c95c271538
### What this PR does / why we need it?
Optimize nightly testcase.
Changes:
- tests/e2e/nightly/multi_node/config/models/Qwen3-235B-A3B.yaml: Add
accuracy and performance benchmark
- tests/e2e/models/configs/Qwen3-8B-Base.yaml: Delete
- tests/e2e/models/configs/internlm-7b.yaml: Change to
internlm3-8b-instruct
- tests/e2e/nightly/models/test_deepseek_r1_w8a8_eplb.py: Change to
DeepSeek-R1-0528-W8A8 model
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: menogrey <1299267905@qq.com>
71 lines
1.9 KiB
YAML
71 lines
1.9 KiB
YAML
test_name: "test Qwen3-235B-A22B multi-dp"
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model: "Qwen/Qwen3-235B-A22B"
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num_nodes: 2
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npu_per_node: 16
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env_common:
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VLLM_USE_MODELSCOPE: true
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OMP_PROC_BIND: false
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OMP_NUM_THREADS: 100
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HCCL_BUFFSIZE: 1024
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SERVER_PORT: 8080
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NUMEXPR_MAX_THREADS: 128
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deployment:
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-
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server_cmd: >
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vllm serve "Qwen/Qwen3-235B-A22B"
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--host 0.0.0.0
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--port $SERVER_PORT
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--data-parallel-size 4
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--data-parallel-size-local 2
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--data-parallel-address $LOCAL_IP
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--data-parallel-rpc-port 13389
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--tensor-parallel-size 8
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--seed 1024
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--enable-expert-parallel
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--max-num-seqs 32
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--max-model-len 8192
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--max-num-batched-tokens 8192
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--trust-remote-code
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--no-enable-prefix-caching
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--gpu-memory-utilization 0.9
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-
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server_cmd: >
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vllm serve "Qwen/Qwen3-235B-A22B"
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--headless
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--data-parallel-size 4
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--data-parallel-size-local 2
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--data-parallel-start-rank 2
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--data-parallel-address $MASTER_IP
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--data-parallel-rpc-port 13389
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--tensor-parallel-size 8
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--seed 1024
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--max-num-seqs 32
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--max-model-len 8192
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--max-num-batched-tokens 8192
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--enable-expert-parallel
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--trust-remote-code
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--no-enable-prefix-caching
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--gpu-memory-utilization 0.9
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benchmarks:
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perf:
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case_type: performance
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dataset_path: vllm-ascend/GSM8K-in3500-bs2800
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request_conf: vllm_api_stream_chat
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dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_str_perf
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num_prompts: 2800
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max_out_len: 1500
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batch_size: 700
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request_rate: 11.2
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baseline: 1
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threshold: 0.97
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acc:
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case_type: accuracy
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dataset_path: vllm-ascend/gsm8k
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request_conf: vllm_api_general_chat
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dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_chat_prompt
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max_out_len: 7680
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batch_size: 512
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baseline: 95
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threshold: 3
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