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