[Test] add test for prefix cache feature of deepseek

.github/workflows/vllm_ascend_test_nightly_a3.yaml

@@ -65,6 +65,9 @@ jobs:
           - name: deepseek-r1-0528-w8a8
             os: linux-aarch64-a3-16
             tests: tests/e2e/nightly/models/test_deepseek_r1_0528_w8a8.py
+          - name: deepseek-r1-0528-w8a8-prefix-cache
+            os: linux-aarch64-a3-16
+            tests: tests/e2e/nightly/features/test_prefix_cache_deepseek_r1_0528_w8a8.py
     uses: ./.github/workflows/_e2e_nightly_single_node.yaml
     with:
       vllm: v0.11.0

tests/e2e/nightly/features/test_prefix_cache_deepseek_r1_0528_w8a8.py

@@ -0,0 +1,124 @@
+# 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 json
+
+import pytest
+from vllm.utils import get_open_port
+
+from tests.e2e.conftest import RemoteOpenAIServer
+from tools.aisbench import get_TTFT, run_aisbench_cases
+
+MODELS = [
+    "vllm-ascend/DeepSeek-R1-0528-W8A8",
+]
+
+aisbench_warm_up = [{
+    "case_type": "performance",
+    "dataset_path": "vllm-ascend/GSM8K-in1024-bs210",
+    "request_conf": "vllm_api_stream_chat",
+    "dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_str_perf",
+    "num_prompts": 210,
+    "max_out_len": 2,
+    "batch_size": 1000,
+    "baseline": 0,
+    "threshold": 0.97
+}]
+
+aisbench_cases0 = [{
+    "case_type": "performance",
+    "dataset_path": "vllm-ascend/prefix0-in3500-bs210",
+    "request_conf": "vllm_api_stream_chat",
+    "dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_str_perf",
+    "num_prompts": 210,
+    "max_out_len": 1500,
+    "batch_size": 18,
+    "baseline": 1,
+    "threshold": 0.97
+}]
+
+aisbench_cases75 = [{
+    "case_type": "performance",
+    "dataset_path": "vllm-ascend/prefix75-in3500-bs210",
+    "request_conf": "vllm_api_stream_chat",
+    "dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_str_perf",
+    "num_prompts": 210,
+    "max_out_len": 1500,
+    "batch_size": 18,
+    "baseline": 1,
+    "threshold": 0.97
+}]
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model", MODELS)
+async def test_models(model: str) -> None:
+    port = get_open_port()
+    env_dict = {
+        "OMP_NUM_THREADS": "10",
+        "OMP_PROC_BIND": "false",
+        "HCCL_BUFFSIZE": "1024",
+        "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+        "VLLM_USE_V1": "1"
+    }
+    additional_config = {
+        "ascend_scheduler_config": {
+            "enabled": False
+        },
+        "torchair_graph_config": {
+            "enabled": True,
+            "enable_multistream_moe": False,
+            "enable_multistream_mla": True,
+            "graph_batch_size": [16],
+            "use_cached_graph": True
+        },
+        "chunked_prefill_for_mla": True,
+        "enable_weight_nz_layout": True
+    }
+    speculative_config = {
+        "num_speculative_tokens": 1,
+        "method": "deepseek_mtp"
+    }
+    server_args = [
+        "--quantization", "ascend", "--data-parallel-size", "2",
+        "--tensor-parallel-size", "8", "--enable-expert-parallel", "--port",
+        str(port), "--seed", "1024", "--max-model-len", "5200",
+        "--max-num-batched-tokens", "4096", "--max-num-seqs", "16",
+        "--trust-remote-code", "--gpu-memory-utilization", "0.9",
+        "--additional-config",
+        json.dumps(additional_config), "--speculative-config",
+        json.dumps(speculative_config)
+    ]
+    with RemoteOpenAIServer(model,
+                            server_args,
+                            server_port=port,
+                            env_dict=env_dict,
+                            auto_port=False):
+        run_aisbench_cases(model, port, aisbench_warm_up)
+        result = run_aisbench_cases(model, port, aisbench_cases0)
+        TTFT0 = get_TTFT(result)
+    with RemoteOpenAIServer(model,
+                            server_args,
+                            server_port=port,
+                            env_dict=env_dict,
+                            auto_port=False):
+        run_aisbench_cases(model, port, aisbench_warm_up)
+        result = run_aisbench_cases(model, port, aisbench_cases75)
+        TTFT75 = get_TTFT(result)
+    assert TTFT75 < 0.8 * TTFT0, f"The TTFT for prefix75 {TTFT75} is not less than 0.8*TTFT for prefix0 {TTFT0}."
+    print(
+        f"The TTFT for prefix75 {TTFT75} is less than 0.8*TTFT for prefix0 {TTFT0}."
+    )