[Test] Add initial multi modal cases of Qwen2.5-VL-7B-Instruct for disaggregated encoder (#5301)
### What this PR does / why we need it? This PR adds disaggregated encoder tests for Qwen2.5-VL-7B-Instruct ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? by running the test by running ci - vLLM version: release/v0.12.0 --------- Signed-off-by: wangyu31577 <wangyu31577@hundsun.com> Signed-off-by: wangyu <53896905+yenuo26@users.noreply.github.com> Co-authored-by: wangyu31577 <wangyu31577@hundsun.com>
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tests/e2e/multicard/2-cards/test_disaggregated_encoder.py
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tests/e2e/multicard/2-cards/test_disaggregated_encoder.py
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# Copyright 2023 The vLLM team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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#
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import pytest
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from vllm.utils.network_utils import get_open_port
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from tests.e2e.conftest import DisaggEpdProxy, RemoteEPDServer
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from tools.send_mm_request import send_image_request
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MODELS = [
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"Qwen/Qwen2.5-VL-7B-Instruct",
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]
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SHARED_STORAGE_PATH = "/dev/shm/epd/storage"
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TENSOR_PARALLELS = [1]
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@pytest.mark.asyncio
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@pytest.mark.parametrize("model", MODELS)
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@pytest.mark.parametrize("tp_size", TENSOR_PARALLELS)
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async def test_models(model: str, tp_size: int) -> None:
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encode_port = get_open_port()
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pd_port = get_open_port()
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vllm_server_args = [
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[
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"--port",
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str(encode_port), "--model", model, "--gpu-memory-utilization",
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"0.01", "--tensor-parallel-size",
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str(tp_size), "--enforce-eager", "--no-enable-prefix-caching",
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"--max-model-len", "10000", "--max-num-batched-tokens", "10000",
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"--max-num-seqs", "1", "--ec-transfer-config",
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'{"ec_connector_extra_config":{"shared_storage_path":"' +
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SHARED_STORAGE_PATH +
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'"},"ec_connector":"ECExampleConnector","ec_role": "ec_producer"}'
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],
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[
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"--port",
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str(pd_port), "--model", model, "--gpu-memory-utilization", "0.95",
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"--tensor-parallel-size",
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str(tp_size), "--enforce-eager", "--max-model-len", "10000",
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"--max-num-batched-tokens", "10000", "--max-num-seqs", "128",
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"--ec-transfer-config",
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'{"ec_connector_extra_config":{"shared_storage_path":"' +
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SHARED_STORAGE_PATH +
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'"},"ec_connector":"ECExampleConnector","ec_role": "ec_consumer"}'
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]
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]
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proxy_port = get_open_port()
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proxy_args = [
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"--host", "127.0.0.1", "--port",
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str(proxy_port), "--encode-servers-urls",
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f"http://localhost:{encode_port}", "--decode-servers-urls",
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f"http://localhost:{pd_port}", "--prefill-servers-urls", "disable"
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]
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with RemoteEPDServer(vllm_serve_args=vllm_server_args) as _:
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with DisaggEpdProxy(proxy_args=proxy_args) as proxy:
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send_image_request(model, proxy)
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