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[CI] migrate ascend-gptq from test/srt to test/registered (#19628)

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This commit is contained in:
SoluMilken
2026-03-14 15:28:57 +08:00
committed by GitHub
parent f9e4221b71
commit c95dc88f86
6 changed files with 115 additions and 236 deletions
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13
.github/workflows/pr-test-npu.yml vendored
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@@ -110,6 +110,19 @@ jobs:
# copy download through proxy
curl -o /tmp/test.jsonl -L https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.jsonl
- name: Run registered test
timeout-minutes: 240
env:
SGLANG_USE_MODELSCOPE: true
SGLANG_IS_IN_CI: true
HF_ENDPOINT: https://hf-mirror.com
TORCH_EXTENSIONS_DIR: /tmp/torch_extensions
PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
STREAMS_PER_DEVICE: 32
run: |
cd test
python3 run_suite.py --hw npu --suite per-commit-1-npu-a2 --continue-on-error --timeout-per-file 3600 --auto-partition-id ${{ matrix.part }} --auto-partition-size 2
- name: Run test
timeout-minutes: 60
env:

228
python/sglang/test/ascend/test_ascend_utils.py
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@@ -1,4 +1,15 @@
"""Common utilities for testing and benchmarking on NPU"""
"""
Common utilities for testing and benchmarking on NPU.
This file contains the following weight path categories:
- LLM model weights path
- VLM model weights path
- Embedding model weights path
- Rerank model weights path
- Reward model weights path
Please remember to sort by variable name within each section.
"""
import os
@@ -6,196 +17,93 @@ import os
MODEL_WEIGHTS_DIR = "/root/.cache/modelscope/hub/models/"
HF_MODEL_WEIGHTS_DIR = "/root/.cache/huggingface/hub/"
# fmt: off
# ruff: noqa: E501
# LLM model weights path
LLAMA_3_1_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "AI-ModelScope/Llama-3.1-8B-Instruct"
)
LLAMA_3_2_1B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "LLM-Research/Llama-3.2-1B")
LLAMA_3_2_1B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "LLM-Research/Llama-3.2-1B-Instruct"
)
LLAMA_3_2_1B_INSTRUCT_TOOL_CALLING_LORA_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "codelion/Llama-3.2-1B-Instruct-tool-calling-lora"
)
META_LLAMA_3_1_8B_INSTRUCT = os.path.join(
MODEL_WEIGHTS_DIR, "LLM-Research/Meta-Llama-3.1-8B-Instruct"
)
DEEPSEEK_R1_0528_W8A8_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "vllm-ascend/DeepSeek-R1-0528-W8A8"
)
DEEPSEEK_V2_LITE_W8A8_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "vllm-ascend/DeepSeek-V2-Lite-W8A8"
)
QWEN2_5_7B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-7B-Instruct"
)
AFM_4_5B_BASE_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "arcee-ai/AFM-4.5B-Base")
BAICHUAN2_13B_CHAT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "baichuan-inc/Baichuan2-13B-Chat"
)
C4AI_COMMAND_R_V01_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "CohereForAI/c4ai-command-r-v01"
)
BAICHUAN2_13B_CHAT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "baichuan-inc/Baichuan2-13B-Chat")
C4AI_COMMAND_R_V01_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "CohereForAI/c4ai-command-r-v01")
CHATGLM2_6B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "ZhipuAI/chatglm2-6b")
DBRX_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "AI-ModelScope/dbrx-instruct"
)
DEEPSEEK_V3_2_EXP_W8A8_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "DeepSeek-V3.2-Exp-W8A8"
)
ERNIE_4_5_21B_A3B_PT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "baidu/ERNIE-4.5-21B-A3B-PT"
)
EXAONE_3_5_7_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct"
)
DBRX_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "AI-ModelScope/dbrx-instruct")
DEEPSEEK_R1_0528_W4A8_PER_CHANNEL_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "DeepSeek-R1-0528-w4a8-per-channel")
