[HybridKV][Bugfix] Fix Hybrid kvcache sharing bug in same attention type (#3760)

### What this PR does / why we need it?
Part of https://github.com/vllm-project/vllm-ascend/pull/3106
Fix Hybrid kvcache sharing bug in same attention type
Change the `shared_by` logic so that the same attention spec could share
the same buffer instead of allocating more hbm.
After this pr, kvcache memory saved 50% in qwen3-next compared with
before (`self_attn:linear_attn=1:3` in an `attn_group`), and
`gpu_memory_utilization` could increase to `0.8` on Qwen3-Next when
running on A2 64G/card with tp4

<img width="2833" height="1540" alt="image"
src="https://github.com/user-attachments/assets/2a91fa99-fb0f-447c-9e8b-acd587890fbe"
/>

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

### How was this patch tested?
Test pass with the latest e2e test case on qwen3-next

- vLLM version: v0.11.0rc3
- vLLM main:
c9461e05a4

---------

Signed-off-by: MengqingCao <cmq0113@163.com>

tests/e2e/multicard/test_qwen3_next.py

@@ -27,12 +27,12 @@ from tests.e2e.conftest import VllmRunner
 def test_models_distributed_Qwen3_NEXT_TP4():
     example_prompts = [
         "Hello, my name is",
-    ]
+    ] * 4
     max_tokens = 5
     with VllmRunner("Qwen/Qwen3-Next-80B-A3B-Instruct",
                     tensor_parallel_size=4,
                     max_model_len=4096,
-                    gpu_memory_utilization=0.7,
+                    gpu_memory_utilization=0.8,
                     distributed_executor_backend="mp",
                     enforce_eager=True) as vllm_model:
         vllm_model.generate_greedy(example_prompts, max_tokens)