[v0.18.0][CI] Fix and simplify the CI for Qwen3 32B (#8093)
### What this PR does / why we need it? This PR fixes and simplifies the CI configuration for Qwen3 32B. The main changes are: - Remove the redundant `Qwen3-32B-Int8-A3-Feature-Stack3.yaml` config and consolidate the CI setup into `Qwen3-32B-Int8.yaml`. - Improve runtime stability by adding `PYTORCH_NPU_ALLOC_CONF=expandable_segments:True` and setting `--max-num-seqs 80`. - Update the accuracy benchmark from `aime2024` to `gsm8k-lite`, and adjust the related dataset config, output length, baseline, and threshold accordingly. These changes make the Qwen3 32B CI easier to maintain and more stable in nightly validation. --------- Signed-off-by: ZYang6263 <zy626375@gmail.com>
This commit is contained in:
@@ -214,9 +214,6 @@ jobs:
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- name: qwen2-5-vl-32b
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- name: qwen2-5-vl-32b
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os: linux-aarch64-a3-4
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os: linux-aarch64-a3-4
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config_file_path: Qwen2.5-VL-32B-Instruct.yaml
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config_file_path: Qwen2.5-VL-32B-Instruct.yaml
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- name: qwen3-32b-int8-a3-feature-stack3
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os: linux-aarch64-a3-4
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config_file_path: Qwen3-32B-Int8-A3-Feature-Stack3.yaml
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- name: qwen3-32b-int8-prefix-cache
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- name: qwen3-32b-int8-prefix-cache
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os: linux-aarch64-a3-4
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os: linux-aarch64-a3-4
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config_file_path: Prefix-Cache-Qwen3-32B-Int8.yaml
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config_file_path: Prefix-Cache-Qwen3-32B-Int8.yaml
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@@ -1,69 +0,0 @@
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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: "Qwen3-32B-W8A8-a3-feature-stack3"
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model: "vllm-ascend/Qwen3-32B-W8A8"
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envs:
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VLLM_USE: "1"
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TASK_QUEUE_ENABLE: "1"
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HCCL_OP_EXPANSION_MODE: "AIV"
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OMP_PROC_BIND: "false"
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VLLM_ASCEND_ENABLE_TOPK_OPTIMIZE: "1"
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VLLM_ASCEND_ENABLE_FLASHCOMM: "1"
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SERVER_PORT: "DEFAULT_PORT"
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prompts:
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- "9.11 and 9.8, which is greater?"
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api_keyword_args:
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chat_template_kwargs:
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enable_thinking: true
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server_cmd:
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- "--quantization"
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- "ascend"
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- "--tensor-parallel-size"
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- "4"
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- "--port"
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- "$SERVER_PORT"
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- "--trust-remote-code"
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- "--reasoning-parser"
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- "qwen3"
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- "--distributed_executor_backend"
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- "mp"
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- "--gpu-memory-utilization"
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- "0.9"
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- "--block-size"
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- "128"
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- "--max-num-seqs"
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- "256"
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- "--enforce-eager"
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- "--max-model-len"
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- "35840"
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- "--max-num-batched-tokens"
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- "35840"
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- "--additional-config"
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- '{"enable_weight_nz_layout":true, "weight_prefetch_config":{"enabled": true}}'
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- "--compilation-config"
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- '{"cudagraph_mode":"FULL_DECODE_ONLY", "cudagraph_capture_sizes":[1,8,24,48,60]}'
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test_content:
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- "chat_completion"
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benchmarks:
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acc:
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case_type: accuracy
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dataset_path: vllm-ascend/gsm8k-lite
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request_conf: vllm_api_general_chat
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dataset_conf: gsm8k/gsm8k_gen_0_shot_noncot_chat_prompt
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max_out_len: 10240
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batch_size: 32
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baseline: 96
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threshold: 4
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perf:
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case_type: performance
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dataset_path: vllm-ascend/GSM8K-in3500-bs400
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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: 240
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max_out_len: 1500
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batch_size: 60
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baseline: 1
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threshold: 0.97
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@@ -4,6 +4,7 @@
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_envs: &envs
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_envs: &envs
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TASK_QUEUE_ENABLE: "1"
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TASK_QUEUE_ENABLE: "1"
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PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
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HCCL_OP_EXPANSION_MODE: "AIV"
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HCCL_OP_EXPANSION_MODE: "AIV"
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VLLM_ASCEND_ENABLE_FLASHCOMM: "1"
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VLLM_ASCEND_ENABLE_FLASHCOMM: "1"
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SERVER_PORT: "DEFAULT_PORT"
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SERVER_PORT: "DEFAULT_PORT"
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@@ -14,6 +15,8 @@ _server_cmd: &server_cmd
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- "--no-enable-prefix-caching"
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- "--no-enable-prefix-caching"
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- "--tensor-parallel-size"
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- "--tensor-parallel-size"
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- "4"
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- "4"
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- "--max-num-seqs"
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- "80"
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- "--port"
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- "--port"
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- "$SERVER_PORT"
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- "$SERVER_PORT"
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- "--max-model-len"
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- "--max-model-len"
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@@ -23,8 +26,6 @@ _server_cmd: &server_cmd
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- "--block-size"
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- "--block-size"
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- "128"
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- "128"
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- "--trust-remote-code"
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- "--trust-remote-code"
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- "--reasoning-parser"
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- "qwen3"
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- "--gpu-memory-utilization"
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- "--gpu-memory-utilization"
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- "0.9"
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- "0.9"
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- "--async-scheduling"
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- "--async-scheduling"
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@@ -34,23 +35,23 @@ _server_cmd: &server_cmd
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_benchmarks: &benchmarks
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_benchmarks: &benchmarks
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acc:
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acc:
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case_type: accuracy
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case_type: accuracy
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dataset_path: vllm-ascend/aime2024
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dataset_path: vllm-ascend/gsm8k-lite
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request_conf: vllm_api_general_chat
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request_conf: vllm_api_general_chat
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dataset_conf: aime2024/aime2024_gen_0_shot_chat_prompt
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dataset_conf: gsm8k/gsm8k_gen_0_shot_noncot_chat_prompt
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max_out_len: 32768
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max_out_len: 10240
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batch_size: 32
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batch_size: 32
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baseline: 83.33
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baseline: 96
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threshold: 7
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threshold: 4
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perf:
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perf:
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case_type: performance
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case_type: performance
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dataset_path: vllm-ascend/GSM8K-in3500-bs400
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dataset_path: vllm-ascend/GSM8K-in3500-bs400
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request_conf: vllm_api_stream_chat
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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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dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_str_perf
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num_prompts: 304
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num_prompts: 304
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max_out_len: 1500
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max_out_len: 1500
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batch_size: 76
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batch_size: 76
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baseline: 1
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baseline: 1
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threshold: 0.97
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threshold: 0.97
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# ==========================================
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# ==========================================
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# ACTUAL TEST CASES
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# ACTUAL TEST CASES
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