[feature]dcp&pcp support mlapo (#5672)

### What this PR does / why we need it?
mlapo in deepseek is a huge performance improvement in decode, this pr
support pcp & dcp with mlapo

### Does this PR introduce _any_ user-facing change?
NO

### How was this patch tested?

- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef

---------

Signed-off-by: zhenwenqi2024 <zhenwenqi_2022@qq.com>

vllm_ascend/attention/context_parallel/mla_cp.py

@@ -70,6 +70,26 @@ class AscendMlaCPMetadataBuilder(AscendMLAMetadataBuilder):
                                               dtype=torch.uint8,
                                               device=device)
 
+    def build(
+        self,
+        common_prefix_len: int,
+        common_attn_metadata: AscendCommonAttentionMetadata,
+        fast_build: bool = False,
+    ) -> AscendMLAMetadata:
+        metadata_cls = super().build(common_prefix_len, common_attn_metadata)
+        if self.num_prefills == 0 and self.pcp_size > 1:
+            self.slot_mapping[:self.
+                              num_decode_tokens] = self.slot_mapping[:self.
+                                                                     num_decode_tokens
+                                                                     * self.
+                                                                     pcp_size:
+                                                                     self.
+                                                                     pcp_size]
+            self.slot_mapping[self.num_decode_tokens:self.num_decode_tokens *
+                              self.pcp_size].fill_(-1)
+        metadata_cls.slot_mapping = self.slot_mapping
+        return metadata_cls
+
     @classmethod
     def get_cudagraph_support(
         cls: type["AscendMlaCPMetadataBuilder"],
@@ -363,8 +383,7 @@ class AscendMlaCPImpl(AscendMLAImpl):
         decode_ql_nope, decode_q_pe = self.reorg_decode_q(
             decode_ql_nope, decode_q_pe)
         decode_q_pe = self.rope_single(decode_q_pe, cos, sin)
-        decode_slots = attn_metadata.slot_mapping[:num_decode_tokens *
-                                                  self.pcp_size:self.pcp_size]
+        decode_slots = attn_metadata.slot_mapping[:num_decode_tokens]
         decode_kv_no_split = kv_no_split[:num_decode_tokens]
         decode_k_pe, decode_k_nope = self.exec_kv_decode(
             decode_kv_no_split, cos, sin, kv_cache, decode_slots)

vllm_ascend/attention/mla_v1.py

@@ -438,7 +438,6 @@ class AscendMLAMetadataBuilder(MLACommonMetadataBuilder[AscendMLAMetadata]):
         if self.num_decodes > 0:
             decode_metadata = self.build_decode_metadata(
                 common_prefix_len, common_attn_metadata)
-
         return self.metadata_cls(  # type: ignore
             num_actual_tokens_pcp_padded=self.num_actual_tokens,
             num_input_tokens=common_attn_metadata.num_input_tokens,
@@ -1330,7 +1329,7 @@ class AscendMLAImpl(MLAAttentionImpl):
             self.W_UK_T,
             decode_k_nope,
             decode_k_pe,
-            attn_metadata.slot_mapping[:bsz].flatten(),
+            attn_metadata.slot_mapping[:bsz],
             quant_scale0=self.quant_scale0,
             quant_offset0=self.quant_offset0,
             bias0=self.quant_bias_qkv,