[5/N][CI/UT]add spec decode e2e UT && fix chunk prefill bug

Co-authored-by: mengwei805 <mengwei25@huawei.com>
Co-authored-by: XWFAlone <xuewenfei2@huawei.com>
Signed-off-by: mengwei805 <mengwei25@huawei.com>

Author: mengwei805

.github/workflows/vllm_ascend_test.yaml

@@ -148,8 +148,8 @@ jobs:
       - name: Run vllm-project/vllm-ascend key feature test
         if: steps.filter.outputs.speculative_tests_changed
         run: |
-          pytest -sv tests/spec_decode/e2e/test_mtp_correctness.py
-          pytest -sv tests/spec_decode --ignore=tests/spec_decode/e2e/test_mtp_correctness.py 
+          pytest -sv tests/spec_decode/e2e/test_mtp_correctness.py  # it needs a clean process
+          pytest -sv tests/spec_decode --ignore=tests/spec_decode/e2e/test_mtp_correctness.py
 
       - name: Run vllm-project/vllm test
         run: |

tests/spec_decode/e2e/test_eagle_correctness.py

@@ -350,13 +350,13 @@ def test_eagle_disable_queue(vllm_runner, common_llm_kwargs,
         "dtype": "float16",
 
         # Main model
-        "model_name": "meta-llama/Llama-2-7b-chat-hf"
+        "model_name": "vllm-ascend/Llama-2-7b-chat-hf"
     }])
 @pytest.mark.parametrize("per_test_common_llm_kwargs", [{}])
 @pytest.mark.parametrize("baseline_llm_kwargs", [{}])
 @pytest.mark.parametrize("test_llm_kwargs", [
     {
-        "speculative_model": "yuhuili/EAGLE-llama2-chat-7B",
+        "speculative_model": "vllm-ascend/EAGLE-llama2-chat-7B",
         "num_speculative_tokens": MAX_SPEC_TOKENS,
     },
 ])
@@ -368,21 +368,25 @@ def test_eagle_disable_queue(vllm_runner, common_llm_kwargs,
     ])
 @pytest.mark.parametrize("batch_size", [1, 5])
 @pytest.mark.parametrize("seed", [1])
-def test_llama2_eagle_e2e_greedy_correctness(vllm_runner, common_llm_kwargs,
+def test_llama2_eagle_e2e_greedy_correctness(monkeypatch: pytest.MonkeyPatch,
+                                             vllm_runner, common_llm_kwargs,
                                              per_test_common_llm_kwargs,
                                              baseline_llm_kwargs,
                                              test_llm_kwargs, batch_size: int,
                                              output_len: int, seed: int):
 
-    run_equality_correctness_test(vllm_runner,
-                                  common_llm_kwargs,
-                                  per_test_common_llm_kwargs,
-                                  baseline_llm_kwargs,
-                                  test_llm_kwargs,
-                                  batch_size,
-                                  output_len,
-                                  seed,
-                                  temperature=0.0)
+    # TODO: it is a wrong way to use modelscope.
+    with monkeypatch.context() as m:
+        m.setenv("VLLM_USE_MODELSCOPE", "True")
+        run_equality_correctness_test(vllm_runner,
+                                      common_llm_kwargs,
+                                      per_test_common_llm_kwargs,
+                                      baseline_llm_kwargs,
+                                      test_llm_kwargs,
+                                      batch_size,
+                                      output_len,
+                                      seed,
+                                      temperature=0.0)
 
 
 @pytest.mark.skipif(True, reason="Open it when CI could use modelscope")
@@ -399,13 +403,13 @@ def test_llama2_eagle_e2e_greedy_correctness(vllm_runner, common_llm_kwargs,
         "dtype": "float16",
 
         # Main model
-        "model_name": "meta-llama/Meta-Llama-3-8B-Instruct"
+        "model_name": "vllm-ascend/Meta-Llama-3-8B-Instruct"
     }])
 @pytest.mark.parametrize("per_test_common_llm_kwargs", [{}])
 @pytest.mark.parametrize("baseline_llm_kwargs", [{}])
 @pytest.mark.parametrize("test_llm_kwargs", [
     {
-        "speculative_model": "yuhuili/EAGLE-LLaMA3-Instruct-8B",
+        "speculative_model": "vllm-ascend/EAGLE-LLaMA3-Instruct-8B",
         "num_speculative_tokens": MAX_SPEC_TOKENS,
     },
 ])
@@ -417,21 +421,25 @@ def test_llama2_eagle_e2e_greedy_correctness(vllm_runner, common_llm_kwargs,
     ])
 @pytest.mark.parametrize("batch_size", [1, 5])
 @pytest.mark.parametrize("seed", [1])
-def test_llama3_eagle_e2e_greedy_correctness(vllm_runner, common_llm_kwargs,
+def test_llama3_eagle_e2e_greedy_correctness(monkeypatch: pytest.MonkeyPatch,
+                                             vllm_runner, common_llm_kwargs,
                                              per_test_common_llm_kwargs,
                                              baseline_llm_kwargs,
                                              test_llm_kwargs, batch_size: int,
                                              output_len: int, seed: int):
 
-    run_equality_correctness_test(vllm_runner,
-                                  common_llm_kwargs,
-                                  per_test_common_llm_kwargs,
-                                  baseline_llm_kwargs,
-                                  test_llm_kwargs,
-                                  batch_size,
-                                  output_len,
-                                  seed,
-                                  temperature=0.0)
+    # TODO: it is a wrong way to use modelscope.
+    with monkeypatch.context() as m:
+        m.setenv("VLLM_USE_MODELSCOPE", "True")
+        run_equality_correctness_test(vllm_runner,
+                                      common_llm_kwargs,
+                                      per_test_common_llm_kwargs,
+                                      baseline_llm_kwargs,
+                                      test_llm_kwargs,
+                                      batch_size,
+                                      output_len,
+                                      seed,
+                                      temperature=0.0)
 
 
 @pytest.mark.parametrize(