[KVCache][Bugfix] Fix kv cache initialization error of attention layer (#3113)

### What this PR does / why we need it?
Fixes #3096 
1. Fix kv cache initialization error of attention layer. There are some
models with layer name like `attn.attn`, instead of `self_attn`, but the
initialization of kv cache tensors only check for `self_attn` and
`attn.attn`, which leding to the error `AssertionError: Some layers are
not correctly initialized`
2. Set the default value of input arg `sampling_metadata` in
`compute_logits` for the modeling files in vllm-ascend. Thus fixing the
error `Qwen3NextForCausalLM.compute_logits() missing 1 required
positional argument: 'sampling_metadata'`

### Does this PR introduce _any_ user-facing change?
N/A

### How was this patch tested?
test locally with internlm


- vLLM version: v0.10.2
- vLLM main:
5aeb925452

---------

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

vllm_ascend/torchair/models/torchair_deepseek_mtp.py

@@ -170,7 +170,7 @@ class TorchairDeepSeekMultiTokenPredictor(DeepSeekMultiTokenPredictor):
     def compute_logits(
         self,
         hidden_states: torch.Tensor,
-        sampling_metadata,  # type: ignore
+        sampling_metadata=None,  # type: ignore
         spec_step_idx: int = 0,
     ) -> torch.Tensor:
         current_step_idx = (spec_step_idx % self.num_mtp_layers)