[bugfix](CP) Fix and unify the PD request discrimination logic. (#5939)

### What this PR does / why we need it?
Since the PR (https://github.com/vllm-project/vllm/pull/32118) has
modified the criteria for judging Prefill and Decode requests in vLLM,
PCPManager needs to synchronize with this standard. As PCPManager
involves multiple calculations of PD request counts, this PR attempts to
consolidate the related logic and update the PD request count once per
batch.

### How was this patch tested?
```bash
pytest tests/e2e/multicard/4-cards/long_sequence/test_mtp.py
```

- vLLM version: v0.13.0
- vLLM main:
11b6af5280

Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>

vllm_ascend/worker/model_runner_v1.py

@@ -600,10 +600,16 @@ class NPUModelRunner(GPUModelRunner):
             req_indices, positions_np)
         self.input_batch.block_table.commit_slot_mapping(
             total_num_scheduled_tokens)
+
+        if self.pcp_size * self.dcp_size > 1:
+            self.pcp_manager.init_batch_info(
+                num_scheduled_tokens,
+                self.input_batch.num_reqs,
+            )
+
         # for pcp, prefill mtp should use origin scheduleroutput ,
         if self.speculative_config and self.pcp_size * self.dcp_size > 1:
             self.pcp_manager.generate_pcp_mtp_input(
-                num_reqs,
                 total_num_scheduled_tokens,
                 scheduler_output.num_scheduled_tokens,
                 with_prefill,
@@ -621,8 +627,6 @@ class NPUModelRunner(GPUModelRunner):
                                  num_reqs], position_pcp = self.pcp_manager.update_tokens_for_pcp(
                                      num_scheduled_tokens[:num_reqs],
                                      self.arange_np,
-                                     self.input_batch.num_reqs,
-                                     self.reorder_batch_threshold,
                                  )
             # Re-update after PCP split sequences.
             total_num_scheduled_tokens = sum(num_scheduled_tokens)
@@ -772,8 +776,7 @@ class NPUModelRunner(GPUModelRunner):
             num_draft_tokens = None
             num_sampled_tokens = np.ones(num_reqs, dtype=np.int32)
             if self.pcp_size * self.dcp_size > 1:
-                logits_indices = self.pcp_manager.get_logits_indices(
-                    cu_num_tokens, num_reqs)
+                logits_indices = self.pcp_manager.get_logits_indices(cu_num_tokens)
                 logits_indices = logits_indices.pin_memory().to(
                     self.device, non_blocking=True)
             else:
@@ -1020,9 +1023,8 @@ class NPUModelRunner(GPUModelRunner):
                     num_reqs = self.input_batch.num_reqs
                     ori_query_lens = query_start_loc_pcp_full_cpu[1:num_reqs+1] - \
                         query_start_loc_pcp_full_cpu[:num_reqs]
-                    num_prefill_reqs = (ori_query_lens
-                                        > self.decode_threshold).sum().item()
-                    num_decode_reqs = num_reqs - num_prefill_reqs
+                    num_prefill_reqs = self.pcp_manager.num_prefill_reqs
+                    num_decode_reqs = self.pcp_manager.num_decode_reqs
                 else:
                     long_seq_metadata = None  # type: ignore
                     num_prefill_reqs = 0
@@ -1976,7 +1978,7 @@ class NPUModelRunner(GPUModelRunner):
                 )
             return blk_table_tensor, slot_mapping
 
-        long_seq_metdadata = _get_pcp_metadata(num_tokens)
+        self.long_seq_metadata = _get_pcp_metadata(num_tokens)
         block_table_gid_0, slot_mapping_gid_0 = _get_block_table_and_slot_mapping(0)
 
         actual_last_loc = self.query_start_loc.np[num_reqs_padded]
@@ -2008,7 +2010,7 @@ class NPUModelRunner(GPUModelRunner):
             positions=self.positions.gpu,
             attn_state=self.attn_state,
             decode_token_per_req=self.decode_token_per_req,
-            prefill_context_parallel_metadata=long_seq_metdadata,
+            prefill_context_parallel_metadata=self.long_seq_metadata,
         )
 
         if logits_indices is not None and self.cache_config.kv_sharing_fast_prefill:
@@ -2198,6 +2200,11 @@ class NPUModelRunner(GPUModelRunner):
                 force_has_lora=activate_lora,
             )
         )
+        if self.pcp_size * self.dcp_size > 1:
+            self.pcp_manager.init_batch_info(
+                num_scheduled_tokens,
+                num_reqs,
+            )
         if cudagraph_runtime_mode is None:
             cudagraph_runtime_mode = _cudagraph_mode
         else: