[Feature] support eager mode in model runner v2 (#5210)

### What this PR does / why we need it?
#5051 only implement a basic framework for model runner v2, but there
are still some bugs for e2e functionality, this PR aim to enable basic
functionality.
model runner v2 plans:
https://github.com/vllm-project/vllm-ascend/issues/5208

- vLLM version: release/v0.13.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: Ronald1995 <ronaldautomobile@163.com>

vllm_ascend/worker/v2/states.py

@@ -1,8 +1,28 @@
+# Adapt from https://github.com/vllm-project/vllm/blob/main/vllm/v1/worker/gpu/states.py
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# This file is a part of the vllm-ascend project.
+#
+
 from contextlib import contextmanager
 
 import torch
+import vllm
 from vllm.v1.utils import CpuGpuBuffer
-from vllm.v1.worker.gpu.states import RequestState, UvaBuffer
+from vllm.v1.worker.gpu.states import RequestState
 
 
 class AscendRequestState(RequestState):
@@ -18,16 +38,15 @@ class AscendRequestState(RequestState):
         device: torch.device,
         pin_memory: bool,
     ):
-        with uva_wrapper():
-            super().__init__(
-                max_num_reqs,
-                max_model_len,
-                max_num_batched_tokens,
-                num_speculative_steps,
-                vocab_size,
-                device,
-                pin_memory,
-            )
+        super().__init__(
+            max_num_reqs,
+            max_model_len,
+            max_num_batched_tokens,
+            num_speculative_steps,
+            vocab_size,
+            device,
+            pin_memory,
+        )
         # because we will override these attribute, delete these attribute to
         # make sure it's collected by python gc immediately.
         del self.prefill_token_ids
@@ -78,11 +97,9 @@ def uva_wrapper():
         def __init__(self, *args, **kwargs):
             pass
 
-    # TODO(Ronald1995): rectify this when NPU support uva.
-    global UvaBuffer
-    ori_class = UvaBuffer
     try:
-        UvaBuffer = UvaBufferWrapper
+        # TODO(Ronald1995): rectify this when NPU support uva.
+        vllm.v1.worker.gpu.states.UvaBuffer = UvaBufferWrapper
         yield
     finally:
-        UvaBuffer = ori_class
+        pass