64 lines
1.5 KiB
YAML
64 lines
1.5 KiB
YAML
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# ==========================================
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# Shared Configurations
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# ==========================================
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_envs: &envs
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OMP_NUM_THREADS: "1"
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OMP_PROC_BIND: "false"
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TASK_QUEUE_ENABLE: "1"
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HCCL_OP_EXPANSION_MODE: "AIV"
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VLLM_ASCEND_ENABLE_FLASHCOMM1: "1"
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PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
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VLLM_ASCEND_ENABLE_PREFETCH_MLP: "1"
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SERVER_PORT: "DEFAULT_PORT"
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_server_cmd: &server_cmd
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- "--quantization"
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- "ascend"
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- "--no-enable-prefix-caching"
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- "--mm-processor-cache-gb"
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- "0"
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- "--tensor-parallel-size"
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- "2"
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- "--port"
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- "$SERVER_PORT"
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- "--max-model-len"
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- "20000"
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- "--max-num-batched-tokens"
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- "8192"
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- "--trust-remote-code"
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- "--gpu-memory-utilization"
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- "0.9"
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- "--async-scheduling"
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_benchmarks: &benchmarks
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acc:
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case_type: accuracy
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dataset_path: vllm-ascend/textvqa-lite
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request_conf: vllm_api_stream_chat
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dataset_conf: textvqa/textvqa_gen_base64
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max_out_len: 2048
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batch_size: 128
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baseline: 80
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temperature: 0
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top_k: -1
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top_p: 1
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repetition_penalty: 1
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threshold: 5
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# ==========================================
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# ACTUAL TEST CASES
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# ==========================================
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test_cases:
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- name: "Qwen3-VL-32B-Instruct-W8A8"
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model: "Eco-Tech/Qwen3-VL-32B-Instruct-w8a8-QuaRot"
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envs:
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<<: *envs
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server_cmd: *server_cmd
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server_cmd_extra:
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- "--compilation_config"
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- '{"cudagraph_mode": "FULL_DECODE_ONLY", "cudagraph_capture_sizes": [1,12,16,20,24,32,48,64,68,72,76,80,128]}'
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benchmarks:
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<<: *benchmarks
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