DEEPSEEK_R1_0528_W8A8_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "vllm-ascend/DeepSeek-R1-0528-W8A8")
DEEPSEEK_V2_LITE_W8A8_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "vllm-ascend/DeepSeek-V2-Lite-W8A8")
DEEPSEEK_V3_2_EXP_W8A8_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "DeepSeek-V3.2-Exp-W8A8")
EAGLE3_LLAMA3_1_INSTRUCT_8B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "sglang-EAGLE3-LLaMA3.1-Instruct-8B")
ERNIE_4_5_21B_A3B_PT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "baidu/ERNIE-4.5-21B-A3B-PT")
EXAONE_3_5_7_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct")
GEMMA_3_4B_IT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "google/gemma-3-4b-it")
GLM_4_9B_CHAT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "ZhipuAI/glm-4-9b-chat")
GRANITE_3_0_3B_A800M_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "ibm-granite/granite-3.0-3b-a800m-instruct"
)
GRANITE_3_1_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "ibm-granite/granite-3.1-8b-instruct"
)
GRANITE_3_0_3B_A800M_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "ibm-granite/granite-3.0-3b-a800m-instruct")
GRANITE_3_1_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "ibm-granite/granite-3.1-8b-instruct")
GROK_2_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "huihui-ai/grok-2")
INTERNLM2_7B_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Shanghai_AI_Laboratory/internlm2-7b"
)
INTERNLM2_7B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Shanghai_AI_Laboratory/internlm2-7b")
KIMI_K2_THINKING_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Kimi/Kimi-K2-Thinking")
LING_LITE_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "inclusionAI/Ling-lite")
LLAMA_4_SCOUT_17B_16E_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "meta-llama/Llama-4-Scout-17B-16E-Instruct"
)
LLAMA_2_7B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "LLM-Research/Llama-2-7B")
LLAMA_3_1_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "AI-ModelScope/Llama-3.1-8B-Instruct")
LLAMA_3_2_1B_INSTRUCT_TOOL_CALLING_LORA_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "codelion/Llama-3.2-1B-Instruct-tool-calling-lora")
LLAMA_3_2_1B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "LLM-Research/Llama-3.2-1B-Instruct")
LLAMA_3_2_1B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "LLM-Research/Llama-3.2-1B")
LLAMA_4_SCOUT_17B_16E_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "meta-llama/Llama-4-Scout-17B-16E-Instruct")
META_LLAMA_3_1_8B_INSTRUCT = os.path.join(MODEL_WEIGHTS_DIR, "LLM-Research/Meta-Llama-3.1-8B-Instruct")
MIMO_7B_RL_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "XiaomiMiMo/MiMo-7B-RL")
MINICPM3_4B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "OpenBMB/MiniCPM3-4B")
MISTRAL_7B_INSTRUCT_V0_2_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "mistralai/Mistral-7B-Instruct-v0.2"
)
OLMOE_1B_7B_0924_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "allenai/OLMoE-1B-7B-0924"
)
PERSIMMON_8B_CHAT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Howeee/persimmon-8b-chat"
)
PHI_4_MULTIMODAL_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "microsoft/Phi-4-multimodal-instruct"
)
MISTRAL_7B_INSTRUCT_V0_2_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "mistralai/Mistral-7B-Instruct-v0.2")
OLMOE_1B_7B_0924_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "allenai/OLMoE-1B-7B-0924")
PERSIMMON_8B_CHAT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Howeee/persimmon-8b-chat")
PHI_4_MULTIMODAL_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "microsoft/Phi-4-multimodal-instruct")
QWEN2_5_7B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-7B-Instruct")
QWEN3_0_6B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-0.6B")
Qwen3_30B_A3B_Instruct_2507_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen3-30B-A3B-Instruct-2507"
