[CI] refect e2e ci test (#5246)

### What this PR does / why we need it?
efect e2e ci test：
1. tests/e2e/singlecard/pooling/test_embedding.py: remove the eager
parameter and rename test case
2. tests/e2e/singlecard/pooling/test_scoring.py: Rename test cases
3. tests/e2e/singlecard/pooling/test_classification.py: Rename test case
4. tests/e2e/singlecard/test_quantization.py: remove the eager parameter
and chage model to vllm-ascend/Qwen2.5-0.6B-W8A8 and Rename test case
5. tests/e2e/multicard/test_shared_expert_dp.py: Rename test cases
6. tests/e2e/singlecard/test_sampler.py: Rename test cases
7. tests/e2e/singlecard/test_aclgraph_accuracy.py: Rename test cases
8. tests/e2e/multicard/test_offline_inference_distributed.py: Rename
test cases and remove the eager parameter
9. tests/e2e/multicard/long_sequence/test_accuracy.py: Rename test cases
and remove the eager parameter
10. tests/e2e/multicard/long_sequence/test_basic.py: Rename test cases
and remove the eager parameter
11.tests/e2e/multicard/test_expert_parallel.py:remove the eager
parameter
12.tests/e2e/multicard/test_full_graph_mode.py:remove the eager
parameter
13.tests/e2e/multicard/test_ilama_lora_tp2.py:remove the eager parameter

14.tests/e2e/singlecard/spec_decode_v1/test_v1_mtp_correctness.py:remove
the eager parameter
15.tests/e2e/singlecard/spec_decode_v1/test_v1_spec_decode.py:remove the
eager parameter
16.tests/e2e/singlecard/test_aclgraph_accuracy.py:remove the eager
parameter
17.tests/e2e/singlecard/test_camem.py:remove the eager parameter
18.tests/e2e/singlecard/test_ilama_lora.py:remove the eager parameter

19.tests/e2e/singlecard/test_multistream_overlap_shared_expert.py:remove
the eager parameter
20.tests/e2e/singlecard/test_vlm.py:remove the eager parameter
21.tests/e2e/singlecard/test_xli:remove the eager parameter

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

### How was this patch tested?

- vLLM version: release/v0.13.0
- vLLM main:
ad32e3e19c

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

tests/e2e/multicard/long_sequence/test_accuracy.py

@@ -36,7 +36,7 @@ MODELS = [
                     reason="0.12.0 is not supported for context sequence.")
 @pytest.mark.parametrize("model", MODELS)
 @pytest.mark.parametrize("max_tokens", [10])
-def test_output_between_tp_and_cp(
+def test_models_long_sequence_output_between_tp_and_cp(
     model: str,
     max_tokens: int,
 ) -> None:
@@ -69,7 +69,6 @@ def test_output_between_tp_and_cp(
             "tensor_parallel_size": 1,
             "decode_context_parallel_size": 1,
             "prefill_context_parallel_size": 2,
-            "enforce_eager": False,
             "compilation_config": {
                 "cudagraph_mode": "FULL_DECODE_ONLY",
                 "cudagraph_capture_sizes": [4, 8, 24, 48, 60]

tests/e2e/multicard/long_sequence/test_basic.py

@@ -34,7 +34,7 @@ os.environ["HCCL_BUFFSIZE"] = "768"
 
 @pytest.mark.skipif(vllm_version_is('0.12.0'),
                     reason="0.12.0 is not supported for context sequence.")
-def test_pcp_dcp_basic():
+def test_models_pcp_dcp_basic():
     prompts = [
         "The capital of France is", "Hello, my name is Tom, I am",
         "The president of United States is", "AI future is"
@@ -69,7 +69,7 @@ def test_pcp_dcp_basic():
 
 @pytest.mark.skipif(vllm_version_is('0.12.0'),
                     reason="0.12.0 is not supported for context sequence.")
-def test_pcp_dcp_full_graph():
+def test_models_pcp_dcp_full_graph():
     prompts = [
         "The capital of France is", "Hello, my name is Tom, I am",
         "The president of United States is", "AI future is"
@@ -77,7 +77,6 @@ def test_pcp_dcp_full_graph():
     model = "deepseek-ai/DeepSeek-V2-Lite-Chat"
     sampling_params = SamplingParams(max_tokens=32, temperature=0.0)
     with VllmRunner(model,
-                    enforce_eager=False,
                     max_model_len=1024,
                     tensor_parallel_size=2,
                     prefill_context_parallel_size=2,
@@ -93,7 +92,6 @@ def test_pcp_dcp_full_graph():
 
     model = "vllm-ascend/Qwen3-30B-A3B-W8A8"
     with VllmRunner(model,
-                    enforce_eager=False,
                     max_model_len=1024,
                     tensor_parallel_size=2,
                     prefill_context_parallel_size=2,
@@ -110,7 +108,7 @@ def test_pcp_dcp_full_graph():
 
 @pytest.mark.skipif(vllm_version_is('0.12.0'),
                     reason="0.12.0 is not supported for context sequence.")
-def test_pcp_dcp_piece_wise():
+def test_models_pcp_dcp_piece_wise():
     prompts = [
         "The capital of France is", "Hello, my name is Tom, I am",
         "The president of United States is", "AI future is"
@@ -118,7 +116,6 @@ def test_pcp_dcp_piece_wise():
     model = "deepseek-ai/DeepSeek-V2-Lite-Chat"
     sampling_params = SamplingParams(max_tokens=32, temperature=0.0)
     with VllmRunner(model,
-                    enforce_eager=False,
                     max_model_len=1024,
                     tensor_parallel_size=2,
                     prefill_context_parallel_size=2,
@@ -130,7 +127,6 @@ def test_pcp_dcp_piece_wise():
 
     model = "vllm-ascend/Qwen3-30B-A3B-W8A8"
     with VllmRunner(model,
-                    enforce_eager=False,
                     max_model_len=1024,
                     tensor_parallel_size=2,
                     prefill_context_parallel_size=2,