[Misc] Nit fix for disaggregated_prefill and ascend_forward_context (#2097)

we recently added disaggregated_prefill and ascend_forward_context
feature by
ba3dfbd59e
and
df0ec55162.
This PR fix some nit introduced by them to make the code clear.
1. drop `current_platform` usage. It'll lead unknown circular import
error in some case
2. update `set_ascend_forward_context` function to make the logic clear.
for example, remove V0 support in this function.
3. Remove useless `self.local_rank_across_dp` in worker
4. Remove `soc_info.py` to use `get_ascend_soc_version` instead.
 

- vLLM version: v0.10.0
- vLLM main:
02f82fe438

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

vllm_ascend/ascend_forward_context.py

@@ -7,9 +7,9 @@ import torch
 from vllm.config import VllmConfig
 from vllm.distributed import get_dp_group, get_ep_group, get_tp_group
 from vllm.forward_context import get_forward_context, set_forward_context
-from vllm.platforms import current_platform
 
 import vllm_ascend.envs as envs
+from vllm_ascend.platform import NPUPlatform
 
 
 class FusedMoEState(Enum):
@@ -22,8 +22,8 @@ class FusedMoEState(Enum):
 
 
 # TODO(zzzzwwjj): add soc_version to choose branch
-def get_fused_moe_state(ep_size: int, with_prefill: bool,
-                        is_deepseek_v3_r1: bool):
+def _get_fused_moe_state(ep_size: int, with_prefill: bool,
+                         is_deepseek_v3_r1: bool):
     # the fusion operator torch_npu.npu_grouped_matmul_finalize_routing called by allgather ep
     # only supports deepseek v3/r1
     if (envs.VLLM_ENABLE_FUSED_EXPERTS_ALLGATHER_EP and ep_size > 1
@@ -73,11 +73,9 @@ def set_ascend_forward_context(
         is_deepseek_v3_r1 = hasattr(
             vllm_config.model_config.hf_config, 'n_routed_experts'
         ) and vllm_config.model_config.hf_config.n_routed_experts == 256
-        fused_moe_state = get_fused_moe_state(ep_size, with_prefill,
-                                              is_deepseek_v3_r1)
-
+        fused_moe_state = _get_fused_moe_state(ep_size, with_prefill,
+                                               is_deepseek_v3_r1)
         forward_context.fused_moe_state = fused_moe_state
-
         forward_context.in_profile_run = in_profile_run
 
         # NOTE: This cannot be set using set_forward_context
@@ -85,15 +83,7 @@ def set_ascend_forward_context(
         forward_context.capturing = False
 
         if num_tokens is None and attn_metadata is not None:
-            if hasattr(attn_metadata, 'num_actual_tokens'):
-                # for v1 engine
-                num_tokens = attn_metadata.num_actual_tokens
-            else:
-                # for v0 engine
-                num_tokens = attn_metadata.num_prefill_tokens + attn_metadata.num_decode_tokens
-
-        if num_actual_tokens is None:
-            num_actual_tokens = num_tokens
+            num_tokens = attn_metadata.num_actual_tokens
 
         dp_world_size = get_dp_group().world_size
         if dp_world_size > 1 and forward_context.dp_metadata is not None:
@@ -105,6 +95,8 @@ def set_ascend_forward_context(
         forward_context.max_tokens_across_dp = max_tokens_across_dp
 
         if num_tokens is not None:
+            if num_actual_tokens is None:
+                num_actual_tokens = num_tokens
             tp_world_size = get_tp_group().world_size
             # NOTE: token num which need to pad to when mc2
             forward_context.padded_num_tokens = math.ceil(
@@ -112,7 +104,7 @@ def set_ascend_forward_context(
 
             mc2_mask = torch.zeros(forward_context.padded_num_tokens,
                                    dtype=torch.bool,
-                                   device=current_platform.device_type)
+                                   device=NPUPlatform.device_type)
             mc2_mask[:num_actual_tokens] = True
             forward_context.mc2_mask = mc2_mask