0295eeb6f3
Signed-off-by: Asthenia <asthenia0412@gmail.com> Signed-off-by: Gao Han <hgaoaf@connect.ust.hk> Co-authored-by: Asthenia <asthenia0412@gmail.com> Co-authored-by: Gao Han <hgaoaf@connect.ust.hk>
78 lines
2.8 KiB
Python
78 lines
2.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
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"""Real EngineCore cache invalidation through the AsyncOmni control plane."""
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import pytest
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from PIL import Image
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from vllm import SamplingParams
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from tests.helpers.stage_config import get_deploy_config_path, modify_stage_config
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from vllm_omni.entrypoints.async_omni import AsyncOmni
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@pytest.mark.advanced_model
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@pytest.mark.omni
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@pytest.mark.cuda
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@pytest.mark.asyncio
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async def test_cache_resets_invalidate_real_engine_and_allow_repeated_multimodal_inputs():
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deploy_config = modify_stage_config(
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get_deploy_config_path("ci/qwen2_5_omni_thinker_only.yaml"),
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updates={
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"stages": {
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0: {
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"enable_prefix_caching": True,
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"mm_processor_cache_gb": 0.1,
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"max_model_len": 2048,
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"max_num_batched_tokens": 2048,
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"num_gpu_blocks_override": 256,
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"enforce_eager": True,
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}
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}
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},
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)
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engine = AsyncOmni(
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model="Qwen/Qwen2.5-Omni-7B",
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deploy_config=deploy_config,
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stage_init_timeout=600,
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)
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async def generate(prompt, request_id):
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final = None
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async for output in engine.generate(
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prompt,
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request_id=request_id,
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sampling_params_list=[SamplingParams(max_tokens=4, temperature=0)],
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):
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final = output
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assert final is not None and final.finished
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assert final.outputs and final.outputs[0].token_ids
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return final
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try:
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prompt = "Explain how a cache works. " * 40
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cold = await generate(prompt, "cold")
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warm = await generate(prompt, "warm")
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assert cold.num_cached_tokens == 0
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assert warm.num_cached_tokens > 0
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assert await engine.reset_prefix_cache(reset_running_requests=True, reset_connector=True)
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await engine.reset_encoder_cache()
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await engine.reset_mm_cache()
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reset = await generate(prompt, "reset")
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assert reset.num_cached_tokens == 0
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assert reset.outputs[0].token_ids == cold.outputs[0].token_ids
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image_prompt = {
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"prompt": "<|im_start|>user\n<|vision_start|><|IMAGE|><|vision_end|>Describe this image.<|im_end|>\n<|im_start|>assistant\n",
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"multi_modal_data": {"image": Image.new("RGB", (56, 56), "red")},
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}
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before = await generate(image_prompt, "image-before")
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await engine.reset_mm_cache()
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await engine.reset_encoder_cache()
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assert await engine.reset_prefix_cache()
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after = await generate(image_prompt, "image-after")
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assert after.outputs[0].token_ids == before.outputs[0].token_ids
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finally:
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engine.shutdown()
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