)
QWEN3_1_7B_GPTQ_INT8_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-1.7B-GPTQ-Int8")
QWEN3_235B_A22B_W8A8_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "vllm-ascend/Qwen3-235B-A22B-W8A8")
QWEN3_30B_A3B_INSTRUCT_2507_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-30B-A3B-Instruct-2507")
QWEN3_32B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-32B")
QWEN3_235B_A22B_W8A8_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "vllm-ascend/Qwen3-235B-A22B-W8A8"
)
QWEN3_CODER_480B_A35B_INSTRUCT_W8A8_QUAROT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen3-Coder-480B-A35B-Instruct-w8a8-QuaRot"
)
QWEN3_NEXT_80B_A3B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen3-Next-80B-A3B-Instruct"
)
QWEN3_CODER_480B_A35B_INSTRUCT_W8A8_QUAROT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen3-Coder-480B-A35B-Instruct-w8a8-QuaRot")
QWEN3_NEXT_80B_A3B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-Next-80B-A3B-Instruct")
QWQ_32B_W8A8_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "vllm-ascend/QWQ-32B-W8A8")
SMOLLM_1_7B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "HuggingFaceTB/SmolLM-1.7B")
STABLELM_2_1_6B_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "stabilityai/stablelm-2-1_6b"
)
STABLELM_2_1_6B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "stabilityai/stablelm-2-1_6b")
XVERSE_MOE_A36B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "xverse/XVERSE-MoE-A36B")
EAGLE3_LLAMA3_1_INSTRUCT_8B_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "sglang-EAGLE3-LLaMA3.1-Instruct-8B"
)
DEEPSEEK_R1_0528_W4A8_PER_CHANNEL_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "DeepSeek-R1-0528-w4a8-per-channel"
)
# VLM model weights path
DEEPSEEK_VL2_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "deepseek-ai/deepseek-vl2")
GLM_4_5V_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "ZhipuAI/GLM-4.5V")
JANUS_PRO_1B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "deepseek-ai/Janus-Pro-1B")
JANUS_PRO_7B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "deepseek-ai/Janus-Pro-7B")
KIMI_VL_A3B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Kimi/Kimi-VL-A3B-Instruct"
)
LLAMA_3_2_11B_VISION_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "LLM-Research/Llama-3.2-11B-Vision-Instruct"
)
KIMI_VL_A3B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Kimi/Kimi-VL-A3B-Instruct")
LLAMA_3_2_11B_VISION_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "LLM-Research/Llama-3.2-11B-Vision-Instruct")
LLAVA_NEXT_72B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "lmms-lab/llava-next-72b")
LLAVA_ONEVISION_QWEN2_7B_OV_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "lmms-lab/llava-onevision-qwen2-7b-ov"
)
LLAVA_V1_6_34B_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "AI-ModelScope/llava-v1.6-34b"
)
LLAVA_ONEVISION_QWEN2_7B_OV_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "lmms-lab/llava-onevision-qwen2-7b-ov")
LLAVA_V1_6_34B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "AI-ModelScope/llava-v1.6-34b")
MIMO_VL_7B_RL_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "XiaomiMiMo/MiMo-VL-7B-RL")
MINICPM_O_2_6_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "openbmb/MiniCPM-o-2_6")
MINICPM_V_2_6_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "openbmb/MiniCPM-V-2_6")
MISTRAL_SMALL_3_1_24B_INSTRUCT_2503_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "mistralai/Mistral-Small-3.1-24B-Instruct-2503"
)
QWEN2_5_VL_3B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-VL-3B-Instruct"
)
QWEN2_5_VL_72B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-VL-72B-Instruct"
)
QWEN3_VL_4B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-4B-Instruct"
)
QWEN3_VL_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-8B-Instruct"
)
