wangyu
016861385f
Signed-off-by: wangyu <410167048@qq.com> Signed-off-by: [Your Name] <your.email@example.com> Signed-off-by: wangyu <53896905+yenuo26@users.noreply.github.com>
142 lines
4.3 KiB
Python
142 lines
4.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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E2E Online tests for Qwen3-TTS model with text input and audio output.
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These tests verify the /v1/audio/speech endpoint works correctly with
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actual model inference, not mocks.
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"""
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import os
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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import pytest
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from tests.helpers.mark import hardware_test
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from tests.helpers.runtime import OmniServerParams
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from tests.helpers.stage_config import (
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get_deploy_config_path,
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get_deploy_config_stage,
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modify_stage_config,
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)
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MODEL = "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice"
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_DEFAULT_STAGE_CONFIG = get_deploy_config_path("qwen3_tts.yaml")
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_STAGE_CONFIG = modify_stage_config(
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_DEFAULT_STAGE_CONFIG,
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updates={"stages": {0: {"default_sampling_params.max_tokens": 500}}},
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)
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def get_prompt(prompt_type="text"):
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"""Text prompt for text-to-audio tests (same as test_qwen3_omni - beijing test case)."""
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prompts = {
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"text": "Beijing, China's capital, blends ancient wonders like the Great Wall with modern marvels. This vibrant metropolis offers rich culture, delicious Peking duck, and endless exploration opportunities.",
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}
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return prompts.get(prompt_type, prompts["text"])
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def get_max_batch_size(size_type="few"):
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"""Batch size for concurrent requests (same as test_qwen3_omni)."""
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batch_sizes = {"few": 5, "medium": 100, "large": 256}
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return batch_sizes.get(size_type, 5)
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tts_server_params = [
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pytest.param(
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OmniServerParams(
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model=MODEL,
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stage_config_path=_STAGE_CONFIG,
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server_args=["--trust-remote-code"],
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),
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id="async_chunk",
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)
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]
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default_tts_server_params = [
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pytest.param(
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OmniServerParams(
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model=MODEL,
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stage_config_path=_DEFAULT_STAGE_CONFIG,
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server_args=["--trust-remote-code"],
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),
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id="async_chunk",
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)
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]
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@pytest.mark.core_model
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@pytest.mark.advanced_model
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@pytest.mark.tts
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@hardware_test(res={"cuda": "L4"}, num_cards=1)
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@pytest.mark.parametrize("omni_server", default_tts_server_params, indirect=True)
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def test_default_cuda_graph_startup(omni_server) -> None:
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"""Verify both stages start with the shipped CUDA Graph configuration.
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The fixture reaching this test is the smoke assertion: it waits for the
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server to become ready after both stages finish model initialization and
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CUDA Graph capture. The regression covered here exited during stage 1
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capture, before fixture setup could complete.
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"""
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for stage_id in (0, 1):
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stage = get_deploy_config_stage("qwen3_tts.yaml", stage_id=stage_id)
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assert stage.get("enforce_eager", False) is False
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assert omni_server.proc is not None
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assert omni_server.proc.poll() is None
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@pytest.mark.core_model
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@pytest.mark.advanced_model
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@pytest.mark.tts
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@hardware_test(res={"cuda": "L4", "npu": "A3"}, num_cards=1)
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@pytest.mark.parametrize("omni_server", tts_server_params, indirect=True)
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def test_text_to_audio_001(omni_server, openai_client) -> None:
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"""
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Test text input processing and audio output via OpenAI API.
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Deploy Setting: default yaml
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Input Modal: text
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Output Modal: audio
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Input Setting: stream=False
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Datasets: few requests
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"""
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request_config = {
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"model": omni_server.model,
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"input": get_prompt(),
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"stream": False,
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"response_format": "wav",
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"task_type": "CustomVoice",
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"voice": "vivian",
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}
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openai_client.send_audio_speech_request(request_config, request_num=get_max_batch_size())
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@pytest.mark.core_model
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@pytest.mark.advanced_model
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@pytest.mark.tts
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@hardware_test(res={"cuda": "L4", "npu": "A3"}, num_cards=1)
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@pytest.mark.parametrize("omni_server", tts_server_params, indirect=True)
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def test_text_to_audio_002(omni_server, openai_client) -> None:
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"""
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Test text input processing and audio output via OpenAI API.
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Deploy Setting: default yaml
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Input Modal: text
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Output Modal: audio
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Input Setting: stream=True
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Datasets: single request
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"""
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request_config = {
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"model": omni_server.model,
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"input": get_prompt(),
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"stream": True,
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"stream_format": "audio",
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"response_format": "wav",
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"task_type": "CustomVoice",
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"voice": "vivian",
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}
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openai_client.send_audio_speech_request(request_config)
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