfig
     from vllm.utils import FlexibleArgumentParser