[Feature] adapt to uva buffer and main2main (#6657)

### What this PR does / why we need it?
vllm model runner v2 use uva buffer to prepare input data, but npu
doesn't support uva yet, this pr implement a uvawrapper class to mimic
gpu's uva backend. what's more, this pr make some modifications to adapt
to the newer main branch.

### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
- vLLM main:
13397841ab

---------

Signed-off-by: Ronald1995 <ronaldautomobile@163.com>

vllm_ascend/platform.py

@@ -551,7 +551,7 @@ class NPUPlatform(Platform):
         vllm_config: VllmConfig,
         dp_metadata,
         virtual_engine: int = 0,
-        num_tokens: int | None = None,
+        num_tokens: int = 0,
         num_tokens_across_dp: torch.Tensor | None = None,
         cudagraph_runtime_mode=None,
         batch_descriptor=None,
@@ -601,10 +601,6 @@ class NPUPlatform(Platform):
         if not envs_vllm.VLLM_USE_V2_MODEL_RUNNER:
             return {}
 
-        num_actual_tokens = list(attn_metadata.values())[0].num_actual_tokens
-        if num_tokens is None:
-            num_tokens = num_actual_tokens
-
         moe_comm_type = select_moe_comm_method(
             num_tokens,
             vllm_config,
@@ -636,10 +632,13 @@ class NPUPlatform(Platform):
 
         # TODO(Levi-JQ): another PR to normalize the enabling logic for sp/fc2
         flashcomm_v2_enabled = flashcomm2_enable() and tp_world_size > 1 and num_tokens is not None
-        pad_size = 0
+        pad_size = None
+        padded_length = None
         if sp_enabled or flashcomm_v2_enabled:
             pad_size = (tp_world_size - (num_tokens % tp_world_size)) % tp_world_size
 
+        if num_tokens is None and attn_metadata is not None:
+            num_tokens = list(attn_metadata.values())[0].num_actual_tokens
         dp_world_size = get_dp_group().world_size
         if dp_world_size > 1 and dp_metadata is not None:
             max_tokens_across_dp = dp_metadata.max_tokens_across_dp_cpu.item()
@@ -648,8 +647,9 @@ class NPUPlatform(Platform):
                 pad_size = padded_length - num_tokens
         else:
             max_tokens_across_dp = num_tokens
-
+        mc2_mask = None
         if num_tokens is not None:
+            num_actual_tokens = num_tokens
             # NOTE: token num which need to pad to when mc2
             padded_num_tokens = math.ceil(max_tokens_across_dp / tp_world_size) * tp_world_size
             reserved_mc2_mask = get_mc2_mask()