QWEN3_VL_30B_A3B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-30B-A3B-Instruct"
)
QWEN3_VL_235B_A22B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-235B-A22B-Instruct"
)
MISTRAL_SMALL_3_1_24B_INSTRUCT_2503_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "mistralai/Mistral-Small-3.1-24B-Instruct-2503")
QWEN2_5_VL_3B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-VL-3B-Instruct")
QWEN2_5_VL_72B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-VL-72B-Instruct")
QWEN3_30B_A3B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-30B-A3B")
QWEN3_30B_MODELSLIM_INT4_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Eco-Tech/Qwen3-30B-A3B-w4a4-LAOS"
)
QWEN3_30B_MODELSLIM_INT4_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Eco-Tech/Qwen3-30B-A3B-w4a4-LAOS")
QWEN3_VL_235B_A22B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-235B-A22B-Instruct")
QWEN3_VL_30B_A3B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-30B-A3B-Instruct")
QWEN3_VL_4B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-4B-Instruct")
QWEN3_VL_8B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-VL-8B-Instruct")
# Embedding model weights path
BGE_LARGE_EN_V1_5_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "bge-large-en-v1.5")
CLIP_VIT_LARGE_PATCH14_336_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "AI-ModelScope/clip-vit-large-patch14-336"
)
E5_MISTRAL_7B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "intfloat/e5-mistral-7b-instruct"
)
GME_QWEN2_VL_2B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Alibaba-NLP/gme-Qwen2-VL-2B-Instruct"
)
GTE_QWEN2_1_5B_INSTRUCT_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "iic/gte_Qwen2-1.5B-instruct"
)
QWEN3_EMBEDDING_8B_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen3-Embedding-8B"
)
CLIP_VIT_LARGE_PATCH14_336_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "AI-ModelScope/clip-vit-large-patch14-336")
E5_MISTRAL_7B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "intfloat/e5-mistral-7b-instruct")
GME_QWEN2_VL_2B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Alibaba-NLP/gme-Qwen2-VL-2B-Instruct")
GTE_QWEN2_1_5B_INSTRUCT_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "iic/gte_Qwen2-1.5B-instruct")
QWEN3_EMBEDDING_8B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen3-Embedding-8B")
# Rerank model weights path
BGE_RERANKER_V2_M3_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "BAAI/bge-reranker-v2-m3"
)
BGE_RERANKER_V2_M3_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "BAAI/bge-reranker-v2-m3")
# Reward model weights path
SKYWORK_REWARD_GEMMA_2_27B_V0_2_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "AI-ModelScope/Skywork-Reward-Gemma-2-27B-v0.2"
)
INTERNLM2_7B_REWARD_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Shanghai_AI_Laboratory/internlm2-7b-reward"
)
SKYWORK_REWARD_LLAMA_3_1_8B_V0_2_WEIGHTS_PATH = os.path.join(
HF_MODEL_WEIGHTS_DIR,
"models--Skywork--Skywork-Reward-Llama-3.1-8B-v0.2/snapshots/d4117fbfd81b72f41b96341238baa1e3e90a4ce1",
)
QWEN2_5_1_5B_APEACH_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Howeee/Qwen2.5-1.5B-apeach"
)
QWEN2_5_MATH_RM_72B_WEIGHTS_PATH = os.path.join(
MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-Math-RM-72B"
)
INTERNLM2_7B_REWARD_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Shanghai_AI_Laboratory/internlm2-7b-reward")
QWEN2_5_1_5B_APEACH_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Howeee/Qwen2.5-1.5B-apeach")
QWEN2_5_MATH_RM_72B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "Qwen/Qwen2.5-Math-RM-72B")
SKYWORK_REWARD_GEMMA_2_27B_V0_2_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "AI-ModelScope/Skywork-Reward-Gemma-2-27B-v0.2")
SKYWORK_REWARD_LLAMA_3_1_8B_V0_2_WEIGHTS_PATH = os.path.join(HF_MODEL_WEIGHTS_DIR, "models--Skywork--Skywork-Reward-Llama-3.1-8B-v0.2/snapshots/d4117fbfd81b72f41b96341238baa1e3e90a4ce1")
# fmt: on

