wehub-resource-sync
89 lines
3.0 KiB
Python
89 lines
3.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Msgpack roundtrip tests for OmniEngineCoreOutputs with multimodal_output.
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Validates that tensor-only payloads survive msgspec encode/decode and that
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non-tensor values fail decoding (enforcing the wire invariant).
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"""
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import pytest
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import torch
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from vllm.v1.serial_utils import MsgpackDecoder, MsgpackEncoder
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from vllm_omni.engine import OmniEngineCoreOutput, OmniEngineCoreOutputs
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pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
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def _roundtrip(outputs: OmniEngineCoreOutputs) -> OmniEngineCoreOutputs:
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encoder = MsgpackEncoder()
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encoded = encoder.encode(outputs)
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decoder = MsgpackDecoder(OmniEngineCoreOutputs)
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return decoder.decode(encoded)
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def test_tensor_only_roundtrip():
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"""Tensor-only multimodal_output survives msgpack roundtrip."""
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audio = torch.randn(16000)
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sr = torch.tensor(24000)
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eco = OmniEngineCoreOutput(
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request_id="req-1",
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new_token_ids=[1, 2, 3],
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finish_reason=None,
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multimodal_output={"audio": audio, "sr": sr},
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)
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decoded = _roundtrip(OmniEngineCoreOutputs(outputs=[eco]))
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assert len(decoded.outputs) == 1
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out = decoded.outputs[0]
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assert out.request_id == "req-1"
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assert isinstance(out.multimodal_output, dict)
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assert torch.allclose(out.multimodal_output["audio"], audio)
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assert out.multimodal_output["sr"].item() == 24000
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def test_empty_multimodal_roundtrip():
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"""None multimodal_output roundtrips correctly."""
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eco = OmniEngineCoreOutput(
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request_id="req-2",
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new_token_ids=[4],
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finish_reason=None,
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multimodal_output=None,
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)
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decoded = _roundtrip(OmniEngineCoreOutputs(outputs=[eco]))
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assert decoded.outputs[0].multimodal_output is None
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def test_multiple_tensor_keys_roundtrip():
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"""Multiple tensor keys survive roundtrip."""
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hidden = torch.randn(10, 4096)
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codes = torch.randint(0, 1024, (1, 100))
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eco = OmniEngineCoreOutput(
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request_id="req-3",
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new_token_ids=[],
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finish_reason=None,
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multimodal_output={"hidden": hidden, "codes": codes},
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)
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decoded = _roundtrip(OmniEngineCoreOutputs(outputs=[eco]))
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out = decoded.outputs[0]
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assert torch.allclose(out.multimodal_output["hidden"], hidden)
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assert torch.equal(out.multimodal_output["codes"], codes)
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def test_non_tensor_value_fails_decode():
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"""Non-tensor values in multimodal_output cause decode failure.
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This validates that the wire field must be tensor-only and that
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the _ensure_tensor_values boundary in model runners is necessary.
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"""
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eco = OmniEngineCoreOutput(
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request_id="req-bad",
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new_token_ids=[],
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finish_reason=None,
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multimodal_output={"audio": torch.randn(10), "sr": 24000}, # scalar!
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)
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encoder = MsgpackEncoder()
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encoded = encoder.encode(OmniEngineCoreOutputs(outputs=[eco]))
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decoder = MsgpackDecoder(OmniEngineCoreOutputs)
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with pytest.raises(Exception):
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decoder.decode(encoded)
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