Yukim1andHongsheng Liu
4b66f62e10
Signed-off-by: zwhzzz0821 <2831474076@qq.com> Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com> Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
80 lines
2.3 KiB
Python
80 lines
2.3 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 offline tests for OmniVoice TTS model with text input and audio output.
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Uses GPUGenerationWorker for both stages (iterative unmasking + DAC decoder).
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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 numpy as np
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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 OmniRunner
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from tests.helpers.stage_config import get_deploy_config_path
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MODEL = "k2-fsa/OmniVoice"
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DEPLOY_CONFIG = get_deploy_config_path("omnivoice.yaml")
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# OmniRunner tuple: model, deploy config path, extra Omni kwargs.
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_OMNI_RUNNER_PARAM = (
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MODEL,
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DEPLOY_CONFIG,
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{
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"trust_remote_code": True,
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"log_stats": True,
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},
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)
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pytestmark = [
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pytest.mark.slow,
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pytest.mark.tts,
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pytest.mark.parametrize("omni_runner", [_OMNI_RUNNER_PARAM], indirect=True),
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]
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@hardware_test(res={"cuda": "L4"}, num_cards=1)
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def test_omnivoice_text_to_audio(omni_runner: OmniRunner) -> None:
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"""
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Test OmniVoice text-to-audio generation via offline Omni runner.
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Deploy Setting: omnivoice.yaml (enforce_eager=true)
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Input Modal: text
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Output Modal: audio
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"""
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from vllm_omni.inputs.data import OmniDiffusionSamplingParams
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prompts = {"prompt": "Hello, this is a test for text to audio."}
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sampling_params_list = [OmniDiffusionSamplingParams()]
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outputs = list(omni_runner.omni.generate(prompts, sampling_params_list=sampling_params_list))
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assert len(outputs) > 0, "No outputs generated"
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# Check final output has audio
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final_output = outputs[-1]
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ro = final_output
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assert ro is not None, "No request_output"
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mm = getattr(ro, "multimodal_output", None)
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if not mm and ro.outputs:
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mm = getattr(ro.outputs[0], "multimodal_output", None)
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assert mm is not None, "No multimodal_output"
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assert "audio" in mm, f"No 'audio' key in multimodal_output: {mm.keys()}"
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audio = mm["audio"]
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if isinstance(audio, np.ndarray):
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audio_np = audio
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else:
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audio_np = audio.cpu().numpy().squeeze()
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assert audio_np.size > 0, "Audio output is empty"
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rms = np.sqrt(np.mean(audio_np**2))
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assert rms > 0.01, f"Audio RMS too low ({rms:.4f}), likely silence"
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print(f"Generated audio: {len(audio_np) / 24000:.2f}s, rms={rms:.4f}")
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