[Refactor]5/N Extract common code of mla_v1.py & extract mla_cp (#5097)

RFC: https://github.com/vllm-project/vllm-ascend/issues/4629
Reason：
The functions related to Cp differ significantly from those of normal
MLA-Attention, but the coupling is quite severe.

Steps：
1)Extract common code AscendMLAMetadataBuilder.build to 4 functions: 
build_prefill_metadata, build_decode_metadata,build_cp_metadata,
build_chunked_metadata

todo：
1)refactor function _compute_prefill_context;
2)refactor function _mla_preprocess,_mla_decode_preprocess
3）Extract public data and processing functions from the attention_cp.py
and mla_cp.py files to the common_cp file.

vLLM version: 0.13.0rc3
vLLM main:
ad32e3e19c

- vLLM version: 0.13.0rc3
- vLLM main:
ad32e3e19c

---------

Signed-off-by: wujinyuan1 <wjy9595@qq.com>
Signed-off-by: wujinyuan1 <wujinyuan1@huawei.com>
Co-authored-by: wujinyuan1 <wjy9595@qq.com>
Co-authored-by: weijinqian0 <1184188277@qq.com>

vllm_ascend/attention/common_cp.py

@@ -0,0 +1,40 @@
+from dataclasses import dataclass
+from typing import Optional
+
+import torch
+
+
+@dataclass
+class AscendPCPMetadata:
+    q_head_idx: torch.Tensor = None
+    q_tail_idx: torch.Tensor = None
+    kv_with_q_head_nomask_idx: torch.Tensor = None
+    kv_with_q_head_mask_idx: torch.Tensor = None
+    kv_with_q_tail_nomask_idx: torch.Tensor = None
+    kv_with_q_tail_mask_idx: torch.Tensor = None
+    attn_mask_seqlens: torch.Tensor = None
+    head_attn_nomask_seqlens: torch.Tensor = None
+    tail_attn_nomask_seqlens: torch.Tensor = None
+    q_full_idx: torch.Tensor = None
+    pcp_prefill_mask: torch.Tensor = None
+    pcp_allgather_restore_idx: Optional[list[int]] = None
+
+
+@dataclass
+class CPChunkedContextMetadata:
+    # New for MLA (compared to FlashAttention)
+    # For handling chunked prefill
+    cu_seq_lens: torch.Tensor
+    starts: torch.Tensor
+    seq_tot: list[int]
+    max_seq_lens: list[int]
+    workspace: torch.Tensor
+    chunk_seq_lens: torch.Tensor
+    chunk_seq_lens_npu: torch.Tensor
+    # for mla DCP & PCP
+    padded_chunk_seq_lens_npu: torch.Tensor = None
+    padded_local_chunk_seq_lens: Optional[list[list[int]]] = None
+    local_context_lens_allranks: Optional[list[list[int]]] = None
+    padded_local_cu_seq_lens: torch.Tensor = None
+    cu_seq_lens_lst: Optional[list[list[int]]] = None
+    chunk_size: Optional[int] = None