Files
vllm-omni/tests/inputs/test_mm_processor.py
T
tzhouam efda9369a8 refactor: reduce copied vLLM 0.29 compatibility code
Reuse upstream weight mapping and multimodal processing, consolidate Omni processor bridges, and trim unused Hunyuan internals. Route no-media kwargs through the active renderer and preserve GLM generation prompt formatting.

Validation: 453 CPU tests passed, 7 skipped; processor imports, Ruff, and diff checks passed. GPU and end-to-end CI not rerun.
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
2026-09-10 00:41:53 +08:00

45 lines
1.7 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
from types import SimpleNamespace
from unittest.mock import Mock
import pytest
from transformers import BatchFeature
from vllm_omni.inputs.mm_processor import OmniMultiModalProcessor
pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
@pytest.mark.parametrize("counts", [{}, {"audio": 1, "image": 0}])
@pytest.mark.parametrize("original_text", [None, "", "voice cloning text"])
def test_custom_processor_bridge_preserves_prompt_kwargs_and_passthrough(counts, original_text):
class Processor(OmniMultiModalProcessor):
def _get_mm_fields_config(self, *args):
return {}
def _get_prompt_updates(self, *args):
return []
processor = object.__new__(Processor)
processor.dummy_inputs = SimpleNamespace(get_dummy_text=Mock(return_value="dummy"))
processor._get_hf_mm_data = Mock(return_value=({"audios": ["wave"]}, {"embedding": "preserve"}))
processor._call_hf_processor = Mock(return_value=BatchFeature({"features": "processed"}))
items = Mock()
items.get_all_counts.return_value = counts
kwargs = {"sampling_rate": 16000}
if original_text is not None:
kwargs[processor._OMNI_PROMPT_TEXT_KEY] = original_text
before = dict(kwargs)
result = processor._apply_hf_processor_main(items, kwargs)
items.select.assert_called_once_with({k for k, v in counts.items() if v > 0})
processor._call_hf_processor.assert_called_once_with(
"dummy" if original_text is None else original_text,
{"audios": ["wave"]},
{"sampling_rate": 16000},
{},
)
assert dict(result) == {"features": "processed", "embedding": "preserve"}
assert kwargs == before