[Bugfix] Fix num_hidden_layers when Qwen2-Audio 7B (#1803)

### What this PR does / why we need it?
Fix num_hidden_layers when Qwen2-Audio 7B and #1760 ：
```
INFO 07-15 04:38:53 [platform.py:174] PIECEWISE compilation enabled on NPU. use_inductor not supported - using only ACL Graph mode
Traceback (most recent call last):
  File "/workspace/test1.py", line 58, in <module>
    main(audio_count)
  File "/workspace/test1.py", line 38, in main
    llm = LLM(model="Qwen/Qwen2-Audio-7B-Instruct",
  File "/vllm-workspace/vllm/vllm/entrypoints/llm.py", line 271, in __init__
    self.llm_engine = LLMEngine.from_engine_args(
  File "/vllm-workspace/vllm/vllm/engine/llm_engine.py", line 494, in from_engine_args
    vllm_config = engine_args.create_engine_config(usage_context)
  File "/vllm-workspace/vllm/vllm/engine/arg_utils.py", line 1286, in create_engine_config
    config = VllmConfig(
  File "/usr/local/python3.10.17/lib/python3.10/site-packages/pydantic/_internal/_dataclasses.py", line 123, in __init__
    s.__pydantic_validator__.validate_python(ArgsKwargs(args, kwargs), self_instance=s)
  File "/vllm-workspace/vllm/vllm/config.py", line 4624, in __post_init__
    current_platform.check_and_update_config(self)
  File "/vllm-workspace/vllm-ascend/vllm_ascend/platform.py", line 180, in check_and_update_config
    update_aclgraph_sizes(vllm_config)
  File "/vllm-workspace/vllm-ascend/vllm_ascend/utils.py", line 307, in update_aclgraph_sizes
    num_hidden_layers = vllm_config.model_config.hf_config.num_hidden_layers
  File "/usr/local/python3.10.17/lib/python3.10/site-packages/transformers/configuration_utils.py", line 211, in __getattribute__
    return super().__getattribute__(key)
AttributeError: 'Qwen2AudioConfig' object has no attribute 'num_hidden_layers'
```

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

Closes: https://github.com/vllm-project/vllm-ascend/issues/1780
https://github.com/vllm-project/vllm-ascend/issues/1760
https://github.com/vllm-project/vllm-ascend/issues/1276
https://github.com/vllm-project/vllm-ascend/issues/359

- vLLM version: v0.10.0
- vLLM main:
7728dd77bb

Signed-off-by: hfadzxy <starmoon_zhang@163.com>

tests/e2e/singlecard/test_offline_inference.py

@@ -27,6 +27,7 @@ import pytest
 import vllm  # noqa: F401
 from modelscope import snapshot_download  # type: ignore[import-untyped]
 from vllm import SamplingParams
+from vllm.assets.audio import AudioAsset
 from vllm.assets.image import ImageAsset
 
 import vllm_ascend  # noqa: F401
@@ -36,12 +37,18 @@ MODELS = [
     "Qwen/Qwen2.5-0.5B-Instruct",
     "Qwen/Qwen3-0.6B-Base",
 ]
-MULTIMODALITY_MODELS = ["Qwen/Qwen2.5-VL-3B-Instruct"]
+MULTIMODALITY_VL_MODELS = ["Qwen/Qwen2.5-VL-3B-Instruct"]
+MULTIMODALITY_AUDIO_MODELS = ["Qwen/Qwen2-Audio-7B-Instruct"]
 
 QUANTIZATION_MODELS = [
     "vllm-ascend/Qwen2.5-0.5B-Instruct-W8A8",
 ]
 os.environ["PYTORCH_NPU_ALLOC_CONF"] = "max_split_size_mb:256"
+AUDIO_ASSETS = [AudioAsset("mary_had_lamb"), AudioAsset("winning_call")]
+AUDIO_PROMPT_TEMPLATES = {
+    1: "What is recited in the audio?",
+    2: "What sport and what nursery rhyme are referenced?"
+}
 
 
 @pytest.mark.parametrize("model", MODELS)
@@ -84,8 +91,8 @@ def test_quantization_models(model: str, max_tokens: int) -> None:
         vllm_model.generate_greedy(example_prompts, max_tokens)
 
 
-@pytest.mark.parametrize("model", MULTIMODALITY_MODELS)
-def test_multimodal(model, prompt_template, vllm_runner):
+@pytest.mark.parametrize("model", MULTIMODALITY_VL_MODELS)
+def test_multimodal_vl(model, prompt_template, vllm_runner):
     image = ImageAsset("cherry_blossom") \
         .pil_image.convert("RGB")
     img_questions = [
@@ -108,6 +115,45 @@ def test_multimodal(model, prompt_template, vllm_runner):
                                    max_tokens=64)
 
 
+def prepare_audio_inputs(audio_count: int):
+    audio_prompt = "".join([
+        f"Audio {idx+1}: <|audio_bos|><|AUDIO|><|audio_eos|>\n"
+        for idx in range(audio_count)
+    ])
+    question = AUDIO_PROMPT_TEMPLATES[audio_count]
+    prompt = ("<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n"
+              "<|im_start|>user\n"
+              f"{audio_prompt}{question}<|im_end|>\n"
+              "<|im_start|>assistant\n")
+    mm_data = {
+        "audio":
+        [asset.audio_and_sample_rate for asset in AUDIO_ASSETS[:audio_count]]
+    }
+    inputs = {"prompt": prompt, "multi_modal_data": mm_data}
+    return inputs
+
+
+@pytest.mark.parametrize("model", MULTIMODALITY_AUDIO_MODELS)
+@pytest.mark.parametrize("audio_count", [2])
+@pytest.mark.parametrize("max_tokens", [10])
+def test_multimodal_audio(model: str, audio_count: int,
+                          max_tokens: int) -> None:
+    inputs = prepare_audio_inputs(audio_count)
+
+    sampling_params = SamplingParams(temperature=0.2,
+                                     max_tokens=max_tokens,
+                                     stop_token_ids=None)
+
+    with VllmRunner(model,
+                    max_model_len=4096,
+                    max_num_seqs=5,
+                    enforce_eager=False,
+                    dtype="bfloat16",
+                    limit_mm_per_prompt={"audio": audio_count},
+                    gpu_memory_utilization=0.9) as vllm_model:
+        vllm_model.generate(inputs, sampling_params=sampling_params)
+
+
 @patch.dict(os.environ, {"VLLM_ASCEND_ENABLE_TOPK_TOPP_OPTIMIZATION": "1"})
 def test_models_topk() -> None:
     example_prompts = [