[Refactor] Fix AttentionMaskBuilder singleton and remove redundant pcp_prefill_mask (#4870)

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

This PR fixes the `AttentionMaskBuilder` singleton initialization issue
introduced in PR #4779 and removes the unused `pcp_prefill_mask` field.

### Background

After PR #4779 made `AttentionMaskBuilder` a singleton with `@singleton`
decorator, the class constructor now requires a `device` parameter.
However, two initialization sites were still using the old parameterless
constructor, causing failures.

### Changes

1. **Fix singleton initialization**
- Fixed `AttentionMaskBuilder()` → `AttentionMaskBuilder(self.device)`
in `AscendMLAMetadataBuilder.__init__()`
- Fixed `AttentionMaskBuilder()` → `AttentionMaskBuilder(self.device)`
in `AscendAttentionMetadataBuilder.__init__()`

2. **Remove unused field**
- Removed `pcp_prefill_mask` field from
`AscendPrefillContextParallelMetadata` (never used in codebase)
   - Updated related test assertions

### Related

- Issue #5463
- PR #4779 (Unify all mask generation methods)
- PR #5389 (Make AttentionMaskBuilder singleton)

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

No. This is an internal refactoring.

## How was this patch tested?

- ✅ Local testing: No linter errors
- ✅ Unit tests for attention modules verified
- ⏳ CI pipeline

Signed-off-by: lico67373 <918688502@qq.com>
Co-authored-by: weijinqian0 <1184188277@qq.com>

vllm_ascend/worker/v2/attn_utils.py

@@ -58,9 +58,6 @@ def build_attn_metadata(
     decode_token_per_req: int,
     actual_seq_lengths_q: list[int],
     positions: torch.Tensor | None = None,
-    attn_mask: torch.Tensor
-    | None = None,
-    spec_attn_mask: torch.Tensor | None = None,
     attn_state: Any | None = None,
     graph_pad_size: int = -1,
     num_input_tokens: int = 0,
@@ -92,8 +89,6 @@ def build_attn_metadata(
             slot_mapping=slot_mapping,
             actual_seq_lengths_q=actual_seq_lengths_q,
             positions=positions,
-            attn_mask=attn_mask,
-            spec_attn_mask=spec_attn_mask,
             attn_state=attn_state,
             graph_pad_size=graph_pad_size,
             num_input_tokens=num_input_tokens,