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sglang/test/registered/models_e2e/test_vlm_models.py
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Python

import random
import tempfile
import unittest
from types import SimpleNamespace
from sglang.srt.utils import is_hip
from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
from sglang.test.kits.mmmu_vlm_kit import (
MMMUMultiModelTestBase,
)
from sglang.test.test_utils import is_in_amd_ci, is_in_ci
# VLM (Vision Language Model) tests
register_cuda_ci(est_time=317, stage="extra-a", runner_config="1-gpu-large")
register_amd_ci(est_time=850, suite="stage-b-test-1-gpu-small-amd-nondeterministic")
_is_hip = is_hip()
# VLM models for testing
if _is_hip:
MODELS = [
# SimpleNamespace(model="openbmb/MiniCPM-V-2_6", mmmu_accuracy=0.4), # temporarily disabled: NaN in next_token_logits
SimpleNamespace(model="Qwen/Qwen2.5-VL-3B-Instruct", mmmu_accuracy=0.4),
]
else:
MODELS = [
SimpleNamespace(model="google/gemma-3-4b-it", mmmu_accuracy=0.38),
SimpleNamespace(model="Qwen/Qwen2.5-VL-3B-Instruct", mmmu_accuracy=0.4),
# SimpleNamespace(model="openbmb/MiniCPM-V-2_6", mmmu_accuracy=0.4), # temporarily disabled: NaN in next_token_logits
]
class TestVLMModels(MMMUMultiModelTestBase):
def test_vlm_mmmu_benchmark(self):
"""Test VLM models against MMMU benchmark."""
models_to_test = MODELS
if is_in_ci():
models_to_test = [random.choice(MODELS)]
for model in models_to_test:
# Use a unique temporary directory for each model to avoid cached results
with tempfile.TemporaryDirectory(
prefix=f"test_vlm_mmmu_{model.model.replace('/', '_')}_"
) as temp_dir:
# On AMD CI, the aiter greedy_sample kernel returns an out-of-range
# token id (== vocab_size) for degenerate (all-NaN / all -inf) logit
# rows, producing empty completions that crash the MMMU eval. Disable
# it there so greedy sampling falls back to torch.argmax.
custom_env = None
if is_in_amd_ci():
custom_env = {"SGLANG_DISABLE_AITER_GREEDY_SAMPLE": "1"}
self._run_vlm_mmmu_test(model, temp_dir, custom_env=custom_env)
if __name__ == "__main__":
unittest.main()