Refactor e2e CI (#2276)

Refactor E2E CI to make it clear and faster
1. remove some uesless e2e test
2. remove some uesless function
3. Make sure all test runs with VLLMRunner to avoid oom error
4. Make sure all ops test end with torch.empty_cache to avoid oom error
5. run the test one by one to avoid resource limit error


- vLLM version: v0.10.1.1
- vLLM main:
a344a5aa0a

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

tests/e2e/singlecard/test_aclgraph.py

@@ -21,16 +21,13 @@ Run `pytest tests/compile/test_aclgraph.py`.
 """
 
 import pytest
-import torch
-from vllm import LLM, SamplingParams
+from vllm import SamplingParams
 
 from tests.e2e.conftest import VllmRunner
 from tests.e2e.model_utils import check_outputs_equal
 
 MODELS = [
-    "Qwen/Qwen2.5-0.5B-Instruct",
-    # TODO: REVERT ME when oom is fixed
-    # "vllm-ascend/Qwen3-30B-A3B-Puring"
+    "Qwen/Qwen3-0.6B",
 ]
 
 
@@ -46,17 +43,19 @@ def test_models_with_aclgraph(
     ]
 
     sampling_params = SamplingParams(max_tokens=max_tokens, temperature=0.0)
-    # TODO: change to use vllmrunner when the registry of custom op is solved
-    # while running pytest
-    vllm_model = LLM(model, max_model_len=1024)
-    vllm_aclgraph_outputs = vllm_model.generate(prompts, sampling_params)
-    del vllm_model
-    torch.npu.empty_cache()
+    with VllmRunner(
+            model,
+            max_model_len=1024,
+            enforce_eager=False,
+    ) as runner:
+        vllm_aclgraph_outputs = runner.model.generate(prompts, sampling_params)
 
-    vllm_model = LLM(model, enforce_eager=True, max_model_len=1024)
-    vllm_eager_outputs = vllm_model.generate(prompts, sampling_params)
-    del vllm_model
-    torch.npu.empty_cache()
+    with VllmRunner(
+            model,
+            max_model_len=1024,
+            enforce_eager=True,
+    ) as runner:
+        vllm_eager_outputs = runner.model.generate(prompts, sampling_params)
 
     vllm_aclgraph_outputs_list = []
     for output in vllm_aclgraph_outputs:
@@ -74,21 +73,3 @@ def test_models_with_aclgraph(
         name_0="vllm_eager_outputs",
         name_1="vllm_aclgraph_outputs",
     )
-
-
-def test_deepseek_raises_error(monkeypatch: pytest.MonkeyPatch) -> None:
-    with monkeypatch.context() as m:
-        m.setenv("VLLM_USE_MODELSCOPE", "True")
-        with pytest.raises(NotImplementedError) as excinfo:
-            VllmRunner("deepseek-ai/DeepSeek-V2-Lite-Chat",
-                       max_model_len=1024,
-                       enforce_eager=False)
-        assert "ACL Graph does not support deepseek" in str(excinfo.value)
-
-
-@pytest.mark.parametrize("model", MODELS)
-def test_ray_backend_sets_no_compilation(model: str) -> None:
-    runner = VllmRunner(model,
-                        enforce_eager=False,
-                        distributed_executor_backend="ray")
-    assert runner.model.llm_engine.vllm_config.compilation_config.level == 0