vllm-omni/tests/e2e/offline_inference/test_stable_audio_model.py

import sys
from pathlib import Path

import numpy as np
import pytest
import torch

from vllm_omni.outputs import OmniRequestOutput

# ruff: noqa: E402
REPO_ROOT = Path(__file__).resolve().parents[2]
if str(REPO_ROOT) not in sys.path:
    sys.path.insert(0, str(REPO_ROOT))

from vllm_omni import Omni

# Use random weights model for CI testing (small, no authentication required)
models = ["linyueqian/stable_audio_random"]


@pytest.mark.parametrize("model_name", models)
def test_stable_audio_model(model_name: str):
    m = Omni(model=model_name)

    # Use minimal settings for testing
    # Generate a short 2-second audio clip with minimal inference steps
    audio_start_in_s = 0.0
    audio_end_in_s = 2.0  # Short duration for fast testing
    sample_rate = 44100  # Stable Audio uses 44100 Hz

    outputs = m.generate(
        "The sound of a dog barking",
        negative_prompt="Low quality.",
        num_inference_steps=4,  # Minimal steps for speed
        guidance_scale=7.0,
        generator=torch.Generator("cuda").manual_seed(42),
        num_outputs_per_prompt=1,
        extra={
            "audio_start_in_s": audio_start_in_s,
            "audio_end_in_s": audio_end_in_s,
        },
    )

    # Extract audio from OmniRequestOutput
    assert outputs is not None
    first_output = outputs[0]
    assert first_output.final_output_type == "image"  # Generic output type
    assert hasattr(first_output, "request_output") and first_output.request_output

    req_out = first_output.request_output[0]
    assert isinstance(req_out, OmniRequestOutput)
    assert hasattr(req_out, "images") and len(req_out.images) >= 1

    # For stable audio, the "images" field contains audio numpy arrays
    audio = req_out.images[0]
    assert isinstance(audio, np.ndarray)
    # audio shape: (batch, channels, samples)
    # For stable-audio-open-1.0: sample_rate=44100, so 2 seconds = 88200 samples
    assert audio.ndim == 3
    assert audio.shape[0] == 1  # batch size
    assert audio.shape[1] == 2  # stereo channels
    expected_samples = int((audio_end_in_s - audio_start_in_s) * sample_rate)
    assert audio.shape[2] == expected_samples  # 88200 samples for 2 seconds