Add DeepSeek V3.2 support (#3270)

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

This PR added the initial DeepSeek V3.2 support with [vLLM
v0.11.0](https://github.com/vllm-project/vllm/tree/releases/v0.11.0)
(not released yet). We will complete vLLM adaptation as soon as
possible. This feature will be ready in recent 1-2 days.

Related doc: https://github.com/vllm-project/vllm-ascend/pull/3223 .

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

### How was this patch tested?
CI passed and Run deepseek doc soon.


- vLLM version: v0.11.0rc3
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.0

---------

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Signed-off-by: zzzzwwjj <1183291235@qq.com>
Signed-off-by: linfeng-yuan <1102311262@qq.com>
Signed-off-by: wxsIcey <1790571317@qq.com>
Signed-off-by: MengqingCao <cmq0113@163.com>
Co-authored-by: zzzzwwjj <1183291235@qq.com>
Co-authored-by: linfeng-yuan <1102311262@qq.com>
Co-authored-by: wxsIcey <1790571317@qq.com>
Co-authored-by: MengqingCao <cmq0113@163.com>

vllm_ascend/worker/worker_v1.py

@@ -43,7 +43,7 @@ from vllm.v1.outputs import (EMPTY_MODEL_RUNNER_OUTPUT, AsyncModelRunnerOutput,
 from vllm.v1.worker.worker_base import WorkerBase
 
 import vllm_ascend.envs as envs_ascend
-from vllm_ascend.ascend_config import init_ascend_config
+from vllm_ascend.ascend_config import get_ascend_config, init_ascend_config
 from vllm_ascend.device_allocator.camem import CaMemAllocator
 from vllm_ascend.distributed.parallel_state import init_ascend_model_parallel
 from vllm_ascend.platform import NPUPlatform
@@ -88,6 +88,17 @@ class NPUWorker(WorkerBase):
         # init ascend config and soc version
         init_ascend_config(vllm_config)
         init_ascend_soc_version()
+        if get_ascend_config().use_sfa:
+            # Direct import instead of using try_register_lib to ensure proper error handling when
+            # custom_ops is necessary but not available (e.g., in DeepSeek v3.2 deployments)
+            # yapf: disable
+            import custom_ops  # type: ignore # noqa
+
+            # yapf: enable
+            logger.info(
+                "custom_ops module loaded successfully. Custom operators like "
+                "torch.ops.custom.npu_sparse_flash_attention are now available."
+            )
 
         super().__init__(vllm_config=vllm_config,
                          local_rank=local_rank,