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xc-llm-ascend/tests/e2e/nightly/single_node/models/configs/Prefix-Cache-DeepSeek-R1-0528-W8A8.yaml

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[Nightly][Refactor]Migrate nightly single-node model tests from `.py` to `.yaml` (#6503) ### What this PR does / why we need it? This PR refactors the nightly single-node model test by migrating test configurations from Python scripts to a more maintainable `YAML-based` format. | Original PR | Python (`.py`) | YAML (`.yaml`) | | :--- | :--- | :--- | | [#3568](https://github.com/vllm-project/vllm-ascend/pull/3568) | `test_deepseek_r1_0528_w8a8_eplb.py` | `DeepSeek-R1-0528-W8A8.yaml` | | [#3631](https://github.com/vllm-project/vllm-ascend/pull/3631) | `test_deepseek_r1_0528_w8a8.py` | `DeepSeek-R1-0528-W8A8.yaml` | | [#5874](https://github.com/vllm-project/vllm-ascend/pull/5874) | `test_deepseek_r1_w8a8_hbm.py` | `DeepSeek-R1-W8A8-HBM.yaml` | | [#3908](https://github.com/vllm-project/vllm-ascend/pull/3908) | `test_deepseek_v3_2_w8a8.py` | `DeepSeek-V3.2-W8A8.yaml` | | [#5682](https://github.com/vllm-project/vllm-ascend/pull/5682) | `test_kimi_k2_thinking.py` | `Kimi-K2-Thinking.yaml` | | [#4111](https://github.com/vllm-project/vllm-ascend/pull/4111) | `test_mtpx_deepseek_r1_0528_w8a8.py` | `MTPX-DeepSeek-R1-0528-W8A8.yaml` | | [#3733](https://github.com/vllm-project/vllm-ascend/pull/3733) | `test_prefix_cache_deepseek_r1_0528_w8a8.py` | `Prefix-Cache-DeepSeek-R1-0528-W8A8.yaml` | | [#6543](https://github.com/vllm-project/vllm-ascend/pull/6543) | `test_qwen3_235b_w8a8.py` | `Qwen3-235B-A22B-W8A8.yaml` | | [#6543](https://github.com/vllm-project/vllm-ascend/pull/6543) | `test_qwen3_235b_a22b_w8a8_eplb.py` | `Qwen3-235B-A22B-W8A8.yaml` | | [#3973](https://github.com/vllm-project/vllm-ascend/pull/3973) | `test_qwen3_30b_w8a8.py` | `Qwen3-30B-A3B-W8A8.yaml` | | [#3541](https://github.com/vllm-project/vllm-ascend/pull/3541) | `test_qwen3_32b_int8.py` | `Qwen3-32B-Int8.yaml` | | [#3757](https://github.com/vllm-project/vllm-ascend/pull/3757) | `test_qwq_32b.py` | `QwQ-32B.yaml` | | [#5616](https://github.com/vllm-project/vllm-ascend/pull/5616) | `test_qwen3_next_w8a8.py` | `Qwen3-Next-80B-A3B-Instruct-W8A8.yaml` | | [#3541](https://github.com/vllm-project/vllm-ascend/pull/3541) | `test_qwen2_5_vl_7b.py` | `Qwen2.5-VL-7B-Instruct.yaml` | | [#5301](https://github.com/vllm-project/vllm-ascend/pull/5301) | `test_qwen2_5_vl_7b_epd.py` | `Qwen2.5-VL-7B-Instruct-EPD.yaml` | | [#3707](https://github.com/vllm-project/vllm-ascend/pull/3707) | `test_qwen2_5_vl_32b.py` | `Qwen2.5-VL-32B-Instruct.yaml` | | [#3676](https://github.com/vllm-project/vllm-ascend/pull/3676) | `test_qwen3_32b_int8_a3_feature_stack3.py` | `Qwen3-32B-Int8-A3-Feature-Stack3.yaml` | | [#3709](https://github.com/vllm-project/vllm-ascend/pull/3709) | `test_prefix_cache_qwen3_32b_int8.py` | `Prefix-Cache-Qwen3-32B-Int8.yaml` | | [#5395](https://github.com/vllm-project/vllm-ascend/pull/5395) | `test_qwen3_next.py` | `Qwen3-Next-80B-A3B-Instruct-A2.yaml` | | [#3474](https://github.com/vllm-project/vllm-ascend/pull/3474) | `test_qwen3_32b.py` | `Qwen3-32B.yaml` | | [#3541](https://github.com/vllm-project/vllm-ascend/pull/3541) | `test_qwen3_32b_int8.py` | `Qwen3-32B-Int8-A2.yaml` | ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.15.0 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.15.0 --------- Signed-off-by: MrZ20 <2609716663@qq.com>
2026-03-03 20:13:43 +08:00
# ==========================================
# ACTUAL TEST CASES
# ==========================================
test_cases:
- name: "prefix-cache-deepseek-r1-0528-w8a8"
model: "vllm-ascend/DeepSeek-R1-0528-W8A8"
envs:
OMP_NUM_THREADS: "10"
OMP_PROC_BIND: "false"
HCCL_BUFFSIZE: "1024"
PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
SERVER_PORT: "DEFAULT_PORT"
server_cmd:
- "--quantization"
- "ascend"
- "--data-parallel-size"
- "2"
- "--tensor-parallel-size"
- "8"
- "--enable-expert-parallel"
- "--port"
- "$SERVER_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"
- '{"enable_weight_nz_layout": true}'
- "--speculative-config"
- '{"num_speculative_tokens": 1, "method": "mtp"}'
test_content:
- "benchmark_comparisons"
benchmark_comparisons_args:
- metric: "TTFT"
baseline: "prefix0"
target: "prefix75"
ratio: 0.8
operator: "<"
benchmarks:
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
prefix0:
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
prefix75:
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
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