[Feature]: Support 310P device run qwen2.5/3 dense and qwen2.5vl models (#5776)

### What this PR does / why we need it?
Add basic 310p support. Only dense models work with eager mode now.

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

---------

Signed-off-by: Tflowers-0129 <2906339855@qq.com>
Signed-off-by: Shaoxu Cheng <2906339855@qq.com>

tests/e2e/310p/test_offline_inference_310p.py

@@ -36,7 +36,9 @@ def test_llm_models(dtype: str, max_tokens: int) -> None:
         vllm_model.generate_greedy(example_prompts, max_tokens)
 
 
-def test_multimodal_vl():
+@pytest.mark.skip(reason="310P: multimodal test skipped, offline is ok")
+@pytest.mark.parametrize("dtype", ["float16"])
+def test_multimodal_vl(dtype: str):
     image = ImageAsset("cherry_blossom").pil_image.convert("RGB")
 
     img_questions = [
@@ -60,6 +62,7 @@ def test_multimodal_vl():
                         "max_pixels": 1280 * 28 * 28,
                         "fps": 1,
                     },
+                    dtype=dtype,
                     max_model_len=8192,
                     enforce_eager=True,
                     limit_mm_per_prompt={"image": 1}) as vllm_model:

tests/e2e/310p/test_offline_inference_parallel_310p.py

@@ -1,3 +1,20 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# Copyright 2023 The vLLM team.
+#
+# 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.
+
 import pytest
 
 from tests.e2e.conftest import VllmRunner
@@ -5,7 +22,6 @@ from tests.e2e.conftest import VllmRunner
 
 @pytest.mark.parametrize("dtype", ["float16"])
 @pytest.mark.parametrize("max_tokens", [5])
-@pytest.skip("310p does not support parallel inference now. Fix me")
 def test_models(dtype: str, max_tokens: int) -> None:
     example_prompts = [
         "Hello, my name is",