Merge branch 'main' into dev/vllm-align

This commit is contained in:
Gao Han authored and GitHub committed 2026-09-10 11:23:08 +08:00
commit 0ae9bdd8c2
54 files changed
+1659 -500

No files matched your search

@@ -166,6 +166,56 @@ def test_moss_tts_seed_falls_back_to_stage_default(adapter_cls, mocker):
assert prepared.tts_params["seed"] == [42]
@pytest.mark.parametrize(
"variant,ref_text,mode",
[
("local", " Reference. ", "continuation"),
("local", None, "generation"),
("local", " ", "generation"),
("tts", "Reference.", "generation"),
],
)
def test_moss_reference_transcript_mode(variant, ref_text, mode, mocker):
import torch
reference = [torch.ones((3, 12), dtype=torch.int64)]
unified = torch.arange(52, dtype=torch.int64).reshape(1, 4, 13)
processor = mocker.Mock(return_value={"input_ids": unified})
server = mocker.Mock(_moss_variant="local", uploaded_speakers={"speaker": {}})
server._voice_created_at.return_value = 123
request = OpenAICreateSpeechRequest(
input="Target.", ref_text=ref_text, language="English", voice="Speaker", seed=0, max_new_tokens=2048
)
adapter = MossTTSAdapter(SpeechServingContext(server=server))
adapter._moss_variant = variant
mocker.patch.object(adapter, "_get_moss_processor", return_value=processor)
mocker.patch.object(
adapter, "_encode_moss_references", new=mocker.AsyncMock(return_value=(reference, {0: "reference-key"}))
)
prepared = asyncio.run(adapter.build(request, [], has_inline_ref_audio=False))
if mode == "continuation":
processor.build_user_message.assert_called_once_with(text="Reference. Target.", language="English")
processor.build_assistant_message.assert_called_once_with(audio_codes_list=reference)
conversation = [processor.build_user_message.return_value, processor.build_assistant_message.return_value]
else:
processor.build_user_message.assert_called_once_with(text="Target.", language="English", reference=reference)
processor.build_assistant_message.assert_not_called()
conversation = [processor.build_user_message.return_value]
processor.assert_called_once_with(conversations=[conversation], mode=mode)
assert prepared.prompt["prompt_token_ids"] == unified[0, :, 0].tolist()
assert torch.equal(prepared.tts_params["codes"]["ref"], unified[0, :, 1:])
assert prepared.tts_params["max_new_frames"] == [2048]
assert prepared.tts_params["ref_audio_cache_key"] == "reference-key"
assert prepared.tts_params["voice_name"] == ["speaker"]
assert prepared.tts_params["voice_created_at"] == [123]
assert prepared.tts_params["seed"] == [0]
assert prepared.prompt["cache_salt"]
assert request.input == "Target."
def test_qwen3_tts_metadata():
assert Qwen3TTSAdapter.backend == "ar"
assert issubclass(Qwen3TTSAdapter, ARTTSAdapter)
+25 -1
View File
@@ -1,3 +1,6 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
from __future__ import annotations
import queue
@@ -97,9 +100,11 @@ class FakeAsyncOmniEngine:
) -> None:
self.model = model
self.config_path = None
self.stage_configs: list[Any] = []
self.stage_metadata = stage_metadata or [THREE_STAGE_META[-1]]
self.num_stages = len(self.stage_metadata)
self.stage_configs = [
StageConfig(stage_id=i, model_stage="dummy-model").to_omegaconf() for i in range(self.num_stages)
]
self.default_sampling_params_list = default_sampling_params_list or [
SamplingParams(max_tokens=8) for _ in range(self.num_stages)
]
@@ -222,6 +227,25 @@ def test_resolve_sampling_params_list_preserves_stage_constraints():
assert caller_params.stop_token_ids == [7]
@pytest.mark.parametrize("use_defaults", [False, True])
def test_moss_local_output_policy_preserves_codec_streaming(use_defaults):
from vllm_omni.model_executor.models.moss_tts.pipeline import MOSS_TTS_LOCAL_PIPELINE
base = _make_base()
base.engine.num_stages = 2
base.sampling_constraints_list = [stage.sampling_constraints for stage in MOSS_TTS_LOCAL_PIPELINE.stages]
base.default_sampling_params_list = [
base._apply_sampling_constraints(SamplingParams(), constraints)
for constraints in base.sampling_constraints_list
]
caller = [SamplingParams(output_kind=RequestOutputKind.DELTA) for _ in range(2)]
result = base.resolve_sampling_params_list(None if use_defaults else caller, allow_delta_coercion=True)
assert [params.output_kind for params in result] == [RequestOutputKind.FINAL_ONLY, RequestOutputKind.DELTA]
assert all(params.output_kind == RequestOutputKind.DELTA for params in caller)
assert base.default_sampling_params_list[0].output_kind == RequestOutputKind.FINAL_ONLY
def _stage_spec(
stage_id: int,
*,