32
test/registered/ascend/llm_models/test_ascend_qwen3_1_7b_gptq_int8.py Normal file
View File

@@ -0,0 +1,32 @@
import unittest
from sglang.test.ascend.gsm8k_ascend_mixin import GSM8KAscendMixin
from sglang.test.ascend.test_ascend_utils import QWEN3_1_7B_GPTQ_INT8_WEIGHTS_PATH
from sglang.test.ci.ci_register import register_npu_ci
from sglang.test.test_utils import CustomTestCase
register_npu_ci(est_time=400, suite="per-commit-1-npu-a2")
class TestQwen317BGPTQInt8(GSM8KAscendMixin, CustomTestCase):
"""Testcase: Verify that the inference accuracy of the Qwen/Qwen3-1.7B-GPTQ-Int8 model on the GSM8K dataset is no less than 0.65.
[Test Category] Model
[Test Target] Qwen/Qwen3-1.7B-GPTQ-Int8
"""
model = QWEN3_1_7B_GPTQ_INT8_WEIGHTS_PATH
accuracy = 0.65
other_args = [
"--trust-remote-code",
"--mem-fraction-static",
"0.8",
"--attention-backend",
"ascend",
"--quantization",
"gptq",
]
if __name__ == "__main__":
unittest.main()

4
test/registered/ascend/llm_models/test_ascend_qwen3_30b.py
View File

@@ -2,7 +2,7 @@ import unittest
from sglang.test.ascend.gsm8k_ascend_mixin import GSM8KAscendMixin
from sglang.test.ascend.test_ascend_utils import (
Qwen3_30B_A3B_Instruct_2507_WEIGHTS_PATH,
QWEN3_30B_A3B_INSTRUCT_2507_WEIGHTS_PATH,
)
from sglang.test.ci.ci_register import register_npu_ci
from sglang.test.test_utils import CustomTestCase
@@ -17,7 +17,7 @@ class TestQwen330B(GSM8KAscendMixin, CustomTestCase):
[Test Target] Qwen/Qwen3-30B-A3B-Instruct-2507
"""
model = Qwen3_30B_A3B_Instruct_2507_WEIGHTS_PATH
model = QWEN3_30B_A3B_INSTRUCT_2507_WEIGHTS_PATH
accuracy = 0.90
other_args = [
"--trust-remote-code",

73
test/srt/ascend/test_ascend_gptq.py
View File

@@ -1,73 +0,0 @@
import unittest
from types import SimpleNamespace
from urllib.parse import urlparse
from sglang.srt.utils import kill_process_tree
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
from sglang.test.test_utils import (
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
popen_launch_server,
)
TEST_MODEL_MATRIX = {
"Qwen/Qwen3-1.7B-GPTQ-Int8": {
"accuracy": 0.65,
},
}
class TestAscendGPTQInt8(CustomTestCase):
@classmethod
def setUpClass(cls):
cls.models = TEST_MODEL_MATRIX.keys()
cls.base_url = DEFAULT_URL_FOR_TEST
cls.url = urlparse(DEFAULT_URL_FOR_TEST)
cls.common_args = [
"--trust-remote-code",
"--mem-fraction-static",
0.8,
"--attention-backend",
"ascend",
"--quantization",
"gptq",
]
def test_a_gsm8k(self):
for model in self.models:
with self.subTest(model=model):
print(f"##=== Testing accuracy: {model} ===##")
process = popen_launch_server(
model,
self.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
*self.common_args,
],
)
try:
args = SimpleNamespace(
num_shots=5,
data_path=None,
num_questions=1319,
max_new_tokens=512,
parallel=128,
host=f"http://{self.url.hostname}",
port=int(self.url.port),
)
metrics = run_eval_few_shot_gsm8k(args)
self.assertGreaterEqual(
metrics["accuracy"],
TEST_MODEL_MATRIX[model]["accuracy"],
)
finally:
kill_process_tree(process.pid)
if __name__ == "__main__":
unittest.main()

1
test/srt/run_suite.py
View File

@@ -85,7 +85,6 @@ suite_ascend = {
"per-commit-1-npu-a2": [
TestFile("ascend/test_ascend_autoround_dense.py", 400),
TestFile("ascend/test_ascend_autoround_moe.py", 400),
TestFile("ascend/test_ascend_gptq.py", 400),
TestFile("ascend/test_ascend_gptq_moe.py", 400),
TestFile("ascend/test_ascend_graph_tp1_bf16.py", 400),
TestFile("ascend/test_ascend_piecewise_graph_prefill.py", 400),